awswrangler.cloudwatch.read_logs

awswrangler.cloudwatch.read_logs(query: str, log_group_names: List[str], start_time: datetime = datetime.datetime(1970, 1, 1, 0, 0, tzinfo=datetime.timezone.utc), end_time: datetime = datetime.datetime(2023, 1, 9, 21, 3, 58, 259231), limit: int | None = None, boto3_session: Session | None = None) → DataFrame

Run a query against AWS CloudWatchLogs Insights and convert the results to Pandas DataFrame.

https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CWL_QuerySyntax.html

Parameters:

  • query (str) – The query string.

  • log_group_names (str) – The list of log groups to be queried. You can include up to 20 log groups.

  • start_time (datetime.datetime) – The beginning of the time range to query.

  • end_time (datetime.datetime) – The end of the time range to query.

  • limit (Optional[int]) – The maximum number of log events to return in the query.

  • boto3_session (boto3.Session(), optional) – Boto3 Session. The default boto3 session will be used if boto3_session receive None.

Returns:

Result as a Pandas DataFrame.

Return type:

pandas.DataFrame

Examples

>>> import awswrangler as wr
>>> df = wr.cloudwatch.read_logs(
...     log_group_names=["loggroup"],
...     query="fields @timestamp, @message | sort @timestamp desc | limit 5",
... )