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<h1><a href="dlp_v2.html">Sensitive Data Protection (DLP)</a> . <a href="dlp_v2.organizations.html">organizations</a> . <a href="dlp_v2.organizations.locations.html">locations</a> . <a href="dlp_v2.organizations.locations.jobTriggers.html">jobTriggers</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
  <code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
  <code><a href="#create">create(parent, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a job trigger to run DLP actions such as scanning storage for sensitive information on a set schedule. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.</p>
<p class="toc_element">
  <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes a job trigger. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.</p>
<p class="toc_element">
  <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Gets a job trigger. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.</p>
<p class="toc_element">
  <code><a href="#list">list(parent, filter=None, locationId=None, orderBy=None, pageSize=None, pageToken=None, type=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists job triggers. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.</p>
<p class="toc_element">
  <code><a href="#list_next">list_next()</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<p class="toc_element">
  <code><a href="#patch">patch(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Updates a job trigger. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.</p>
<h3>Method Details</h3>
<div class="method">
    <code class="details" id="close">close()</code>
  <pre>Close httplib2 connections.</pre>
</div>

<div class="method">
    <code class="details" id="create">create(parent, body=None, x__xgafv=None)</code>
  <pre>Creates a job trigger to run DLP actions such as scanning storage for sensitive information on a set schedule. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.

Args:
  parent: string, Required. Parent resource name. The format of this value varies depending on whether you have [specified a processing location](https://cloud.google.com/sensitive-data-protection/docs/specifying-location): + Projects scope, location specified: `projects/{project_id}/locations/{location_id}` + Projects scope, no location specified (defaults to global): `projects/{project_id}` The following example `parent` string specifies a parent project with the identifier `example-project`, and specifies the `europe-west3` location for processing data: parent=projects/example-project/locations/europe-west3 (required)
  body: object, The request body.
    The object takes the form of:

{ # Request message for CreateJobTrigger.
  &quot;jobTrigger&quot;: { # Contains a configuration to make API calls on a repeating basis. See https://cloud.google.com/sensitive-data-protection/docs/concepts-job-triggers to learn more. # Required. The JobTrigger to create.
    &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of a triggeredJob.
    &quot;description&quot;: &quot;A String&quot;, # User provided description (max 256 chars)
    &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 100 chars)
    &quot;errors&quot;: [ # Output only. A stream of errors encountered when the trigger was activated. Repeated errors may result in the JobTrigger automatically being paused. Will return the last 100 errors. Whenever the JobTrigger is modified this list will be cleared.
      { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
        &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
          &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
          &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
            {
              &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
            },
          ],
          &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
        },
        &quot;extraInfo&quot;: &quot;A String&quot;, # Additional information about the error.
        &quot;timestamps&quot;: [ # The times the error occurred. List includes the oldest timestamp and the last 9 timestamps.
          &quot;A String&quot;,
        ],
      },
    ],
    &quot;inspectJob&quot;: { # Controls what and how to inspect for findings. # For inspect jobs, a snapshot of the configuration.
      &quot;actions&quot;: [ # Actions to execute at the completion of the job.
        { # A task to execute on the completion of a job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-actions to learn more.
          &quot;deidentify&quot;: { # Create a de-identified copy of a storage bucket. Only compatible with Cloud Storage buckets. A TransformationDetail will be created for each transformation. Compatible with: Inspection of Cloud Storage # Create a de-identified copy of the input data.
            &quot;cloudStorageOutput&quot;: &quot;A String&quot;, # Required. User settable Cloud Storage bucket and folders to store de-identified files. This field must be set for Cloud Storage deidentification. The output Cloud Storage bucket must be different from the input bucket. De-identified files will overwrite files in the output path. Form of: gs://bucket/folder/ or gs://bucket
            &quot;fileTypesToTransform&quot;: [ # List of user-specified file type groups to transform. If specified, only the files with these file types are transformed. If empty, all supported files are transformed. Supported types may be automatically added over time. Any unsupported file types that are set in this field are excluded from de-identification. An error is recorded for each unsupported file in the TransformationDetails output table. Currently the only file types supported are: IMAGES, TEXT_FILES, CSV, TSV.
              &quot;A String&quot;,
            ],
            &quot;transformationConfig&quot;: { # User specified templates and configs for how to deidentify structured, unstructures, and image files. User must provide either a unstructured deidentify template or at least one redact image config. # User specified deidentify templates and configs for structured, unstructured, and image files.
              &quot;deidentifyTemplate&quot;: &quot;A String&quot;, # De-identify template. If this template is specified, it will serve as the default de-identify template. This template cannot contain `record_transformations` since it can be used for unstructured content such as free-form text files. If this template is not set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify unstructured content.
              &quot;imageRedactTemplate&quot;: &quot;A String&quot;, # Image redact template. If this template is specified, it will serve as the de-identify template for images. If this template is not set, all findings in the image will be redacted with a black box.
              &quot;structuredDeidentifyTemplate&quot;: &quot;A String&quot;, # Structured de-identify template. If this template is specified, it will serve as the de-identify template for structured content such as delimited files and tables. If this template is not set but the `deidentify_template` is set, then `deidentify_template` will also apply to the structured content. If neither template is set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify structured content.
            },
            &quot;transformationDetailsStorageConfig&quot;: { # Config for storing transformation details. # Config for storing transformation details. This field specifies the configuration for storing detailed metadata about each transformation performed during a de-identification process. The metadata is stored separately from the de-identified content itself and provides a granular record of both successful transformations and any failures that occurred. Enabling this configuration is essential for users who need to access comprehensive information about the status, outcome, and specifics of each transformation. The details are captured in the TransformationDetails message for each operation. Key use cases: * **Auditing and compliance** * Provides a verifiable audit trail of de-identification activities, which is crucial for meeting regulatory requirements and internal data governance policies. * Logs what data was transformed, what transformations were applied, when they occurred, and their success status. This helps demonstrate accountability and due diligence in protecting sensitive data. * **Troubleshooting and debugging** * Offers detailed error messages and context if a transformation fails. This information is useful for diagnosing and resolving issues in the de-identification pipeline. * Helps pinpoint the exact location and nature of failures, speeding up the debugging process. * **Process verification and quality assurance** * Allows users to confirm that de-identification rules and transformations were applied correctly and consistently across the dataset as intended. * Helps in verifying the effectiveness of the chosen de-identification strategies. * **Data lineage and impact analysis** * Creates a record of how data elements were modified, contributing to data lineage. This is useful for understanding the provenance of de-identified data. * Aids in assessing the potential impact of de-identification choices on downstream analytical processes or data usability. * **Reporting and operational insights** * You can analyze the metadata stored in a queryable BigQuery table to generate reports on transformation success rates, common error types, processing volumes (e.g., transformedBytes), and the types of transformations applied. * These insights can inform optimization of de-identification configurations and resource planning. To take advantage of these benefits, set this configuration. The stored details include a description of the transformation, success or error codes, error messages, the number of bytes transformed, the location of the transformed content, and identifiers for the job and source data.
              &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # The BigQuery table in which to store the output. This may be an existing table or in a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_transformation_details_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details.
                &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
              },
            },
          },
          &quot;jobNotificationEmails&quot;: { # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts). # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts).
          },
          &quot;pubSub&quot;: { # Publish a message into a given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a Pub/Sub topic.
            &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
          },
          &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Data Catalog. In Data Catalog, tag templates are applied to the resource that Cloud DLP scanned. Data Catalog tag templates are stored in the same project and region where the BigQuery table exists. For Cloud DLP to create and apply the tag template, the Cloud DLP service agent must have the `roles/datacatalog.tagTemplateOwner` permission on the project. The tag template contains fields summarizing the results of the DlpJob. Any field values previously written by another DlpJob are deleted. InfoType naming patterns are strictly enforced when using this feature. Findings are persisted in Data Catalog storage and are governed by service-specific policies for Data Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
          },
          &quot;publishFindingsToDataplexCatalog&quot;: { # Publish findings of a DlpJob to Dataplex Universal Catalog as a `sensitive-data-protection-job-result` aspect. For more information, see [Send inspection results to Dataplex Universal Catalog as aspects](https://cloud.google.com/sensitive-data-protection/docs/add-aspects-inspection-job). Aspects are stored in Dataplex Universal Catalog storage and are governed by service-specific policies for Dataplex Universal Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings as an aspect to Dataplex Universal Catalog.
          },
          &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to [Security Command Center](https://cloud.google.com/security-command-center). This action is available for only projects that belong to an organization. This action publishes the count of finding instances and their infoTypes. The summary of findings are persisted in Security Command Center and are governed by [service-specific policies for Security Command Center](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
          },
          &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
          },
          &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
            &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
              &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
              &quot;storagePath&quot;: { # Message representing a single file or path in Cloud Storage. # Store findings in an existing Cloud Storage bucket. Files will be generated with the job ID and file part number as the filename and will contain findings in textproto format as SaveToGcsFindingsOutput. The filename will follow the naming convention `-`. Example: `my-job-id-2`. Supported for Inspect jobs. The bucket must not be the same as the bucket being inspected. If storing findings to Cloud Storage, the output schema field should not be set. If set, it will be ignored.
                &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
              },
              &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
              },
            },
          },
        },
      ],
      &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
        &quot;contentOptions&quot;: [ # Deprecated and unused.
          &quot;A String&quot;,
        ],
        &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes to learn more.
          { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
            &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
              { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                  &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                    &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                    &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                  },
                  &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                    &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                    &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  },
                },
              },
            ],
            &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
              &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
              },
              &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                  &quot;A String&quot;,
                ],
              },
            },
            &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
            &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
            &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
            &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
              &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                42,
              ],
              &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
            },
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Sensitivity for this CustomInfoType. If this CustomInfoType extends an existing InfoType, the sensitivity here will take precedence over that of the original InfoType. If unset for a CustomInfoType, it will default to HIGH. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
              &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
              &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
            },
            &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
            },
          },
        ],
        &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings. This is not used for data profiling.
        &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote. This is not used for data profiling.
        &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose a default list of detectors to run, which may change over time. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
          { # Type of information detected by the API.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
          },
        ],
        &quot;limits&quot;: { # Configuration to control the number of findings returned for inspection. This is not used for de-identification or data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. # Configuration to control the number of findings returned. This is not used for data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. When set within an InspectJobConfig, the specified maximum values aren&#x27;t hard limits. If an inspection job reaches these limits, the job ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than these maximum values.
          &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
            { # Max findings configuration per infoType, per content item or long running DlpJob.
              &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                  &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                },
                &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
              },
              &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
            },
          ],
          &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that are returned for each item scanned. When set within an InspectContentRequest, this field is ignored. This value isn&#x27;t a hard limit. If the number of findings for an item reaches this limit, the inspection of that item ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns for the item can be multiple times higher than this value.
          &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that are returned per request or job. If you set this field in an InspectContentRequest, the resulting maximum value is the value that you set or 3,000, whichever is lower. This value isn&#x27;t a hard limit. If an inspection reaches this limit, the inspection ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than this value.
        },
        &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. The default is POSSIBLE. In general, the highest likelihood setting yields the fewest findings in results and the lowest chance of a false positive. For more information, see [Match likelihood](https://cloud.google.com/sensitive-data-protection/docs/likelihood).
        &quot;minLikelihoodPerInfoType&quot;: [ # Minimum likelihood per infotype. For each infotype, a user can specify a minimum likelihood. The system only returns a finding if its likelihood is above this threshold. If this field is not set, the system uses the InspectConfig min_likelihood.
          { # Configuration for setting a minimum likelihood per infotype. Used to customize the minimum likelihood level for specific infotypes in the request. For example, use this if you want to lower the precision for PERSON_NAME without lowering the precision for the other infotypes in the request.
            &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the likelihood threshold applies to. Only one likelihood per info_type should be provided. If InfoTypeLikelihood does not have an info_type, the configuration fails.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
            &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. This field is required or else the configuration fails.
          },
        ],
        &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
          { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
            &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
              { # Type of information detected by the API.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                  &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                },
                &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
              },
            ],
            &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
              { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                  &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                    &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                      &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
                    },
                    &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                      &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                        &quot;A String&quot;,
                      ],
                    },
                  },
                  &quot;excludeByHotword&quot;: { # The rule to exclude findings based on a hotword. For record inspection of tables, column names are considered hotwords. An example of this is to exclude a finding if it belongs to a BigQuery column that matches a specific pattern. # Drop if the hotword rule is contained in the proximate context. For tabular data, the context includes the column name.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The windowBefore property in proximity should be set to 1 if the hotword needs to be included in a column header.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                    },
                  },
                  &quot;excludeInfoTypes&quot;: { # List of excluded infoTypes. # Set of infoTypes for which findings would affect this rule.
                    &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                      { # Type of information detected by the API.
                        &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                        &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                          &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                        },
                        &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
                      },
                    ],
                  },
                  &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                  &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                },
                &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                  &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                    &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                    &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                  },
                  &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                    &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                    &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  },
                },
              },
            ],
          },
        ],
      },
      &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
      &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
        &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
          &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
          &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
          &quot;includedFields&quot;: [ # Limit scanning only to these fields. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
          &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
          &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig. Caution: A [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-sampling) is causing the `rowsLimitPercent` field to behave unexpectedly. We recommend using `rowsLimit` instead.
          &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
          &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
            &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
            &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
            &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
          },
        },
        &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Cloud Storage bucket. # Cloud Storage options.
          &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of `bytes_limit_per_file` and `bytes_limit_per_file_percent` can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
          &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
          &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
            &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
              &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
              &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                &quot;A String&quot;,
              ],
              &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                &quot;A String&quot;,
              ],
            },
            &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
          },
          &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
            &quot;A String&quot;,
          ],
          &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
          &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
        },
        &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
          &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
            &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
          },
          &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
            &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
            &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
          },
        },
        &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
          &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
          &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
            &quot;a_key&quot;: &quot;A String&quot;,
          },
          &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
            &quot;A String&quot;,
          ],
          &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
            &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
          },
        },
        &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Cloud Storage and BigQuery. # Configuration of the timespan of the items to include in scanning.
          &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger or the timespan end_time used in the last run of the JobTrigger. **For BigQuery** Inspect jobs triggered by automatic population will scan data that is at least three hours old when the job starts. This is because streaming buffer rows are not read during inspection and reading up to the current timestamp will result in skipped rows. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#recently-streamed-data) related to this operation.
          &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
          &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
          &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. **For BigQuery** If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. If your BigQuery table is [partitioned at ingestion time](https://cloud.google.com/bigquery/docs/partitioned-tables#ingestion_time), you can use any of the following pseudo-columns as your timestamp field. When used with Cloud DLP, these pseudo-column names are case sensitive. - `_PARTITIONTIME` - `_PARTITIONDATE` - `_PARTITION_LOAD_TIME` **For Datastore** If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-timespan) related to this operation.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        },
      },
    },
    &quot;lastRunTime&quot;: &quot;A String&quot;, # Output only. The timestamp of the last time this trigger executed.
    &quot;name&quot;: &quot;A String&quot;, # Unique resource name for the triggeredJob, assigned by the service when the triggeredJob is created, for example `projects/dlp-test-project/jobTriggers/53234423`.
    &quot;status&quot;: &quot;A String&quot;, # Required. A status for this trigger.
    &quot;triggers&quot;: [ # A list of triggers which will be OR&#x27;ed together. Only one in the list needs to trigger for a job to be started. The list may contain only a single Schedule trigger and must have at least one object.
      { # What event needs to occur for a new job to be started.
        &quot;manual&quot;: { # Job trigger option for hybrid jobs. Jobs must be manually created and finished. # For use with hybrid jobs. Jobs must be manually created and finished.
        },
        &quot;schedule&quot;: { # Schedule for inspect job triggers. # Create a job on a repeating basis based on the elapse of time.
          &quot;recurrencePeriodDuration&quot;: &quot;A String&quot;, # With this option a job is started on a regular periodic basis. For example: every day (86400 seconds). A scheduled start time will be skipped if the previous execution has not ended when its scheduled time occurs. This value must be set to a time duration greater than or equal to 1 day and can be no longer than 60 days.
        },
      },
    ],
    &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of a triggeredJob.
  },
  &quot;locationId&quot;: &quot;A String&quot;, # Deprecated. This field has no effect.
  &quot;triggerId&quot;: &quot;A String&quot;, # The trigger id can contain uppercase and lowercase letters, numbers, and hyphens; that is, it must match the regular expression: `[a-zA-Z\d-_]+`. The maximum length is 100 characters. Can be empty to allow the system to generate one.
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Contains a configuration to make API calls on a repeating basis. See https://cloud.google.com/sensitive-data-protection/docs/concepts-job-triggers to learn more.
  &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of a triggeredJob.
  &quot;description&quot;: &quot;A String&quot;, # User provided description (max 256 chars)
  &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 100 chars)
  &quot;errors&quot;: [ # Output only. A stream of errors encountered when the trigger was activated. Repeated errors may result in the JobTrigger automatically being paused. Will return the last 100 errors. Whenever the JobTrigger is modified this list will be cleared.
    { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
      &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
        &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
        &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
          {
            &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
          },
        ],
        &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
      },
      &quot;extraInfo&quot;: &quot;A String&quot;, # Additional information about the error.
      &quot;timestamps&quot;: [ # The times the error occurred. List includes the oldest timestamp and the last 9 timestamps.
        &quot;A String&quot;,
      ],
    },
  ],
  &quot;inspectJob&quot;: { # Controls what and how to inspect for findings. # For inspect jobs, a snapshot of the configuration.
    &quot;actions&quot;: [ # Actions to execute at the completion of the job.
      { # A task to execute on the completion of a job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-actions to learn more.
        &quot;deidentify&quot;: { # Create a de-identified copy of a storage bucket. Only compatible with Cloud Storage buckets. A TransformationDetail will be created for each transformation. Compatible with: Inspection of Cloud Storage # Create a de-identified copy of the input data.
          &quot;cloudStorageOutput&quot;: &quot;A String&quot;, # Required. User settable Cloud Storage bucket and folders to store de-identified files. This field must be set for Cloud Storage deidentification. The output Cloud Storage bucket must be different from the input bucket. De-identified files will overwrite files in the output path. Form of: gs://bucket/folder/ or gs://bucket
          &quot;fileTypesToTransform&quot;: [ # List of user-specified file type groups to transform. If specified, only the files with these file types are transformed. If empty, all supported files are transformed. Supported types may be automatically added over time. Any unsupported file types that are set in this field are excluded from de-identification. An error is recorded for each unsupported file in the TransformationDetails output table. Currently the only file types supported are: IMAGES, TEXT_FILES, CSV, TSV.
            &quot;A String&quot;,
          ],
          &quot;transformationConfig&quot;: { # User specified templates and configs for how to deidentify structured, unstructures, and image files. User must provide either a unstructured deidentify template or at least one redact image config. # User specified deidentify templates and configs for structured, unstructured, and image files.
            &quot;deidentifyTemplate&quot;: &quot;A String&quot;, # De-identify template. If this template is specified, it will serve as the default de-identify template. This template cannot contain `record_transformations` since it can be used for unstructured content such as free-form text files. If this template is not set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify unstructured content.
            &quot;imageRedactTemplate&quot;: &quot;A String&quot;, # Image redact template. If this template is specified, it will serve as the de-identify template for images. If this template is not set, all findings in the image will be redacted with a black box.
            &quot;structuredDeidentifyTemplate&quot;: &quot;A String&quot;, # Structured de-identify template. If this template is specified, it will serve as the de-identify template for structured content such as delimited files and tables. If this template is not set but the `deidentify_template` is set, then `deidentify_template` will also apply to the structured content. If neither template is set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify structured content.
          },
          &quot;transformationDetailsStorageConfig&quot;: { # Config for storing transformation details. # Config for storing transformation details. This field specifies the configuration for storing detailed metadata about each transformation performed during a de-identification process. The metadata is stored separately from the de-identified content itself and provides a granular record of both successful transformations and any failures that occurred. Enabling this configuration is essential for users who need to access comprehensive information about the status, outcome, and specifics of each transformation. The details are captured in the TransformationDetails message for each operation. Key use cases: * **Auditing and compliance** * Provides a verifiable audit trail of de-identification activities, which is crucial for meeting regulatory requirements and internal data governance policies. * Logs what data was transformed, what transformations were applied, when they occurred, and their success status. This helps demonstrate accountability and due diligence in protecting sensitive data. * **Troubleshooting and debugging** * Offers detailed error messages and context if a transformation fails. This information is useful for diagnosing and resolving issues in the de-identification pipeline. * Helps pinpoint the exact location and nature of failures, speeding up the debugging process. * **Process verification and quality assurance** * Allows users to confirm that de-identification rules and transformations were applied correctly and consistently across the dataset as intended. * Helps in verifying the effectiveness of the chosen de-identification strategies. * **Data lineage and impact analysis** * Creates a record of how data elements were modified, contributing to data lineage. This is useful for understanding the provenance of de-identified data. * Aids in assessing the potential impact of de-identification choices on downstream analytical processes or data usability. * **Reporting and operational insights** * You can analyze the metadata stored in a queryable BigQuery table to generate reports on transformation success rates, common error types, processing volumes (e.g., transformedBytes), and the types of transformations applied. * These insights can inform optimization of de-identification configurations and resource planning. To take advantage of these benefits, set this configuration. The stored details include a description of the transformation, success or error codes, error messages, the number of bytes transformed, the location of the transformed content, and identifiers for the job and source data.
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # The BigQuery table in which to store the output. This may be an existing table or in a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_transformation_details_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
        &quot;jobNotificationEmails&quot;: { # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts). # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts).
        },
        &quot;pubSub&quot;: { # Publish a message into a given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a Pub/Sub topic.
          &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
        },
        &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Data Catalog. In Data Catalog, tag templates are applied to the resource that Cloud DLP scanned. Data Catalog tag templates are stored in the same project and region where the BigQuery table exists. For Cloud DLP to create and apply the tag template, the Cloud DLP service agent must have the `roles/datacatalog.tagTemplateOwner` permission on the project. The tag template contains fields summarizing the results of the DlpJob. Any field values previously written by another DlpJob are deleted. InfoType naming patterns are strictly enforced when using this feature. Findings are persisted in Data Catalog storage and are governed by service-specific policies for Data Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
        },
        &quot;publishFindingsToDataplexCatalog&quot;: { # Publish findings of a DlpJob to Dataplex Universal Catalog as a `sensitive-data-protection-job-result` aspect. For more information, see [Send inspection results to Dataplex Universal Catalog as aspects](https://cloud.google.com/sensitive-data-protection/docs/add-aspects-inspection-job). Aspects are stored in Dataplex Universal Catalog storage and are governed by service-specific policies for Dataplex Universal Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings as an aspect to Dataplex Universal Catalog.
        },
        &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to [Security Command Center](https://cloud.google.com/security-command-center). This action is available for only projects that belong to an organization. This action publishes the count of finding instances and their infoTypes. The summary of findings are persisted in Security Command Center and are governed by [service-specific policies for Security Command Center](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
        },
        &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
        },
        &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
          &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
            &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
            &quot;storagePath&quot;: { # Message representing a single file or path in Cloud Storage. # Store findings in an existing Cloud Storage bucket. Files will be generated with the job ID and file part number as the filename and will contain findings in textproto format as SaveToGcsFindingsOutput. The filename will follow the naming convention `-`. Example: `my-job-id-2`. Supported for Inspect jobs. The bucket must not be the same as the bucket being inspected. If storing findings to Cloud Storage, the output schema field should not be set. If set, it will be ignored.
              &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
      },
    ],
    &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
      &quot;contentOptions&quot;: [ # Deprecated and unused.
        &quot;A String&quot;,
      ],
      &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes to learn more.
        { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
          &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
            { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
              &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
                &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                  &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                  &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                },
                &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                  &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                },
              },
            },
          ],
          &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
            &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
              &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
            },
            &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
              &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                &quot;A String&quot;,
              ],
            },
          },
          &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
          &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
          },
          &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
          &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
            &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
              42,
            ],
            &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
          },
          &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Sensitivity for this CustomInfoType. If this CustomInfoType extends an existing InfoType, the sensitivity here will take precedence over that of the original InfoType. If unset for a CustomInfoType, it will default to HIGH. This only applies to data profiling.
            &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
          },
          &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
            &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
            &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
          },
          &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
          },
        },
      ],
      &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings. This is not used for data profiling.
      &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote. This is not used for data profiling.
      &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose a default list of detectors to run, which may change over time. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
        { # Type of information detected by the API.
          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
          &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
            &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
          },
          &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
        },
      ],
      &quot;limits&quot;: { # Configuration to control the number of findings returned for inspection. This is not used for de-identification or data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. # Configuration to control the number of findings returned. This is not used for data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. When set within an InspectJobConfig, the specified maximum values aren&#x27;t hard limits. If an inspection job reaches these limits, the job ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than these maximum values.
        &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
          { # Max findings configuration per infoType, per content item or long running DlpJob.
            &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
            &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
          },
        ],
        &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that are returned for each item scanned. When set within an InspectContentRequest, this field is ignored. This value isn&#x27;t a hard limit. If the number of findings for an item reaches this limit, the inspection of that item ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns for the item can be multiple times higher than this value.
        &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that are returned per request or job. If you set this field in an InspectContentRequest, the resulting maximum value is the value that you set or 3,000, whichever is lower. This value isn&#x27;t a hard limit. If an inspection reaches this limit, the inspection ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than this value.
      },
      &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. The default is POSSIBLE. In general, the highest likelihood setting yields the fewest findings in results and the lowest chance of a false positive. For more information, see [Match likelihood](https://cloud.google.com/sensitive-data-protection/docs/likelihood).
      &quot;minLikelihoodPerInfoType&quot;: [ # Minimum likelihood per infotype. For each infotype, a user can specify a minimum likelihood. The system only returns a finding if its likelihood is above this threshold. If this field is not set, the system uses the InspectConfig min_likelihood.
        { # Configuration for setting a minimum likelihood per infotype. Used to customize the minimum likelihood level for specific infotypes in the request. For example, use this if you want to lower the precision for PERSON_NAME without lowering the precision for the other infotypes in the request.
          &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the likelihood threshold applies to. Only one likelihood per info_type should be provided. If InfoTypeLikelihood does not have an info_type, the configuration fails.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
          },
          &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. This field is required or else the configuration fails.
        },
      ],
      &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
        { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
          &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
          ],
          &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
            { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
              &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                  &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                    &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
                  },
                  &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                    &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                      &quot;A String&quot;,
                    ],
                  },
                },
                &quot;excludeByHotword&quot;: { # The rule to exclude findings based on a hotword. For record inspection of tables, column names are considered hotwords. An example of this is to exclude a finding if it belongs to a BigQuery column that matches a specific pattern. # Drop if the hotword rule is contained in the proximate context. For tabular data, the context includes the column name.
                  &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The windowBefore property in proximity should be set to 1 if the hotword needs to be included in a column header.
                    &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                    &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  },
                },
                &quot;excludeInfoTypes&quot;: { # List of excluded infoTypes. # Set of infoTypes for which findings would affect this rule.
                  &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                    { # Type of information detected by the API.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                      &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                        &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                      },
                      &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
                    },
                  ],
                },
                &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
              },
              &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
                &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                  &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                  &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                },
                &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                  &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                },
              },
            },
          ],
        },
      ],
    },
    &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
    &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
      &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
        &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;includedFields&quot;: [ # Limit scanning only to these fields. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
        &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig. Caution: A [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-sampling) is causing the `rowsLimitPercent` field to behave unexpectedly. We recommend using `rowsLimit` instead.
        &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
        &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
          &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
          &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
          &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
        },
      },
      &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Cloud Storage bucket. # Cloud Storage options.
        &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of `bytes_limit_per_file` and `bytes_limit_per_file_percent` can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
        &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
        &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
          &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
            &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
            &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
              &quot;A String&quot;,
            ],
            &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
              &quot;A String&quot;,
            ],
          },
          &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
        },
        &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
          &quot;A String&quot;,
        ],
        &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
        &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
      },
      &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
        &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
          &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
        },
        &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
          &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
          &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
        },
      },
      &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
        &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
        &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
          &quot;a_key&quot;: &quot;A String&quot;,
        },
        &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
          &quot;A String&quot;,
        ],
        &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
          &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
        },
      },
      &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Cloud Storage and BigQuery. # Configuration of the timespan of the items to include in scanning.
        &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger or the timespan end_time used in the last run of the JobTrigger. **For BigQuery** Inspect jobs triggered by automatic population will scan data that is at least three hours old when the job starts. This is because streaming buffer rows are not read during inspection and reading up to the current timestamp will result in skipped rows. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#recently-streamed-data) related to this operation.
        &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
        &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
        &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. **For BigQuery** If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. If your BigQuery table is [partitioned at ingestion time](https://cloud.google.com/bigquery/docs/partitioned-tables#ingestion_time), you can use any of the following pseudo-columns as your timestamp field. When used with Cloud DLP, these pseudo-column names are case sensitive. - `_PARTITIONTIME` - `_PARTITIONDATE` - `_PARTITION_LOAD_TIME` **For Datastore** If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-timespan) related to this operation.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
    },
  },
  &quot;lastRunTime&quot;: &quot;A String&quot;, # Output only. The timestamp of the last time this trigger executed.
  &quot;name&quot;: &quot;A String&quot;, # Unique resource name for the triggeredJob, assigned by the service when the triggeredJob is created, for example `projects/dlp-test-project/jobTriggers/53234423`.
  &quot;status&quot;: &quot;A String&quot;, # Required. A status for this trigger.
  &quot;triggers&quot;: [ # A list of triggers which will be OR&#x27;ed together. Only one in the list needs to trigger for a job to be started. The list may contain only a single Schedule trigger and must have at least one object.
    { # What event needs to occur for a new job to be started.
      &quot;manual&quot;: { # Job trigger option for hybrid jobs. Jobs must be manually created and finished. # For use with hybrid jobs. Jobs must be manually created and finished.
      },
      &quot;schedule&quot;: { # Schedule for inspect job triggers. # Create a job on a repeating basis based on the elapse of time.
        &quot;recurrencePeriodDuration&quot;: &quot;A String&quot;, # With this option a job is started on a regular periodic basis. For example: every day (86400 seconds). A scheduled start time will be skipped if the previous execution has not ended when its scheduled time occurs. This value must be set to a time duration greater than or equal to 1 day and can be no longer than 60 days.
      },
    },
  ],
  &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of a triggeredJob.
}</pre>
</div>

<div class="method">
    <code class="details" id="delete">delete(name, x__xgafv=None)</code>
  <pre>Deletes a job trigger. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.

Args:
  name: string, Required. Resource name of the project and the triggeredJob, for example `projects/dlp-test-project/jobTriggers/53234423`. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
}</pre>
</div>

<div class="method">
    <code class="details" id="get">get(name, x__xgafv=None)</code>
  <pre>Gets a job trigger. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.

Args:
  name: string, Required. Resource name of the project and the triggeredJob, for example `projects/dlp-test-project/jobTriggers/53234423`. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Contains a configuration to make API calls on a repeating basis. See https://cloud.google.com/sensitive-data-protection/docs/concepts-job-triggers to learn more.
  &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of a triggeredJob.
  &quot;description&quot;: &quot;A String&quot;, # User provided description (max 256 chars)
  &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 100 chars)
  &quot;errors&quot;: [ # Output only. A stream of errors encountered when the trigger was activated. Repeated errors may result in the JobTrigger automatically being paused. Will return the last 100 errors. Whenever the JobTrigger is modified this list will be cleared.
    { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
      &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
        &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
        &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
          {
            &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
          },
        ],
        &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
      },
      &quot;extraInfo&quot;: &quot;A String&quot;, # Additional information about the error.
      &quot;timestamps&quot;: [ # The times the error occurred. List includes the oldest timestamp and the last 9 timestamps.
        &quot;A String&quot;,
      ],
    },
  ],
  &quot;inspectJob&quot;: { # Controls what and how to inspect for findings. # For inspect jobs, a snapshot of the configuration.
    &quot;actions&quot;: [ # Actions to execute at the completion of the job.
      { # A task to execute on the completion of a job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-actions to learn more.
        &quot;deidentify&quot;: { # Create a de-identified copy of a storage bucket. Only compatible with Cloud Storage buckets. A TransformationDetail will be created for each transformation. Compatible with: Inspection of Cloud Storage # Create a de-identified copy of the input data.
          &quot;cloudStorageOutput&quot;: &quot;A String&quot;, # Required. User settable Cloud Storage bucket and folders to store de-identified files. This field must be set for Cloud Storage deidentification. The output Cloud Storage bucket must be different from the input bucket. De-identified files will overwrite files in the output path. Form of: gs://bucket/folder/ or gs://bucket
          &quot;fileTypesToTransform&quot;: [ # List of user-specified file type groups to transform. If specified, only the files with these file types are transformed. If empty, all supported files are transformed. Supported types may be automatically added over time. Any unsupported file types that are set in this field are excluded from de-identification. An error is recorded for each unsupported file in the TransformationDetails output table. Currently the only file types supported are: IMAGES, TEXT_FILES, CSV, TSV.
            &quot;A String&quot;,
          ],
          &quot;transformationConfig&quot;: { # User specified templates and configs for how to deidentify structured, unstructures, and image files. User must provide either a unstructured deidentify template or at least one redact image config. # User specified deidentify templates and configs for structured, unstructured, and image files.
            &quot;deidentifyTemplate&quot;: &quot;A String&quot;, # De-identify template. If this template is specified, it will serve as the default de-identify template. This template cannot contain `record_transformations` since it can be used for unstructured content such as free-form text files. If this template is not set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify unstructured content.
            &quot;imageRedactTemplate&quot;: &quot;A String&quot;, # Image redact template. If this template is specified, it will serve as the de-identify template for images. If this template is not set, all findings in the image will be redacted with a black box.
            &quot;structuredDeidentifyTemplate&quot;: &quot;A String&quot;, # Structured de-identify template. If this template is specified, it will serve as the de-identify template for structured content such as delimited files and tables. If this template is not set but the `deidentify_template` is set, then `deidentify_template` will also apply to the structured content. If neither template is set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify structured content.
          },
          &quot;transformationDetailsStorageConfig&quot;: { # Config for storing transformation details. # Config for storing transformation details. This field specifies the configuration for storing detailed metadata about each transformation performed during a de-identification process. The metadata is stored separately from the de-identified content itself and provides a granular record of both successful transformations and any failures that occurred. Enabling this configuration is essential for users who need to access comprehensive information about the status, outcome, and specifics of each transformation. The details are captured in the TransformationDetails message for each operation. Key use cases: * **Auditing and compliance** * Provides a verifiable audit trail of de-identification activities, which is crucial for meeting regulatory requirements and internal data governance policies. * Logs what data was transformed, what transformations were applied, when they occurred, and their success status. This helps demonstrate accountability and due diligence in protecting sensitive data. * **Troubleshooting and debugging** * Offers detailed error messages and context if a transformation fails. This information is useful for diagnosing and resolving issues in the de-identification pipeline. * Helps pinpoint the exact location and nature of failures, speeding up the debugging process. * **Process verification and quality assurance** * Allows users to confirm that de-identification rules and transformations were applied correctly and consistently across the dataset as intended. * Helps in verifying the effectiveness of the chosen de-identification strategies. * **Data lineage and impact analysis** * Creates a record of how data elements were modified, contributing to data lineage. This is useful for understanding the provenance of de-identified data. * Aids in assessing the potential impact of de-identification choices on downstream analytical processes or data usability. * **Reporting and operational insights** * You can analyze the metadata stored in a queryable BigQuery table to generate reports on transformation success rates, common error types, processing volumes (e.g., transformedBytes), and the types of transformations applied. * These insights can inform optimization of de-identification configurations and resource planning. To take advantage of these benefits, set this configuration. The stored details include a description of the transformation, success or error codes, error messages, the number of bytes transformed, the location of the transformed content, and identifiers for the job and source data.
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # The BigQuery table in which to store the output. This may be an existing table or in a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_transformation_details_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
        &quot;jobNotificationEmails&quot;: { # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts). # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts).
        },
        &quot;pubSub&quot;: { # Publish a message into a given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a Pub/Sub topic.
          &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
        },
        &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Data Catalog. In Data Catalog, tag templates are applied to the resource that Cloud DLP scanned. Data Catalog tag templates are stored in the same project and region where the BigQuery table exists. For Cloud DLP to create and apply the tag template, the Cloud DLP service agent must have the `roles/datacatalog.tagTemplateOwner` permission on the project. The tag template contains fields summarizing the results of the DlpJob. Any field values previously written by another DlpJob are deleted. InfoType naming patterns are strictly enforced when using this feature. Findings are persisted in Data Catalog storage and are governed by service-specific policies for Data Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
        },
        &quot;publishFindingsToDataplexCatalog&quot;: { # Publish findings of a DlpJob to Dataplex Universal Catalog as a `sensitive-data-protection-job-result` aspect. For more information, see [Send inspection results to Dataplex Universal Catalog as aspects](https://cloud.google.com/sensitive-data-protection/docs/add-aspects-inspection-job). Aspects are stored in Dataplex Universal Catalog storage and are governed by service-specific policies for Dataplex Universal Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings as an aspect to Dataplex Universal Catalog.
        },
        &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to [Security Command Center](https://cloud.google.com/security-command-center). This action is available for only projects that belong to an organization. This action publishes the count of finding instances and their infoTypes. The summary of findings are persisted in Security Command Center and are governed by [service-specific policies for Security Command Center](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
        },
        &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
        },
        &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
          &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
            &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
            &quot;storagePath&quot;: { # Message representing a single file or path in Cloud Storage. # Store findings in an existing Cloud Storage bucket. Files will be generated with the job ID and file part number as the filename and will contain findings in textproto format as SaveToGcsFindingsOutput. The filename will follow the naming convention `-`. Example: `my-job-id-2`. Supported for Inspect jobs. The bucket must not be the same as the bucket being inspected. If storing findings to Cloud Storage, the output schema field should not be set. If set, it will be ignored.
              &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
      },
    ],
    &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
      &quot;contentOptions&quot;: [ # Deprecated and unused.
        &quot;A String&quot;,
      ],
      &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes to learn more.
        { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
          &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
            { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
              &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
                &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                  &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                  &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                },
                &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                  &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                },
              },
            },
          ],
          &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
            &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
              &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
            },
            &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
              &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                &quot;A String&quot;,
              ],
            },
          },
          &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
          &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
          },
          &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
          &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
            &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
              42,
            ],
            &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
          },
          &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Sensitivity for this CustomInfoType. If this CustomInfoType extends an existing InfoType, the sensitivity here will take precedence over that of the original InfoType. If unset for a CustomInfoType, it will default to HIGH. This only applies to data profiling.
            &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
          },
          &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
            &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
            &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
          },
          &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
          },
        },
      ],
      &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings. This is not used for data profiling.
      &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote. This is not used for data profiling.
      &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose a default list of detectors to run, which may change over time. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
        { # Type of information detected by the API.
          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
          &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
            &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
          },
          &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
        },
      ],
      &quot;limits&quot;: { # Configuration to control the number of findings returned for inspection. This is not used for de-identification or data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. # Configuration to control the number of findings returned. This is not used for data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. When set within an InspectJobConfig, the specified maximum values aren&#x27;t hard limits. If an inspection job reaches these limits, the job ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than these maximum values.
        &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
          { # Max findings configuration per infoType, per content item or long running DlpJob.
            &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
            &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
          },
        ],
        &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that are returned for each item scanned. When set within an InspectContentRequest, this field is ignored. This value isn&#x27;t a hard limit. If the number of findings for an item reaches this limit, the inspection of that item ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns for the item can be multiple times higher than this value.
        &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that are returned per request or job. If you set this field in an InspectContentRequest, the resulting maximum value is the value that you set or 3,000, whichever is lower. This value isn&#x27;t a hard limit. If an inspection reaches this limit, the inspection ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than this value.
      },
      &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. The default is POSSIBLE. In general, the highest likelihood setting yields the fewest findings in results and the lowest chance of a false positive. For more information, see [Match likelihood](https://cloud.google.com/sensitive-data-protection/docs/likelihood).
      &quot;minLikelihoodPerInfoType&quot;: [ # Minimum likelihood per infotype. For each infotype, a user can specify a minimum likelihood. The system only returns a finding if its likelihood is above this threshold. If this field is not set, the system uses the InspectConfig min_likelihood.
        { # Configuration for setting a minimum likelihood per infotype. Used to customize the minimum likelihood level for specific infotypes in the request. For example, use this if you want to lower the precision for PERSON_NAME without lowering the precision for the other infotypes in the request.
          &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the likelihood threshold applies to. Only one likelihood per info_type should be provided. If InfoTypeLikelihood does not have an info_type, the configuration fails.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
          },
          &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. This field is required or else the configuration fails.
        },
      ],
      &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
        { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
          &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
          ],
          &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
            { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
              &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                  &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                    &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
                  },
                  &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                    &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                      &quot;A String&quot;,
                    ],
                  },
                },
                &quot;excludeByHotword&quot;: { # The rule to exclude findings based on a hotword. For record inspection of tables, column names are considered hotwords. An example of this is to exclude a finding if it belongs to a BigQuery column that matches a specific pattern. # Drop if the hotword rule is contained in the proximate context. For tabular data, the context includes the column name.
                  &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The windowBefore property in proximity should be set to 1 if the hotword needs to be included in a column header.
                    &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                    &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  },
                },
                &quot;excludeInfoTypes&quot;: { # List of excluded infoTypes. # Set of infoTypes for which findings would affect this rule.
                  &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                    { # Type of information detected by the API.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                      &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                        &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                      },
                      &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
                    },
                  ],
                },
                &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
              },
              &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
                &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                  &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                  &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                },
                &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                  &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                },
              },
            },
          ],
        },
      ],
    },
    &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
    &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
      &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
        &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;includedFields&quot;: [ # Limit scanning only to these fields. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
        &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig. Caution: A [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-sampling) is causing the `rowsLimitPercent` field to behave unexpectedly. We recommend using `rowsLimit` instead.
        &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
        &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
          &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
          &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
          &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
        },
      },
      &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Cloud Storage bucket. # Cloud Storage options.
        &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of `bytes_limit_per_file` and `bytes_limit_per_file_percent` can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
        &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
        &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
          &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
            &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
            &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
              &quot;A String&quot;,
            ],
            &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
              &quot;A String&quot;,
            ],
          },
          &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
        },
        &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
          &quot;A String&quot;,
        ],
        &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
        &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
      },
      &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
        &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
          &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
        },
        &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
          &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
          &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
        },
      },
      &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
        &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
        &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
          &quot;a_key&quot;: &quot;A String&quot;,
        },
        &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
          &quot;A String&quot;,
        ],
        &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
          &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
        },
      },
      &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Cloud Storage and BigQuery. # Configuration of the timespan of the items to include in scanning.
        &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger or the timespan end_time used in the last run of the JobTrigger. **For BigQuery** Inspect jobs triggered by automatic population will scan data that is at least three hours old when the job starts. This is because streaming buffer rows are not read during inspection and reading up to the current timestamp will result in skipped rows. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#recently-streamed-data) related to this operation.
        &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
        &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
        &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. **For BigQuery** If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. If your BigQuery table is [partitioned at ingestion time](https://cloud.google.com/bigquery/docs/partitioned-tables#ingestion_time), you can use any of the following pseudo-columns as your timestamp field. When used with Cloud DLP, these pseudo-column names are case sensitive. - `_PARTITIONTIME` - `_PARTITIONDATE` - `_PARTITION_LOAD_TIME` **For Datastore** If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-timespan) related to this operation.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
    },
  },
  &quot;lastRunTime&quot;: &quot;A String&quot;, # Output only. The timestamp of the last time this trigger executed.
  &quot;name&quot;: &quot;A String&quot;, # Unique resource name for the triggeredJob, assigned by the service when the triggeredJob is created, for example `projects/dlp-test-project/jobTriggers/53234423`.
  &quot;status&quot;: &quot;A String&quot;, # Required. A status for this trigger.
  &quot;triggers&quot;: [ # A list of triggers which will be OR&#x27;ed together. Only one in the list needs to trigger for a job to be started. The list may contain only a single Schedule trigger and must have at least one object.
    { # What event needs to occur for a new job to be started.
      &quot;manual&quot;: { # Job trigger option for hybrid jobs. Jobs must be manually created and finished. # For use with hybrid jobs. Jobs must be manually created and finished.
      },
      &quot;schedule&quot;: { # Schedule for inspect job triggers. # Create a job on a repeating basis based on the elapse of time.
        &quot;recurrencePeriodDuration&quot;: &quot;A String&quot;, # With this option a job is started on a regular periodic basis. For example: every day (86400 seconds). A scheduled start time will be skipped if the previous execution has not ended when its scheduled time occurs. This value must be set to a time duration greater than or equal to 1 day and can be no longer than 60 days.
      },
    },
  ],
  &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of a triggeredJob.
}</pre>
</div>

<div class="method">
    <code class="details" id="list">list(parent, filter=None, locationId=None, orderBy=None, pageSize=None, pageToken=None, type=None, x__xgafv=None)</code>
  <pre>Lists job triggers. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.

Args:
  parent: string, Required. Parent resource name. The format of this value varies depending on whether you have [specified a processing location](https://cloud.google.com/sensitive-data-protection/docs/specifying-location): + Projects scope, location specified: `projects/{project_id}/locations/{location_id}` + Projects scope, no location specified (defaults to global): `projects/{project_id}` The following example `parent` string specifies a parent project with the identifier `example-project`, and specifies the `europe-west3` location for processing data: parent=projects/example-project/locations/europe-west3 (required)
  filter: string, Allows filtering. Supported syntax: * Filter expressions are made up of one or more restrictions. * Restrictions can be combined by `AND` or `OR` logical operators. A sequence of restrictions implicitly uses `AND`. * A restriction has the form of `{field} {operator} {value}`. * Supported fields/values for inspect triggers: - `status` - HEALTHY|PAUSED|CANCELLED - `inspected_storage` - DATASTORE|CLOUD_STORAGE|BIGQUERY - &#x27;last_run_time` - RFC 3339 formatted timestamp, surrounded by quotation marks. Nanoseconds are ignored. - &#x27;error_count&#x27; - Number of errors that have occurred while running. * The operator must be `=` or `!=` for status and inspected_storage. The syntax is based on https://google.aip.dev/160. Examples: * inspected_storage = cloud_storage AND status = HEALTHY * inspected_storage = cloud_storage OR inspected_storage = bigquery * inspected_storage = cloud_storage AND (state = PAUSED OR state = HEALTHY) * last_run_time &gt; \&quot;2017-12-12T00:00:00+00:00\&quot; The length of this field should be no more than 500 characters.
  locationId: string, Deprecated. This field has no effect.
  orderBy: string, Comma-separated list of triggeredJob fields to order by, followed by `asc` or `desc` postfix. This list is case insensitive. The default sorting order is ascending. Redundant space characters are insignificant. Example: `name asc,update_time, create_time desc` Supported fields are: - `create_time`: corresponds to the time the JobTrigger was created. - `update_time`: corresponds to the time the JobTrigger was last updated. - `last_run_time`: corresponds to the last time the JobTrigger ran. - `name`: corresponds to the JobTrigger&#x27;s name. - `display_name`: corresponds to the JobTrigger&#x27;s display name. - `status`: corresponds to JobTrigger&#x27;s status.
  pageSize: integer, Size of the page. This value can be limited by a server.
  pageToken: string, Page token to continue retrieval. Comes from the previous call to ListJobTriggers. `order_by` field must not change for subsequent calls.
  type: string, The type of jobs. Will use `DlpJobType.INSPECT` if not set.
    Allowed values
      DLP_JOB_TYPE_UNSPECIFIED - Defaults to INSPECT_JOB.
      INSPECT_JOB - The job inspected Google Cloud for sensitive data.
      RISK_ANALYSIS_JOB - The job executed a Risk Analysis computation.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response message for ListJobTriggers.
  &quot;jobTriggers&quot;: [ # List of triggeredJobs, up to page_size in ListJobTriggersRequest.
    { # Contains a configuration to make API calls on a repeating basis. See https://cloud.google.com/sensitive-data-protection/docs/concepts-job-triggers to learn more.
      &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of a triggeredJob.
      &quot;description&quot;: &quot;A String&quot;, # User provided description (max 256 chars)
      &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 100 chars)
      &quot;errors&quot;: [ # Output only. A stream of errors encountered when the trigger was activated. Repeated errors may result in the JobTrigger automatically being paused. Will return the last 100 errors. Whenever the JobTrigger is modified this list will be cleared.
        { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
          &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
            &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
            &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
              {
                &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
              },
            ],
            &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
          },
          &quot;extraInfo&quot;: &quot;A String&quot;, # Additional information about the error.
          &quot;timestamps&quot;: [ # The times the error occurred. List includes the oldest timestamp and the last 9 timestamps.
            &quot;A String&quot;,
          ],
        },
      ],
      &quot;inspectJob&quot;: { # Controls what and how to inspect for findings. # For inspect jobs, a snapshot of the configuration.
        &quot;actions&quot;: [ # Actions to execute at the completion of the job.
          { # A task to execute on the completion of a job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-actions to learn more.
            &quot;deidentify&quot;: { # Create a de-identified copy of a storage bucket. Only compatible with Cloud Storage buckets. A TransformationDetail will be created for each transformation. Compatible with: Inspection of Cloud Storage # Create a de-identified copy of the input data.
              &quot;cloudStorageOutput&quot;: &quot;A String&quot;, # Required. User settable Cloud Storage bucket and folders to store de-identified files. This field must be set for Cloud Storage deidentification. The output Cloud Storage bucket must be different from the input bucket. De-identified files will overwrite files in the output path. Form of: gs://bucket/folder/ or gs://bucket
              &quot;fileTypesToTransform&quot;: [ # List of user-specified file type groups to transform. If specified, only the files with these file types are transformed. If empty, all supported files are transformed. Supported types may be automatically added over time. Any unsupported file types that are set in this field are excluded from de-identification. An error is recorded for each unsupported file in the TransformationDetails output table. Currently the only file types supported are: IMAGES, TEXT_FILES, CSV, TSV.
                &quot;A String&quot;,
              ],
              &quot;transformationConfig&quot;: { # User specified templates and configs for how to deidentify structured, unstructures, and image files. User must provide either a unstructured deidentify template or at least one redact image config. # User specified deidentify templates and configs for structured, unstructured, and image files.
                &quot;deidentifyTemplate&quot;: &quot;A String&quot;, # De-identify template. If this template is specified, it will serve as the default de-identify template. This template cannot contain `record_transformations` since it can be used for unstructured content such as free-form text files. If this template is not set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify unstructured content.
                &quot;imageRedactTemplate&quot;: &quot;A String&quot;, # Image redact template. If this template is specified, it will serve as the de-identify template for images. If this template is not set, all findings in the image will be redacted with a black box.
                &quot;structuredDeidentifyTemplate&quot;: &quot;A String&quot;, # Structured de-identify template. If this template is specified, it will serve as the de-identify template for structured content such as delimited files and tables. If this template is not set but the `deidentify_template` is set, then `deidentify_template` will also apply to the structured content. If neither template is set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify structured content.
              },
              &quot;transformationDetailsStorageConfig&quot;: { # Config for storing transformation details. # Config for storing transformation details. This field specifies the configuration for storing detailed metadata about each transformation performed during a de-identification process. The metadata is stored separately from the de-identified content itself and provides a granular record of both successful transformations and any failures that occurred. Enabling this configuration is essential for users who need to access comprehensive information about the status, outcome, and specifics of each transformation. The details are captured in the TransformationDetails message for each operation. Key use cases: * **Auditing and compliance** * Provides a verifiable audit trail of de-identification activities, which is crucial for meeting regulatory requirements and internal data governance policies. * Logs what data was transformed, what transformations were applied, when they occurred, and their success status. This helps demonstrate accountability and due diligence in protecting sensitive data. * **Troubleshooting and debugging** * Offers detailed error messages and context if a transformation fails. This information is useful for diagnosing and resolving issues in the de-identification pipeline. * Helps pinpoint the exact location and nature of failures, speeding up the debugging process. * **Process verification and quality assurance** * Allows users to confirm that de-identification rules and transformations were applied correctly and consistently across the dataset as intended. * Helps in verifying the effectiveness of the chosen de-identification strategies. * **Data lineage and impact analysis** * Creates a record of how data elements were modified, contributing to data lineage. This is useful for understanding the provenance of de-identified data. * Aids in assessing the potential impact of de-identification choices on downstream analytical processes or data usability. * **Reporting and operational insights** * You can analyze the metadata stored in a queryable BigQuery table to generate reports on transformation success rates, common error types, processing volumes (e.g., transformedBytes), and the types of transformations applied. * These insights can inform optimization of de-identification configurations and resource planning. To take advantage of these benefits, set this configuration. The stored details include a description of the transformation, success or error codes, error messages, the number of bytes transformed, the location of the transformed content, and identifiers for the job and source data.
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # The BigQuery table in which to store the output. This may be an existing table or in a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_transformation_details_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            },
            &quot;jobNotificationEmails&quot;: { # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts). # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts).
            },
            &quot;pubSub&quot;: { # Publish a message into a given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a Pub/Sub topic.
              &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
            },
            &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Data Catalog. In Data Catalog, tag templates are applied to the resource that Cloud DLP scanned. Data Catalog tag templates are stored in the same project and region where the BigQuery table exists. For Cloud DLP to create and apply the tag template, the Cloud DLP service agent must have the `roles/datacatalog.tagTemplateOwner` permission on the project. The tag template contains fields summarizing the results of the DlpJob. Any field values previously written by another DlpJob are deleted. InfoType naming patterns are strictly enforced when using this feature. Findings are persisted in Data Catalog storage and are governed by service-specific policies for Data Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
            },
            &quot;publishFindingsToDataplexCatalog&quot;: { # Publish findings of a DlpJob to Dataplex Universal Catalog as a `sensitive-data-protection-job-result` aspect. For more information, see [Send inspection results to Dataplex Universal Catalog as aspects](https://cloud.google.com/sensitive-data-protection/docs/add-aspects-inspection-job). Aspects are stored in Dataplex Universal Catalog storage and are governed by service-specific policies for Dataplex Universal Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings as an aspect to Dataplex Universal Catalog.
            },
            &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to [Security Command Center](https://cloud.google.com/security-command-center). This action is available for only projects that belong to an organization. This action publishes the count of finding instances and their infoTypes. The summary of findings are persisted in Security Command Center and are governed by [service-specific policies for Security Command Center](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
            },
            &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
            },
            &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
              &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
                &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
                &quot;storagePath&quot;: { # Message representing a single file or path in Cloud Storage. # Store findings in an existing Cloud Storage bucket. Files will be generated with the job ID and file part number as the filename and will contain findings in textproto format as SaveToGcsFindingsOutput. The filename will follow the naming convention `-`. Example: `my-job-id-2`. Supported for Inspect jobs. The bucket must not be the same as the bucket being inspected. If storing findings to Cloud Storage, the output schema field should not be set. If set, it will be ignored.
                  &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
                },
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            },
          },
        ],
        &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
          &quot;contentOptions&quot;: [ # Deprecated and unused.
            &quot;A String&quot;,
          ],
          &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes to learn more.
            { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
              &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
                { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                    },
                  },
                },
              ],
              &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
                &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                  &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
                },
                &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                  &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                    &quot;A String&quot;,
                  ],
                },
              },
              &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
              &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                  &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                },
                &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
              },
              &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
              &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
                &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                  42,
                ],
                &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
              },
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Sensitivity for this CustomInfoType. If this CustomInfoType extends an existing InfoType, the sensitivity here will take precedence over that of the original InfoType. If unset for a CustomInfoType, it will default to HIGH. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
                &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
                &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
              },
              &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
              },
            },
          ],
          &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings. This is not used for data profiling.
          &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote. This is not used for data profiling.
          &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose a default list of detectors to run, which may change over time. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
          ],
          &quot;limits&quot;: { # Configuration to control the number of findings returned for inspection. This is not used for de-identification or data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. # Configuration to control the number of findings returned. This is not used for data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. When set within an InspectJobConfig, the specified maximum values aren&#x27;t hard limits. If an inspection job reaches these limits, the job ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than these maximum values.
            &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
              { # Max findings configuration per infoType, per content item or long running DlpJob.
                &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                  &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                    &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                  },
                  &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
                },
                &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
              },
            ],
            &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that are returned for each item scanned. When set within an InspectContentRequest, this field is ignored. This value isn&#x27;t a hard limit. If the number of findings for an item reaches this limit, the inspection of that item ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns for the item can be multiple times higher than this value.
            &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that are returned per request or job. If you set this field in an InspectContentRequest, the resulting maximum value is the value that you set or 3,000, whichever is lower. This value isn&#x27;t a hard limit. If an inspection reaches this limit, the inspection ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than this value.
          },
          &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. The default is POSSIBLE. In general, the highest likelihood setting yields the fewest findings in results and the lowest chance of a false positive. For more information, see [Match likelihood](https://cloud.google.com/sensitive-data-protection/docs/likelihood).
          &quot;minLikelihoodPerInfoType&quot;: [ # Minimum likelihood per infotype. For each infotype, a user can specify a minimum likelihood. The system only returns a finding if its likelihood is above this threshold. If this field is not set, the system uses the InspectConfig min_likelihood.
            { # Configuration for setting a minimum likelihood per infotype. Used to customize the minimum likelihood level for specific infotypes in the request. For example, use this if you want to lower the precision for PERSON_NAME without lowering the precision for the other infotypes in the request.
              &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the likelihood threshold applies to. Only one likelihood per info_type should be provided. If InfoTypeLikelihood does not have an info_type, the configuration fails.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                  &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                },
                &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
              },
              &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. This field is required or else the configuration fails.
            },
          ],
          &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
            { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
              &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
                { # Type of information detected by the API.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                  &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                    &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                  },
                  &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
                },
              ],
              &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
                { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                  &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                    &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                      &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                        &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
                      },
                      &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                        &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                          &quot;A String&quot;,
                        ],
                      },
                    },
                    &quot;excludeByHotword&quot;: { # The rule to exclude findings based on a hotword. For record inspection of tables, column names are considered hotwords. An example of this is to exclude a finding if it belongs to a BigQuery column that matches a specific pattern. # Drop if the hotword rule is contained in the proximate context. For tabular data, the context includes the column name.
                      &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                        &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                          42,
                        ],
                        &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                      },
                      &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The windowBefore property in proximity should be set to 1 if the hotword needs to be included in a column header.
                        &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                        &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                      },
                    },
                    &quot;excludeInfoTypes&quot;: { # List of excluded infoTypes. # Set of infoTypes for which findings would affect this rule.
                      &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                        { # Type of information detected by the API.
                          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                          &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                            &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                          },
                          &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
                        },
                      ],
                    },
                    &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                    &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                  },
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                    },
                  },
                },
              ],
            },
          ],
        },
        &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
        &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
          &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
            &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;includedFields&quot;: [ # Limit scanning only to these fields. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
            &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig. Caution: A [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-sampling) is causing the `rowsLimitPercent` field to behave unexpectedly. We recommend using `rowsLimit` instead.
            &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
            &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
          &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Cloud Storage bucket. # Cloud Storage options.
            &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of `bytes_limit_per_file` and `bytes_limit_per_file_percent` can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
            &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
            &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
              &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
                &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
                &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                  &quot;A String&quot;,
                ],
                &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                  &quot;A String&quot;,
                ],
              },
              &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
            },
            &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
              &quot;A String&quot;,
            ],
            &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
            &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
          },
          &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
            &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
              &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
            },
            &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
              &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
              &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
            },
          },
          &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
            &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
            &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
              &quot;a_key&quot;: &quot;A String&quot;,
            },
            &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
              &quot;A String&quot;,
            ],
            &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
              &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
                { # General identifier of a data field in a storage service.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              ],
            },
          },
          &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Cloud Storage and BigQuery. # Configuration of the timespan of the items to include in scanning.
            &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger or the timespan end_time used in the last run of the JobTrigger. **For BigQuery** Inspect jobs triggered by automatic population will scan data that is at least three hours old when the job starts. This is because streaming buffer rows are not read during inspection and reading up to the current timestamp will result in skipped rows. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#recently-streamed-data) related to this operation.
            &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
            &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
            &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. **For BigQuery** If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. If your BigQuery table is [partitioned at ingestion time](https://cloud.google.com/bigquery/docs/partitioned-tables#ingestion_time), you can use any of the following pseudo-columns as your timestamp field. When used with Cloud DLP, these pseudo-column names are case sensitive. - `_PARTITIONTIME` - `_PARTITIONDATE` - `_PARTITION_LOAD_TIME` **For Datastore** If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-timespan) related to this operation.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
        },
      },
      &quot;lastRunTime&quot;: &quot;A String&quot;, # Output only. The timestamp of the last time this trigger executed.
      &quot;name&quot;: &quot;A String&quot;, # Unique resource name for the triggeredJob, assigned by the service when the triggeredJob is created, for example `projects/dlp-test-project/jobTriggers/53234423`.
      &quot;status&quot;: &quot;A String&quot;, # Required. A status for this trigger.
      &quot;triggers&quot;: [ # A list of triggers which will be OR&#x27;ed together. Only one in the list needs to trigger for a job to be started. The list may contain only a single Schedule trigger and must have at least one object.
        { # What event needs to occur for a new job to be started.
          &quot;manual&quot;: { # Job trigger option for hybrid jobs. Jobs must be manually created and finished. # For use with hybrid jobs. Jobs must be manually created and finished.
          },
          &quot;schedule&quot;: { # Schedule for inspect job triggers. # Create a job on a repeating basis based on the elapse of time.
            &quot;recurrencePeriodDuration&quot;: &quot;A String&quot;, # With this option a job is started on a regular periodic basis. For example: every day (86400 seconds). A scheduled start time will be skipped if the previous execution has not ended when its scheduled time occurs. This value must be set to a time duration greater than or equal to 1 day and can be no longer than 60 days.
          },
        },
      ],
      &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of a triggeredJob.
    },
  ],
  &quot;nextPageToken&quot;: &quot;A String&quot;, # If the next page is available then this value is the next page token to be used in the following ListJobTriggers request.
}</pre>
</div>

<div class="method">
    <code class="details" id="list_next">list_next()</code>
  <pre>Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call &#x27;execute()&#x27; on to request the next
          page. Returns None if there are no more items in the collection.
        </pre>
</div>

<div class="method">
    <code class="details" id="patch">patch(name, body=None, x__xgafv=None)</code>
  <pre>Updates a job trigger. See https://cloud.google.com/sensitive-data-protection/docs/creating-job-triggers to learn more.

Args:
  name: string, Required. Resource name of the project and the triggeredJob, for example `projects/dlp-test-project/jobTriggers/53234423`. (required)
  body: object, The request body.
    The object takes the form of:

{ # Request message for UpdateJobTrigger.
  &quot;jobTrigger&quot;: { # Contains a configuration to make API calls on a repeating basis. See https://cloud.google.com/sensitive-data-protection/docs/concepts-job-triggers to learn more. # New JobTrigger value.
    &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of a triggeredJob.
    &quot;description&quot;: &quot;A String&quot;, # User provided description (max 256 chars)
    &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 100 chars)
    &quot;errors&quot;: [ # Output only. A stream of errors encountered when the trigger was activated. Repeated errors may result in the JobTrigger automatically being paused. Will return the last 100 errors. Whenever the JobTrigger is modified this list will be cleared.
      { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
        &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
          &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
          &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
            {
              &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
            },
          ],
          &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
        },
        &quot;extraInfo&quot;: &quot;A String&quot;, # Additional information about the error.
        &quot;timestamps&quot;: [ # The times the error occurred. List includes the oldest timestamp and the last 9 timestamps.
          &quot;A String&quot;,
        ],
      },
    ],
    &quot;inspectJob&quot;: { # Controls what and how to inspect for findings. # For inspect jobs, a snapshot of the configuration.
      &quot;actions&quot;: [ # Actions to execute at the completion of the job.
        { # A task to execute on the completion of a job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-actions to learn more.
          &quot;deidentify&quot;: { # Create a de-identified copy of a storage bucket. Only compatible with Cloud Storage buckets. A TransformationDetail will be created for each transformation. Compatible with: Inspection of Cloud Storage # Create a de-identified copy of the input data.
            &quot;cloudStorageOutput&quot;: &quot;A String&quot;, # Required. User settable Cloud Storage bucket and folders to store de-identified files. This field must be set for Cloud Storage deidentification. The output Cloud Storage bucket must be different from the input bucket. De-identified files will overwrite files in the output path. Form of: gs://bucket/folder/ or gs://bucket
            &quot;fileTypesToTransform&quot;: [ # List of user-specified file type groups to transform. If specified, only the files with these file types are transformed. If empty, all supported files are transformed. Supported types may be automatically added over time. Any unsupported file types that are set in this field are excluded from de-identification. An error is recorded for each unsupported file in the TransformationDetails output table. Currently the only file types supported are: IMAGES, TEXT_FILES, CSV, TSV.
              &quot;A String&quot;,
            ],
            &quot;transformationConfig&quot;: { # User specified templates and configs for how to deidentify structured, unstructures, and image files. User must provide either a unstructured deidentify template or at least one redact image config. # User specified deidentify templates and configs for structured, unstructured, and image files.
              &quot;deidentifyTemplate&quot;: &quot;A String&quot;, # De-identify template. If this template is specified, it will serve as the default de-identify template. This template cannot contain `record_transformations` since it can be used for unstructured content such as free-form text files. If this template is not set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify unstructured content.
              &quot;imageRedactTemplate&quot;: &quot;A String&quot;, # Image redact template. If this template is specified, it will serve as the de-identify template for images. If this template is not set, all findings in the image will be redacted with a black box.
              &quot;structuredDeidentifyTemplate&quot;: &quot;A String&quot;, # Structured de-identify template. If this template is specified, it will serve as the de-identify template for structured content such as delimited files and tables. If this template is not set but the `deidentify_template` is set, then `deidentify_template` will also apply to the structured content. If neither template is set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify structured content.
            },
            &quot;transformationDetailsStorageConfig&quot;: { # Config for storing transformation details. # Config for storing transformation details. This field specifies the configuration for storing detailed metadata about each transformation performed during a de-identification process. The metadata is stored separately from the de-identified content itself and provides a granular record of both successful transformations and any failures that occurred. Enabling this configuration is essential for users who need to access comprehensive information about the status, outcome, and specifics of each transformation. The details are captured in the TransformationDetails message for each operation. Key use cases: * **Auditing and compliance** * Provides a verifiable audit trail of de-identification activities, which is crucial for meeting regulatory requirements and internal data governance policies. * Logs what data was transformed, what transformations were applied, when they occurred, and their success status. This helps demonstrate accountability and due diligence in protecting sensitive data. * **Troubleshooting and debugging** * Offers detailed error messages and context if a transformation fails. This information is useful for diagnosing and resolving issues in the de-identification pipeline. * Helps pinpoint the exact location and nature of failures, speeding up the debugging process. * **Process verification and quality assurance** * Allows users to confirm that de-identification rules and transformations were applied correctly and consistently across the dataset as intended. * Helps in verifying the effectiveness of the chosen de-identification strategies. * **Data lineage and impact analysis** * Creates a record of how data elements were modified, contributing to data lineage. This is useful for understanding the provenance of de-identified data. * Aids in assessing the potential impact of de-identification choices on downstream analytical processes or data usability. * **Reporting and operational insights** * You can analyze the metadata stored in a queryable BigQuery table to generate reports on transformation success rates, common error types, processing volumes (e.g., transformedBytes), and the types of transformations applied. * These insights can inform optimization of de-identification configurations and resource planning. To take advantage of these benefits, set this configuration. The stored details include a description of the transformation, success or error codes, error messages, the number of bytes transformed, the location of the transformed content, and identifiers for the job and source data.
              &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # The BigQuery table in which to store the output. This may be an existing table or in a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_transformation_details_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details.
                &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
              },
            },
          },
          &quot;jobNotificationEmails&quot;: { # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts). # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts).
          },
          &quot;pubSub&quot;: { # Publish a message into a given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a Pub/Sub topic.
            &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
          },
          &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Data Catalog. In Data Catalog, tag templates are applied to the resource that Cloud DLP scanned. Data Catalog tag templates are stored in the same project and region where the BigQuery table exists. For Cloud DLP to create and apply the tag template, the Cloud DLP service agent must have the `roles/datacatalog.tagTemplateOwner` permission on the project. The tag template contains fields summarizing the results of the DlpJob. Any field values previously written by another DlpJob are deleted. InfoType naming patterns are strictly enforced when using this feature. Findings are persisted in Data Catalog storage and are governed by service-specific policies for Data Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
          },
          &quot;publishFindingsToDataplexCatalog&quot;: { # Publish findings of a DlpJob to Dataplex Universal Catalog as a `sensitive-data-protection-job-result` aspect. For more information, see [Send inspection results to Dataplex Universal Catalog as aspects](https://cloud.google.com/sensitive-data-protection/docs/add-aspects-inspection-job). Aspects are stored in Dataplex Universal Catalog storage and are governed by service-specific policies for Dataplex Universal Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings as an aspect to Dataplex Universal Catalog.
          },
          &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to [Security Command Center](https://cloud.google.com/security-command-center). This action is available for only projects that belong to an organization. This action publishes the count of finding instances and their infoTypes. The summary of findings are persisted in Security Command Center and are governed by [service-specific policies for Security Command Center](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
          },
          &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
          },
          &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
            &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
              &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
              &quot;storagePath&quot;: { # Message representing a single file or path in Cloud Storage. # Store findings in an existing Cloud Storage bucket. Files will be generated with the job ID and file part number as the filename and will contain findings in textproto format as SaveToGcsFindingsOutput. The filename will follow the naming convention `-`. Example: `my-job-id-2`. Supported for Inspect jobs. The bucket must not be the same as the bucket being inspected. If storing findings to Cloud Storage, the output schema field should not be set. If set, it will be ignored.
                &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
              },
              &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
              },
            },
          },
        },
      ],
      &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
        &quot;contentOptions&quot;: [ # Deprecated and unused.
          &quot;A String&quot;,
        ],
        &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes to learn more.
          { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
            &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
              { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                  &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                    &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                    &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                  },
                  &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                    &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                    &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  },
                },
              },
            ],
            &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
              &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
              },
              &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                  &quot;A String&quot;,
                ],
              },
            },
            &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
            &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
            &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
            &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
              &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                42,
              ],
              &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
            },
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Sensitivity for this CustomInfoType. If this CustomInfoType extends an existing InfoType, the sensitivity here will take precedence over that of the original InfoType. If unset for a CustomInfoType, it will default to HIGH. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
              &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
              &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
            },
            &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
            },
          },
        ],
        &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings. This is not used for data profiling.
        &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote. This is not used for data profiling.
        &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose a default list of detectors to run, which may change over time. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
          { # Type of information detected by the API.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
          },
        ],
        &quot;limits&quot;: { # Configuration to control the number of findings returned for inspection. This is not used for de-identification or data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. # Configuration to control the number of findings returned. This is not used for data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. When set within an InspectJobConfig, the specified maximum values aren&#x27;t hard limits. If an inspection job reaches these limits, the job ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than these maximum values.
          &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
            { # Max findings configuration per infoType, per content item or long running DlpJob.
              &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                  &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                },
                &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
              },
              &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
            },
          ],
          &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that are returned for each item scanned. When set within an InspectContentRequest, this field is ignored. This value isn&#x27;t a hard limit. If the number of findings for an item reaches this limit, the inspection of that item ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns for the item can be multiple times higher than this value.
          &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that are returned per request or job. If you set this field in an InspectContentRequest, the resulting maximum value is the value that you set or 3,000, whichever is lower. This value isn&#x27;t a hard limit. If an inspection reaches this limit, the inspection ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than this value.
        },
        &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. The default is POSSIBLE. In general, the highest likelihood setting yields the fewest findings in results and the lowest chance of a false positive. For more information, see [Match likelihood](https://cloud.google.com/sensitive-data-protection/docs/likelihood).
        &quot;minLikelihoodPerInfoType&quot;: [ # Minimum likelihood per infotype. For each infotype, a user can specify a minimum likelihood. The system only returns a finding if its likelihood is above this threshold. If this field is not set, the system uses the InspectConfig min_likelihood.
          { # Configuration for setting a minimum likelihood per infotype. Used to customize the minimum likelihood level for specific infotypes in the request. For example, use this if you want to lower the precision for PERSON_NAME without lowering the precision for the other infotypes in the request.
            &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the likelihood threshold applies to. Only one likelihood per info_type should be provided. If InfoTypeLikelihood does not have an info_type, the configuration fails.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
            &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. This field is required or else the configuration fails.
          },
        ],
        &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
          { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
            &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
              { # Type of information detected by the API.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                  &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                },
                &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
              },
            ],
            &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
              { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                  &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                    &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                      &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
                    },
                    &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                      &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                        &quot;A String&quot;,
                      ],
                    },
                  },
                  &quot;excludeByHotword&quot;: { # The rule to exclude findings based on a hotword. For record inspection of tables, column names are considered hotwords. An example of this is to exclude a finding if it belongs to a BigQuery column that matches a specific pattern. # Drop if the hotword rule is contained in the proximate context. For tabular data, the context includes the column name.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The windowBefore property in proximity should be set to 1 if the hotword needs to be included in a column header.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                    },
                  },
                  &quot;excludeInfoTypes&quot;: { # List of excluded infoTypes. # Set of infoTypes for which findings would affect this rule.
                    &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                      { # Type of information detected by the API.
                        &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                        &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                          &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                        },
                        &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
                      },
                    ],
                  },
                  &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                  &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                },
                &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                  &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                    &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                    &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                  },
                  &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                    &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                    &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  },
                },
              },
            ],
          },
        ],
      },
      &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
      &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
        &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
          &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
          &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
          &quot;includedFields&quot;: [ # Limit scanning only to these fields. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
          &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
          &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig. Caution: A [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-sampling) is causing the `rowsLimitPercent` field to behave unexpectedly. We recommend using `rowsLimit` instead.
          &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
          &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
            &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
            &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
            &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
          },
        },
        &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Cloud Storage bucket. # Cloud Storage options.
          &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of `bytes_limit_per_file` and `bytes_limit_per_file_percent` can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
          &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
          &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
            &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
              &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
              &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                &quot;A String&quot;,
              ],
              &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                &quot;A String&quot;,
              ],
            },
            &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
          },
          &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
            &quot;A String&quot;,
          ],
          &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
          &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
        },
        &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
          &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
            &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
          },
          &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
            &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
            &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
          },
        },
        &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
          &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
          &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
            &quot;a_key&quot;: &quot;A String&quot;,
          },
          &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
            &quot;A String&quot;,
          ],
          &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
            &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
          },
        },
        &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Cloud Storage and BigQuery. # Configuration of the timespan of the items to include in scanning.
          &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger or the timespan end_time used in the last run of the JobTrigger. **For BigQuery** Inspect jobs triggered by automatic population will scan data that is at least three hours old when the job starts. This is because streaming buffer rows are not read during inspection and reading up to the current timestamp will result in skipped rows. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#recently-streamed-data) related to this operation.
          &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
          &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
          &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. **For BigQuery** If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. If your BigQuery table is [partitioned at ingestion time](https://cloud.google.com/bigquery/docs/partitioned-tables#ingestion_time), you can use any of the following pseudo-columns as your timestamp field. When used with Cloud DLP, these pseudo-column names are case sensitive. - `_PARTITIONTIME` - `_PARTITIONDATE` - `_PARTITION_LOAD_TIME` **For Datastore** If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-timespan) related to this operation.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        },
      },
    },
    &quot;lastRunTime&quot;: &quot;A String&quot;, # Output only. The timestamp of the last time this trigger executed.
    &quot;name&quot;: &quot;A String&quot;, # Unique resource name for the triggeredJob, assigned by the service when the triggeredJob is created, for example `projects/dlp-test-project/jobTriggers/53234423`.
    &quot;status&quot;: &quot;A String&quot;, # Required. A status for this trigger.
    &quot;triggers&quot;: [ # A list of triggers which will be OR&#x27;ed together. Only one in the list needs to trigger for a job to be started. The list may contain only a single Schedule trigger and must have at least one object.
      { # What event needs to occur for a new job to be started.
        &quot;manual&quot;: { # Job trigger option for hybrid jobs. Jobs must be manually created and finished. # For use with hybrid jobs. Jobs must be manually created and finished.
        },
        &quot;schedule&quot;: { # Schedule for inspect job triggers. # Create a job on a repeating basis based on the elapse of time.
          &quot;recurrencePeriodDuration&quot;: &quot;A String&quot;, # With this option a job is started on a regular periodic basis. For example: every day (86400 seconds). A scheduled start time will be skipped if the previous execution has not ended when its scheduled time occurs. This value must be set to a time duration greater than or equal to 1 day and can be no longer than 60 days.
        },
      },
    ],
    &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of a triggeredJob.
  },
  &quot;updateMask&quot;: &quot;A String&quot;, # Mask to control which fields get updated.
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Contains a configuration to make API calls on a repeating basis. See https://cloud.google.com/sensitive-data-protection/docs/concepts-job-triggers to learn more.
  &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of a triggeredJob.
  &quot;description&quot;: &quot;A String&quot;, # User provided description (max 256 chars)
  &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 100 chars)
  &quot;errors&quot;: [ # Output only. A stream of errors encountered when the trigger was activated. Repeated errors may result in the JobTrigger automatically being paused. Will return the last 100 errors. Whenever the JobTrigger is modified this list will be cleared.
    { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
      &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
        &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
        &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
          {
            &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
          },
        ],
        &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
      },
      &quot;extraInfo&quot;: &quot;A String&quot;, # Additional information about the error.
      &quot;timestamps&quot;: [ # The times the error occurred. List includes the oldest timestamp and the last 9 timestamps.
        &quot;A String&quot;,
      ],
    },
  ],
  &quot;inspectJob&quot;: { # Controls what and how to inspect for findings. # For inspect jobs, a snapshot of the configuration.
    &quot;actions&quot;: [ # Actions to execute at the completion of the job.
      { # A task to execute on the completion of a job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-actions to learn more.
        &quot;deidentify&quot;: { # Create a de-identified copy of a storage bucket. Only compatible with Cloud Storage buckets. A TransformationDetail will be created for each transformation. Compatible with: Inspection of Cloud Storage # Create a de-identified copy of the input data.
          &quot;cloudStorageOutput&quot;: &quot;A String&quot;, # Required. User settable Cloud Storage bucket and folders to store de-identified files. This field must be set for Cloud Storage deidentification. The output Cloud Storage bucket must be different from the input bucket. De-identified files will overwrite files in the output path. Form of: gs://bucket/folder/ or gs://bucket
          &quot;fileTypesToTransform&quot;: [ # List of user-specified file type groups to transform. If specified, only the files with these file types are transformed. If empty, all supported files are transformed. Supported types may be automatically added over time. Any unsupported file types that are set in this field are excluded from de-identification. An error is recorded for each unsupported file in the TransformationDetails output table. Currently the only file types supported are: IMAGES, TEXT_FILES, CSV, TSV.
            &quot;A String&quot;,
          ],
          &quot;transformationConfig&quot;: { # User specified templates and configs for how to deidentify structured, unstructures, and image files. User must provide either a unstructured deidentify template or at least one redact image config. # User specified deidentify templates and configs for structured, unstructured, and image files.
            &quot;deidentifyTemplate&quot;: &quot;A String&quot;, # De-identify template. If this template is specified, it will serve as the default de-identify template. This template cannot contain `record_transformations` since it can be used for unstructured content such as free-form text files. If this template is not set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify unstructured content.
            &quot;imageRedactTemplate&quot;: &quot;A String&quot;, # Image redact template. If this template is specified, it will serve as the de-identify template for images. If this template is not set, all findings in the image will be redacted with a black box.
            &quot;structuredDeidentifyTemplate&quot;: &quot;A String&quot;, # Structured de-identify template. If this template is specified, it will serve as the de-identify template for structured content such as delimited files and tables. If this template is not set but the `deidentify_template` is set, then `deidentify_template` will also apply to the structured content. If neither template is set, a default `ReplaceWithInfoTypeConfig` will be used to de-identify structured content.
          },
          &quot;transformationDetailsStorageConfig&quot;: { # Config for storing transformation details. # Config for storing transformation details. This field specifies the configuration for storing detailed metadata about each transformation performed during a de-identification process. The metadata is stored separately from the de-identified content itself and provides a granular record of both successful transformations and any failures that occurred. Enabling this configuration is essential for users who need to access comprehensive information about the status, outcome, and specifics of each transformation. The details are captured in the TransformationDetails message for each operation. Key use cases: * **Auditing and compliance** * Provides a verifiable audit trail of de-identification activities, which is crucial for meeting regulatory requirements and internal data governance policies. * Logs what data was transformed, what transformations were applied, when they occurred, and their success status. This helps demonstrate accountability and due diligence in protecting sensitive data. * **Troubleshooting and debugging** * Offers detailed error messages and context if a transformation fails. This information is useful for diagnosing and resolving issues in the de-identification pipeline. * Helps pinpoint the exact location and nature of failures, speeding up the debugging process. * **Process verification and quality assurance** * Allows users to confirm that de-identification rules and transformations were applied correctly and consistently across the dataset as intended. * Helps in verifying the effectiveness of the chosen de-identification strategies. * **Data lineage and impact analysis** * Creates a record of how data elements were modified, contributing to data lineage. This is useful for understanding the provenance of de-identified data. * Aids in assessing the potential impact of de-identification choices on downstream analytical processes or data usability. * **Reporting and operational insights** * You can analyze the metadata stored in a queryable BigQuery table to generate reports on transformation success rates, common error types, processing volumes (e.g., transformedBytes), and the types of transformations applied. * These insights can inform optimization of de-identification configurations and resource planning. To take advantage of these benefits, set this configuration. The stored details include a description of the transformation, success or error codes, error messages, the number of bytes transformed, the location of the transformed content, and identifiers for the job and source data.
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # The BigQuery table in which to store the output. This may be an existing table or in a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_transformation_details_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
        &quot;jobNotificationEmails&quot;: { # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts). # Sends an email when the job completes. The email goes to IAM project owners and technical [Essential Contacts](https://cloud.google.com/resource-manager/docs/managing-notification-contacts).
        },
        &quot;pubSub&quot;: { # Publish a message into a given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a Pub/Sub topic.
          &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
        },
        &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Data Catalog. In Data Catalog, tag templates are applied to the resource that Cloud DLP scanned. Data Catalog tag templates are stored in the same project and region where the BigQuery table exists. For Cloud DLP to create and apply the tag template, the Cloud DLP service agent must have the `roles/datacatalog.tagTemplateOwner` permission on the project. The tag template contains fields summarizing the results of the DlpJob. Any field values previously written by another DlpJob are deleted. InfoType naming patterns are strictly enforced when using this feature. Findings are persisted in Data Catalog storage and are governed by service-specific policies for Data Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
        },
        &quot;publishFindingsToDataplexCatalog&quot;: { # Publish findings of a DlpJob to Dataplex Universal Catalog as a `sensitive-data-protection-job-result` aspect. For more information, see [Send inspection results to Dataplex Universal Catalog as aspects](https://cloud.google.com/sensitive-data-protection/docs/add-aspects-inspection-job). Aspects are stored in Dataplex Universal Catalog storage and are governed by service-specific policies for Dataplex Universal Catalog. For more information, see [Service Specific Terms](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings as an aspect to Dataplex Universal Catalog.
        },
        &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to [Security Command Center](https://cloud.google.com/security-command-center). This action is available for only projects that belong to an organization. This action publishes the count of finding instances and their infoTypes. The summary of findings are persisted in Security Command Center and are governed by [service-specific policies for Security Command Center](https://cloud.google.com/terms/service-terms). Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
        },
        &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
        },
        &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
          &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
            &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
            &quot;storagePath&quot;: { # Message representing a single file or path in Cloud Storage. # Store findings in an existing Cloud Storage bucket. Files will be generated with the job ID and file part number as the filename and will contain findings in textproto format as SaveToGcsFindingsOutput. The filename will follow the naming convention `-`. Example: `my-job-id-2`. Supported for Inspect jobs. The bucket must not be the same as the bucket being inspected. If storing findings to Cloud Storage, the output schema field should not be set. If set, it will be ignored.
              &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific time zone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
      },
    ],
    &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
      &quot;contentOptions&quot;: [ # Deprecated and unused.
        &quot;A String&quot;,
      ],
      &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes to learn more.
        { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
          &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
            { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
              &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
                &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                  &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                  &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                },
                &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                  &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                },
              },
            },
          ],
          &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
            &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
              &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
            },
            &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
              &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                &quot;A String&quot;,
              ],
            },
          },
          &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
          &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
          },
          &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
          &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
            &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
              42,
            ],
            &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
          },
          &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Sensitivity for this CustomInfoType. If this CustomInfoType extends an existing InfoType, the sensitivity here will take precedence over that of the original InfoType. If unset for a CustomInfoType, it will default to HIGH. This only applies to data profiling.
            &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
          },
          &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
            &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
            &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
          },
          &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/sensitive-data-protection/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
          },
        },
      ],
      &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings. This is not used for data profiling.
      &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote. This is not used for data profiling.
      &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose a default list of detectors to run, which may change over time. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
        { # Type of information detected by the API.
          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
          &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
            &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
          },
          &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
        },
      ],
      &quot;limits&quot;: { # Configuration to control the number of findings returned for inspection. This is not used for de-identification or data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. # Configuration to control the number of findings returned. This is not used for data profiling. When redacting sensitive data from images, finding limits don&#x27;t apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don&#x27;t include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error. When set within an InspectJobConfig, the specified maximum values aren&#x27;t hard limits. If an inspection job reaches these limits, the job ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than these maximum values.
        &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
          { # Max findings configuration per infoType, per content item or long running DlpJob.
            &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
            &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
          },
        ],
        &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that are returned for each item scanned. When set within an InspectContentRequest, this field is ignored. This value isn&#x27;t a hard limit. If the number of findings for an item reaches this limit, the inspection of that item ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns for the item can be multiple times higher than this value.
        &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that are returned per request or job. If you set this field in an InspectContentRequest, the resulting maximum value is the value that you set or 3,000, whichever is lower. This value isn&#x27;t a hard limit. If an inspection reaches this limit, the inspection ends gradually, not abruptly. Therefore, the actual number of findings that Cloud DLP returns can be multiple times higher than this value.
      },
      &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. The default is POSSIBLE. In general, the highest likelihood setting yields the fewest findings in results and the lowest chance of a false positive. For more information, see [Match likelihood](https://cloud.google.com/sensitive-data-protection/docs/likelihood).
      &quot;minLikelihoodPerInfoType&quot;: [ # Minimum likelihood per infotype. For each infotype, a user can specify a minimum likelihood. The system only returns a finding if its likelihood is above this threshold. If this field is not set, the system uses the InspectConfig min_likelihood.
        { # Configuration for setting a minimum likelihood per infotype. Used to customize the minimum likelihood level for specific infotypes in the request. For example, use this if you want to lower the precision for PERSON_NAME without lowering the precision for the other infotypes in the request.
          &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the likelihood threshold applies to. Only one likelihood per info_type should be provided. If InfoTypeLikelihood does not have an info_type, the configuration fails.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
            &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
              &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
            },
            &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
          },
          &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal to or above this threshold. This field is required or else the configuration fails.
        },
      ],
      &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
        { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
          &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
              &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
              },
              &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
            },
          ],
          &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
            { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
              &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/sensitive-data-protection/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                  &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                    &quot;path&quot;: &quot;A String&quot;, # A URL representing a file or path (no wildcards) in Cloud Storage. Example: `gs://[BUCKET_NAME]/dictionary.txt`
                  },
                  &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                    &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                      &quot;A String&quot;,
                    ],
                  },
                },
                &quot;excludeByHotword&quot;: { # The rule to exclude findings based on a hotword. For record inspection of tables, column names are considered hotwords. An example of this is to exclude a finding if it belongs to a BigQuery column that matches a specific pattern. # Drop if the hotword rule is contained in the proximate context. For tabular data, the context includes the column name.
                  &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The windowBefore property in proximity should be set to 1 if the hotword needs to be included in a column header.
                    &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                    &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  },
                },
                &quot;excludeInfoTypes&quot;: { # List of excluded infoTypes. # Set of infoTypes for which findings would affect this rule.
                  &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                    { # Type of information detected by the API.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/sensitive-data-protection/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$_-]{1,64}`.
                      &quot;sensitivityScore&quot;: { # Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive. # Optional custom sensitivity for this InfoType. This only applies to data profiling.
                        &quot;score&quot;: &quot;A String&quot;, # The sensitivity score applied to the resource.
                      },
                      &quot;version&quot;: &quot;A String&quot;, # Optional version name for this InfoType.
                    },
                  ],
                },
                &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
              },
              &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
                &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                  &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                  &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                },
                &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Range of characters within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. The finding itself will be included in the window, so that hotwords can be used to match substrings of the finding itself. Suppose you want Cloud DLP to promote the likelihood of the phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; if the area code is known to be the area code of a company&#x27;s office. In this case, use the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question. For tabular data, if you want to modify the likelihood of an entire column of findngs, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                  &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                  &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider. For tabular data, if you want to modify the likelihood of an entire column of findngs, set this to 1. For more information, see [Hotword example: Set the match likelihood of a table column] (https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes-likelihood#match-column-values).
                },
              },
            },
          ],
        },
      ],
    },
    &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
    &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
      &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
        &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;includedFields&quot;: [ # Limit scanning only to these fields. When inspecting a table, we recommend that you inspect all columns. Otherwise, findings might be affected because hints from excluded columns will not be used.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
        &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig. Caution: A [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-sampling) is causing the `rowsLimitPercent` field to behave unexpectedly. We recommend using `rowsLimit` instead.
        &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
        &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
          &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
          &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud project ID of the project containing the table. If omitted, project ID is inferred from the API call.
          &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
        },
      },
      &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Cloud Storage bucket. # Cloud Storage options.
        &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of `bytes_limit_per_file` and `bytes_limit_per_file_percent` can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
        &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. This field can&#x27;t be set if de-identification is requested. For certain file types, setting this field has no effect. For more information, see [Limits on bytes scanned per file](https://cloud.google.com/sensitive-data-protection/docs/supported-file-types#max-byte-size-per-file).
        &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
          &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
            &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
            &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
              &quot;A String&quot;,
            ],
            &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
              &quot;A String&quot;,
            ],
          },
          &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
        },
        &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
          &quot;A String&quot;,
        ],
        &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
        &quot;sampleMethod&quot;: &quot;A String&quot;, # How to sample the data.
      },
      &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
        &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
          &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
        },
        &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
          &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
          &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
        },
      },
      &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
        &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
        &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
          &quot;a_key&quot;: &quot;A String&quot;,
        },
        &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
          &quot;A String&quot;,
        ],
        &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
          &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
        },
      },
      &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Cloud Storage and BigQuery. # Configuration of the timespan of the items to include in scanning.
        &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger or the timespan end_time used in the last run of the JobTrigger. **For BigQuery** Inspect jobs triggered by automatic population will scan data that is at least three hours old when the job starts. This is because streaming buffer rows are not read during inspection and reading up to the current timestamp will result in skipped rows. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#recently-streamed-data) related to this operation.
        &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
        &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
        &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. **For BigQuery** If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. If your BigQuery table is [partitioned at ingestion time](https://cloud.google.com/bigquery/docs/partitioned-tables#ingestion_time), you can use any of the following pseudo-columns as your timestamp field. When used with Cloud DLP, these pseudo-column names are case sensitive. - `_PARTITIONTIME` - `_PARTITIONDATE` - `_PARTITION_LOAD_TIME` **For Datastore** If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`. See the [known issue](https://cloud.google.com/sensitive-data-protection/docs/known-issues#bq-timespan) related to this operation.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
    },
  },
  &quot;lastRunTime&quot;: &quot;A String&quot;, # Output only. The timestamp of the last time this trigger executed.
  &quot;name&quot;: &quot;A String&quot;, # Unique resource name for the triggeredJob, assigned by the service when the triggeredJob is created, for example `projects/dlp-test-project/jobTriggers/53234423`.
  &quot;status&quot;: &quot;A String&quot;, # Required. A status for this trigger.
  &quot;triggers&quot;: [ # A list of triggers which will be OR&#x27;ed together. Only one in the list needs to trigger for a job to be started. The list may contain only a single Schedule trigger and must have at least one object.
    { # What event needs to occur for a new job to be started.
      &quot;manual&quot;: { # Job trigger option for hybrid jobs. Jobs must be manually created and finished. # For use with hybrid jobs. Jobs must be manually created and finished.
      },
      &quot;schedule&quot;: { # Schedule for inspect job triggers. # Create a job on a repeating basis based on the elapse of time.
        &quot;recurrencePeriodDuration&quot;: &quot;A String&quot;, # With this option a job is started on a regular periodic basis. For example: every day (86400 seconds). A scheduled start time will be skipped if the previous execution has not ended when its scheduled time occurs. This value must be set to a time duration greater than or equal to 1 day and can be no longer than 60 days.
      },
    },
  ],
  &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of a triggeredJob.
}</pre>
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