use*_*709 5 python logging celery
我希望每个正在运行的作业都记录到它自己的文件 logs/ 目录中,其中文件名是 taskid。
logger = get_task_logger(__name__)
@app.task(base=CallbackTask)
def calc(syntax):
some_func()
logger.info('started')
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在我的工作人员中,我使用-f参数将日志文件设置为输出。我想确保它将每个任务输出到它自己的日志文件。
小智 5
好像我迟到了三年。不过,这是我的解决方案,灵感来自 @Mikko Ohtamaa 的想法。我只是通过使用 Celery Signals 和 python 的内置日志框架来准备和清理日志句柄,让它有点不同。
from celery.signals import task_prerun, task_postrun
import logging
# to control the tasks that required logging mechanism
TASK_WITH_LOGGING = ['Proj.tasks.calc']
@task_prerun.connect(sender=TASK_WITH_LOGGING)
def prepare_logging(signal=None, sender=None, task_id=None, task=None, args=None, kwargs=None)
logger = logging.getLogger(task_id)
formatter = logging.Formatter('[%(asctime)s][%(levelname)s] %(message)s')
# optionally logging on the Console as well as file
stream_handler = logging.StreamHandler()
stream_handler.setFormatter(formatter)
stream_handler.setLevel(logging.INFO)
# Adding File Handle with file path. Filename is task_id
task_handler = logging.FileHandler(os.path.join('/tmp/', task_id+'.log'))
task_handler.setFormatter(formatter)
task_handler.setLevel(logging.INFO)
logger.addHandler(stream_handler)
logger.addHandler(task_handler)
@task_postrun.connect(sender=TASK_WITH_LOGGING)
def close_logging(signal=None, sender=None, task_id=None, task=None, args=None, kwargs=None, retval=None, state=None):
# getting the same logger and closing all handles associated with it
logger = logging.getLogger(task_id)
for handler in logger.handlers:
handler.flush()
handler.close()
logger.handlers = []
@app.task(base=CallbackTask, bind=True)
def calc(self, syntax):
# getting logger with name Task ID. This is already
# created and setup in prepare_logging
logger = logging.getLogger(self.request.id)
some_func()
logger.info('started')
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这里bind=True是必要的,以便在任务中使用 id。这将在<task_id>.log每次calc执行任务时创建单独的日志文件。
下面是我的粗略的、凭空写出来的、未经测试的方法。更多地将其视为指导而不是生产级代码。
def get_or_create_task_logger(func):
""" A helper function to create function specific logger lazily. """
# https://docs.python.org/2/library/logging.html?highlight=logging#logging.getLogger
# This will always result the same singleton logger
# based on the task's function name (does not check cross-module name clash,
# for demo purposes only)
logger = logging.getLogger(func.__name__)
# Add our custom logging handler for this logger only
# You could also peek into Celery task context variables here
# http://celery.readthedocs.org/en/latest/userguide/tasks.html#context
if len(logger.handlers) == 0:
# Log to output file based on the function name
hdlr = logging.FileHandler('%s.log' % func.__name__)
formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
hdlr.setFormatter(formatter)
logger.addHandler(hdlr)
logger.setLevel(logging.DEBUG)
return logger
@app.task(base=CallbackTask)
def calc(syntax):
logger = get_or_create_task_logger(calc)
some_func()
logger.info('started')
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