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# coding: utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
FILE: sample_data_feeds.py
DESCRIPTION:
This sample demonstrates how to create, get, list, update, and delete datafeeds under your Metrics Advisor account.
USAGE:
python sample_data_feeds.py
Set the environment variables with your own values before running the sample:
1) METRICS_ADVISOR_ENDPOINT - the endpoint of your Azure Metrics Advisor service
2) METRICS_ADVISOR_SUBSCRIPTION_KEY - Metrics Advisor service subscription key
3) METRICS_ADVISOR_API_KEY - Metrics Advisor service API key
4) METRICS_ADVISOR_SQL_SERVER_CONNECTION_STRING - Used in this sample for demonstration, but you should
add your own credentials specific to the data source type you're using
5) METRICS_ADVISOR_SQL_SERVER_QUERY - Used in this sample for demonstration, but you should
add your own credentials specific to the data source type you're using
"""
import os
import datetime
def sample_create_data_feed():
# [START create_data_feed]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
from azure.ai.metricsadvisor.models import (
SQLServerDataFeed,
DataFeedSchema,
DataFeedMetric,
DataFeedDimension,
DataFeedOptions,
DataFeedRollupSettings,
DataFeedMissingDataPointFillSettings,
)
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
sql_server_connection_string = os.getenv("METRICS_ADVISOR_SQL_SERVER_CONNECTION_STRING")
query = os.getenv("METRICS_ADVISOR_SQL_SERVER_QUERY")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
data_feed = client.create_data_feed(
name="My data feed",
source=SQLServerDataFeed(
connection_string=sql_server_connection_string,
query=query,
),
granularity="Daily",
schema=DataFeedSchema(
metrics=[
DataFeedMetric(name="cost", display_name="Cost"),
DataFeedMetric(name="revenue", display_name="Revenue")
],
dimensions=[
DataFeedDimension(name="category", display_name="Category"),
DataFeedDimension(name="city", display_name="City")
],
timestamp_column="Timestamp"
),
ingestion_settings=datetime.datetime(2019, 10, 1),
options=DataFeedOptions(
data_feed_description="cost/revenue data feed",
rollup_settings=DataFeedRollupSettings(
rollup_type="AutoRollup",
rollup_method="Sum",
rollup_identification_value="__CUSTOM_SUM__"
),
missing_data_point_fill_settings=DataFeedMissingDataPointFillSettings(
fill_type="SmartFilling"
),
access_mode="Private"
)
)
return data_feed
# [END create_data_feed]
def sample_get_data_feed(data_feed_id):
# [START get_data_feed]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
data_feed = client.get_data_feed(data_feed_id)
print("ID: {}".format(data_feed.id))
print("Data feed name: {}".format(data_feed.name))
print("Created time: {}".format(data_feed.created_time))
print("Status: {}".format(data_feed.status))
print("Source type: {}".format(data_feed.source.data_source_type))
print("Granularity type: {}".format(data_feed.granularity.granularity_type))
print("Data feed metrics: {}".format([metric.name for metric in data_feed.schema.metrics]))
print("Data feed dimensions: {}".format([dimension.name for dimension in data_feed.schema.dimensions]))
print("Data feed timestamp column: {}".format(data_feed.schema.timestamp_column))
print("Ingestion data starting on: {}".format(data_feed.ingestion_settings.ingestion_begin_time))
print("Data feed description: {}".format(data_feed.options.data_feed_description))
print("Data feed rollup type: {}".format(data_feed.options.rollup_settings.rollup_type))
print("Data feed rollup method: {}".format(data_feed.options.rollup_settings.rollup_method))
print("Data feed fill setting: {}".format(data_feed.options.missing_data_point_fill_settings.fill_type))
print("Data feed access mode: {}".format(data_feed.options.access_mode))
# [END get_data_feed]
def sample_list_data_feeds():
# [START list_data_feeds]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
data_feeds = client.list_data_feeds()
for feed in data_feeds:
print("Data feed name: {}".format(feed.name))
print("ID: {}".format(feed.id))
print("Created time: {}".format(feed.created_time))
print("Status: {}".format(feed.status))
print("Source type: {}".format(feed.source.data_source_type))
print("Granularity type: {}".format(feed.granularity.granularity_type))
print("\nFeed metrics:")
for metric in feed.schema.metrics:
print(metric.name)
print("\nFeed dimensions:")
for dimension in feed.schema.dimensions:
print(dimension.name)
# [END list_data_feeds]
def sample_update_data_feed(data_feed):
# [START update_data_feed]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
# update data feed on the data feed itself or by using available keyword arguments
data_feed.name = "updated name"
data_feed.options.data_feed_description = "updated description for data feed"
updated_data_feed = client.update_data_feed(
data_feed,
access_mode="Public",
fill_type="CustomValue",
custom_fill_value=1
)
print("Updated name: {}".format(updated_data_feed.name))
print("Updated description: {}".format(updated_data_feed.options.data_feed_description))
print("Updated access mode: {}".format(updated_data_feed.options.access_mode))
print("Updated fill setting, value: {}, {}".format(
updated_data_feed.options.missing_data_point_fill_settings.fill_type,
updated_data_feed.options.missing_data_point_fill_settings.custom_fill_value,
))
# [END update_data_feed]
def sample_delete_data_feed(data_feed_id):
# [START delete_data_feed]
from azure.core.exceptions import ResourceNotFoundError
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
client.delete_data_feed(data_feed_id)
try:
client.get_data_feed(data_feed_id)
except ResourceNotFoundError:
print("Data feed successfully deleted.")
# [END delete_data_feed]
if __name__ == '__main__':
print("---Creating data feed...")
data_feed = sample_create_data_feed()
print("Data feed successfully created...")
print("\n---Get a data feed...")
sample_get_data_feed(data_feed.id)
print("\n---List data feeds...")
sample_list_data_feeds()
print("\n---Update a data feed...")
sample_update_data_feed(data_feed)
print("\n---Delete a data feed...")
sample_delete_data_feed(data_feed.id)
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