1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205
|
# Azure Online Experimentation client library for Python
This package contains Azure Online Experimentation client library for interacting with `Microsoft.OnlineExperimentation/workspaces` resources.
## Getting started
### Install the package
```bash
python -m pip install azure-onlineexperimentation
```
#### Prequisites
- Python 3.9 or later is required to use this package.
- You need an [Azure subscription][azure_sub] to use this package.
- An [Azure Online Experimentation workspace][azure_exp_workspace] resource in the Azure subscription.
### Create and authenticate the client
The Azure Online Experimentation client library initialization requires two parameters:
- The `endpoint` property value from the [`Microsoft.OnlineExperimentation/workspaces`][azure_exp_workspace] resource.
- A credential from `azure.identity`, the simplest approach is to use [DefaultAzureCredential][default_azure_credential] and `az login` to authenticate. See [Azure Identity client library for Python][azure_identity_credentials] for more details.
To construct a synchronous client:
<!-- SNIPPET:sample_initialize_client.initialize_client -->
```python
import os
from azure.identity import DefaultAzureCredential
from azure.onlineexperimentation import OnlineExperimentationClient
# Create a client with your Online Experimentation workspace endpoint and credentials
endpoint = os.environ["AZURE_ONLINEEXPERIMENTATION_ENDPOINT"]
client = OnlineExperimentationClient(endpoint, DefaultAzureCredential())
print(f"Client initialized with endpoint: {endpoint}")
```
<!-- END SNIPPET -->
To construct an asynchronous client, instead import `OnlineExperimentationClient` from `azure.onlineexperimentation.aio` and `DefaultAzureCredential` from `azure.identity.aio` namespaces:
<!-- SNIPPET:sample_initialize_async_client.initialize_async_client -->
```python
import os
from azure.identity.aio import DefaultAzureCredential
from azure.onlineexperimentation.aio import OnlineExperimentationClient
# Create a client with your Online Experimentation workspace endpoint and credentials
endpoint = os.environ["AZURE_ONLINEEXPERIMENTATION_ENDPOINT"]
client = OnlineExperimentationClient(endpoint, DefaultAzureCredential())
print(f"Client initialized with endpoint: {endpoint}")
```
<!-- END SNIPPET -->
## Key concepts
### Online Experimentation Workspace
[`Microsoft.OnlineExperimentation/workspaces`][az_exp_workspace] Azure resources work in conjunction with [Azure App Configuration][app_config] and [Azure Monitor][azure_monitor]. The Online Experimentation workspace handles management of metrics definitions and their continuous computation to monitor and evaluate experiment results.
### Experiment Metrics
Metrics are used to measure the impact of your online experiments. See the [samples][azure_exp_samples] for how to create and manage various types of experiment metrics.
## Troubleshooting
Errors can occur during initial requests and will provide information about how to resolve the error.
## Examples
This examples goes theough the experiment metric management lifecycle, to run the example:
- Set `AZURE_ONLINEEXPERIMENTATION_ENDPOINT` environment variable to the `endpoint` property value (URL) from a [`Microsoft.OnlineExperimentation/workspaces`][az_exp_workspace] resource.
- Enable `DefaultAzureCredential` by running `az login` or `Connect-AzAccount`, see [documentation][default_azure_credential] for details and troubleshooting.
<!-- SNIPPET:sample_experiment_metrics_management.experiment_metrics_management -->
```python
import os
import random
import json
from azure.identity import DefaultAzureCredential
from azure.onlineexperimentation import OnlineExperimentationClient
from azure.onlineexperimentation.models import (
ExperimentMetric,
LifecycleStage,
DesiredDirection,
UserRateMetricDefinition,
ObservedEvent,
)
from azure.core.exceptions import HttpResponseError
# [Step 1] Initialize the SDK client
# The endpoint URL from the Microsoft.OnlineExperimentation/workspaces resource
endpoint = os.environ.get("AZURE_ONLINEEXPERIMENTATION_ENDPOINT", "<endpoint-not-set>")
credential = DefaultAzureCredential()
print(f"AZURE_ONLINEEXPERIMENTATION_ENDPOINT is {endpoint}")
client = OnlineExperimentationClient(endpoint=endpoint, credential=credential)
# [Step 2] Define the experiment metric
example_metric = ExperimentMetric(
lifecycle=LifecycleStage.ACTIVE,
display_name="% users with LLM interaction who made a high-value purchase",
description="Percentage of users who received a response from the LLM and then made a purchase of $100 or more",
categories=["Business"],
desired_direction=DesiredDirection.INCREASE,
definition=UserRateMetricDefinition(
start_event=ObservedEvent(event_name="ResponseReceived"),
end_event=ObservedEvent(event_name="Purchase", filter="Revenue > 100"),
)
)
# [Optional][Step 2a] Validate the metric - checks for input errors without persisting anything
print("Checking if the experiment metric definition is valid...")
print(json.dumps(example_metric.as_dict(), indent=2))
try:
validation_result = client.validate_metric(example_metric)
print(f"Experiment metric definition valid: {validation_result.is_valid}.")
for detail in validation_result.diagnostics or []:
# Inspect details of why the metric definition was rejected as Invalid
print(f"- {detail.code}: {detail.message}")
# [Step 3] Create the experiment metric
example_metric_id = f"sample_metric_id_{random.randint(10000, 20000)}"
print(f"Creating the experiment metric {example_metric_id}...")
# Using upsert to create the metric with If-None-Match header
create_response = client.create_or_update_metric(
experiment_metric_id=example_metric_id,
resource=example_metric,
match_condition=None, # This ensures If-None-Match: * header is sent
etag=None
)
print(f"Experiment metric {create_response.id} created, etag: {create_response.e_tag}.")
# [Step 4] Deactivate the experiment metric and update the description
updated_metric = {
"lifecycle": LifecycleStage.INACTIVE, # pauses computation of this metric
"description": "No longer need to compute this."
}
update_response = client.create_or_update_metric(
experiment_metric_id=example_metric_id,
resource=updated_metric,
etag=create_response.e_tag, # Ensures If-Match header is sent
match_condition=None # Not specifying match_condition as we're using etag
)
print(f"Updated metric: {update_response.id}, etag: {update_response.e_tag}.")
# [Step 5] Delete the experiment metric
client.delete_metric(
experiment_metric_id=example_metric_id,
etag=update_response.e_tag # Ensures If-Match header is sent
)
print(f"Deleted metric: {example_metric_id}.")
except HttpResponseError as error:
print(f"The operation failed with error: {error}")
```
<!-- END SNIPPET -->
## Next steps
Have a look at the [samples][azure_exp_samples] folder, containing fully runnable Python code for synchronous and asynchronous clients.
## Contributing
This project welcomes contributions and suggestions. Most contributions require
you to agree to a Contributor License Agreement (CLA) declaring that you have
the right to, and actually do, grant us the rights to use your contribution.
For details, visit <https://cla.microsoft.co>m.
When you submit a pull request, a CLA-bot will automatically determine whether
you need to provide a CLA and decorate the PR appropriately (e.g., label,
comment). Simply follow the instructions provided by the bot. You will only
need to do this once across all repos using our CLA.
This project has adopted the
[Microsoft Open Source Code of Conduct][code_of_conduct]. For more information,
see the Code of Conduct FAQ or contact <opencode@microsoft.com> with any
additional questions or comments.
<!-- LINKS -->
[code_of_conduct]: https://opensource.microsoft.com/codeofconduct/
[azure_identity_credentials]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/identity/azure-identity#credentials
[default_azure_credential]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/identity/azure-identity#defaultazurecredential
[azure_sub]: https://azure.microsoft.com/free/
[azure_exp_workspace]: https://learn.microsoft.com/azure/templates/microsoft.onlineexperimentation/workspaces
[app_config]: https://learn.microsoft.com/azure/azure-app-configuration/overview
[azure_monitor]: https://learn.microsoft.com/azure/azure-monitor/overview
[azure_exp_samples]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/onlineexperimentation/azure-onlineexperimentation/samples/
|