airflow logs 源码
airflow logs 代码
文件路径:/airflow/providers/amazon/aws/hooks/logs.py
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# Licensed to the Apache Software Foundation (ASF) under one
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# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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"""
This module contains a hook (AwsLogsHook) with some very basic
functionality for interacting with AWS CloudWatch.
"""
from __future__ import annotations
from typing import Generator
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook
class AwsLogsHook(AwsBaseHook):
"""
Interact with AWS CloudWatch Logs
Additional arguments (such as ``aws_conn_id``) may be specified and
are passed down to the underlying AwsBaseHook.
.. seealso::
:class:`~airflow.providers.amazon.aws.hooks.base_aws.AwsBaseHook`
"""
def __init__(self, *args, **kwargs) -> None:
kwargs["client_type"] = "logs"
super().__init__(*args, **kwargs)
def get_log_events(
self,
log_group: str,
log_stream_name: str,
start_time: int = 0,
skip: int = 0,
start_from_head: bool = True,
) -> Generator:
"""
A generator for log items in a single stream. This will yield all the
items that are available at the current moment.
:param log_group: The name of the log group.
:param log_stream_name: The name of the specific stream.
:param start_time: The time stamp value to start reading the logs from (default: 0).
:param skip: The number of log entries to skip at the start (default: 0).
This is for when there are multiple entries at the same timestamp.
:param start_from_head: whether to start from the beginning (True) of the log or
at the end of the log (False).
:rtype: dict
:return: | A CloudWatch log event with the following key-value pairs:
| 'timestamp' (int): The time in milliseconds of the event.
| 'message' (str): The log event data.
| 'ingestionTime' (int): The time in milliseconds the event was ingested.
"""
next_token = None
while True:
if next_token is not None:
token_arg: dict[str, str] | None = {'nextToken': next_token}
else:
token_arg = {}
response = self.get_conn().get_log_events(
logGroupName=log_group,
logStreamName=log_stream_name,
startTime=start_time,
startFromHead=start_from_head,
**token_arg,
)
events = response['events']
event_count = len(events)
if event_count > skip:
events = events[skip:]
skip = 0
else:
skip -= event_count
events = []
yield from events
if next_token != response['nextForwardToken']:
next_token = response['nextForwardToken']
else:
return
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