我希望每个作业都能在log /目录中记录它自己的文件,其中文件名是taskid。
logger = get_task_logger(__name__)
@app.task(base=CallbackTask)
def calc(syntax):
some_func()
logger.info('started')
在我的worker中,我使用-f
参数设置日志文件以输出到。我想确保它将每个任务输出到它自己的日志文件。
答案 0 :(得分:2)
好像我迟到了3年。尽管如此,我的解决方案受到@Mikko Ohtamaa想法的启发。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记录句柄,使其变得与众不同。
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')
此处需要bind=True
才能在任务中提供ID。每次执行任务<task_id>.log
时,这将创建包含calc
的单个日志文件。
答案 1 :(得分:1)
以下是我粗略的,未经考验的方法。将其视为指导而非生产级代码。
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')