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# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""
FILE: sample_server_timeout.py
DESCRIPTION:
This sample demonstrates how to update a server timeout for a long running query.
USAGE:
python sample_server_timeout.py
Set the environment variables with your own values before running the sample:
1) LOGS_WORKSPACE_ID - The first (primary) workspace ID.
This example uses DefaultAzureCredential, which requests a token from Azure Active Directory.
For more information on DefaultAzureCredential, see https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#defaultazurecredential.
**Note** - Although this example uses pandas to print the response, it's optional and
isn't a required package for querying. Alternatively, native Python can be used as well.
"""
from datetime import timedelta
import os
from azure.core.exceptions import HttpResponseError
from azure.identity import DefaultAzureCredential
from azure.monitor.query import LogsQueryClient, LogsQueryStatus
import pandas as pd
credential = DefaultAzureCredential()
client = LogsQueryClient(credential)
query = "range x from 1 to 10000000000 step 1 | count"
try:
response = client.query_workspace(
os.environ["LOGS_WORKSPACE_ID"],
query,
timespan=timedelta(days=1),
server_timeout=600, # sets the timeout to 10 minutes
)
if response.status == LogsQueryStatus.SUCCESS:
data = response.tables
else:
# LogsQueryPartialResult - handle error here
error = response.partial_error
data = response.partial_data
print(error)
for table in data:
df = pd.DataFrame(data=table.rows, columns=table.columns)
print(df)
except HttpResponseError as err:
print("something fatal happened")
print(err)
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