大綱
今天我們就來一起挖一挖Python/ target=_blank class=infotextkey>Python里面的各種日志的用法，廢話不多說，日志包我為了講清楚，涉及到的內容大綱如下：
基本打印
如上圖看到的那么簡單，在python中打印日志只要import logging包即可。直接執行效果如下圖：
日志配置
如果沒有日志配置，日志只能打印到stdout，那就會很糟糕，因此我們需要有一些配置可以輸出到文件
import logging # add filemode="w" to overwrite logging.basicConfig(filename="sample.log", level=logging.INFO) logging.debug("This is a debug message") # This one won't log logging.info("Informational message") logging.error("An error has hAppened!")
增加basicconfig后日志就可以打印到指定文件，但是日志我們還需要設置日志格式
import logging logger = logging.getLogger('stream_logger') logger.setLevel(logging.INFO) console = logging.StreamHandler() formatter = logging.Formatter('%(asctime)s - %(name)s - %(message)s') console.setFormatter(formatter) logger.addHandler(console) logger.info("This is an informational message")
在python中還可以從配置文件讀取日志規則
import logging import logging.config logging.config.fileConfig('logging.conf') logger = logging.getLogger("exampleApp") logger.info("Program started") logger.info("Done!")
logging.conf配置如下：
[loggers] keys=root,exampleApp [handlers] keys=fileHandler, consoleHandler [formatters] keys=myFormatter [logger_root] level=CRITICAL handlers=consoleHandler [logger_exampleApp] level=INFO handlers=fileHandler qualname=exampleApp [handler_consoleHandler] class=StreamHandler level=DEBUG formatter=myFormatter args=(sys.stdout,) [handler_fileHandler] class=FileHandler formatter=myFormatter args=("config.log",) [formatter_myFormatter] format=%(asctime)s - %(name)s - %(levelname)s - %(message)s datefmt=日志過濾
通過Formatter就可以搞定日志格式問題，如果生產環境日志太多，又想有一些日志過濾。
import logging import sys class MyFilter(logging.Filter): def filter(self, record): if record.funcName == 'a': return False return True logger = logging.getLogger('filter_test') logger.addFilter(MyFilter()) def a(): """ Ignore this function's log messages """ logger.debug('Message from function a') def b(): logger.debug('Message from B') if __name__ == '__main__': logging.basicConfig(stream=sys.stderr, level=logging.DEBUG) a() b()
這樣你的日志就可以實現過濾效果。
日志切割
可是生產環境真正運行的服務，又不僅僅是運行一天，日志一直打印到同一個文件非常不方便debug和定位，有時候一天幾個G的文件，如果運行30天去查日志時會非常耗時，我們需要一個日志切割的邏輯來保障日志可以按照時間動態切換文件。
- 按照時間切割
import logging import time from logging.handlers import TimedRotatingFileHandler def create_timed_rotating_log(path): """""" logger = logging.getLogger("Rotating Log") logger.setLevel(logging.INFO) handler = TimedRotatingFileHandler(path, when="s", interval=5, backupCount=5) logger.addHandler(handler) for i in range(6): logger.info("This is a test!") time.sleep(75) if __name__ == "__main__": log_file = "timed_rotation.log" create_timed_rotating_log(log_file)
- 按照大小切割，并設置保留數
import logging import time from logging.handlers import RotatingFileHandler def create_rotating_log(path): """ Creates a rotating log """ logger = logging.getLogger("Rotating Log") logger.setLevel(logging.INFO) # add a rotating handler handler = RotatingFileHandler(path, maxBytes=20, backupCount=5) logger.addHandler(handler) for i in range(10): logger.info("This is test log line %s" % i) time.sleep(1.5) if __name__ == "__main__": log_file = "rotated.log" create_rotating_log(log_file)多進程日志
在python中因為受GIL的影響，涉及到并發性能問題時經常使用多進程方式來解決，此時多進程日志打印會受到文件鎖的影響，為了避免日志打印錯亂，日志異常，我們針對這種場景需要定制化處理下日志：
import logging from logging.handlers import RotatingFileHandler, QueueHandler from multiprocessing import Process class MultiProcessQueueLoggingListner(Process): def __init__(self, name, queue): super().__init__() self.name = name self.queue = queue self.logger = logging.getLogger(name) self.file_handler = RotatingFileHandler(name, maxBytes=536870912, backupCount=2) self.formatter = logging.Formatter('%(asctime)s %(processName)-10s %(name)s %(levelname)-8s %(message)s') self.file_handler.setFormatter(self.formatter) self.logger.addHandler(self.file_handler) def run(self): while True: try: record = self.queue.get() if record is None: break self.logger.handle(record) except Exception: import sys, traceback print('Whoops! Problem:', file=sys.stderr) traceback.print_exc(file=sys.stderr) class MulitProcessQueueLogger(object): def __init__(self, name, queue): self.name = name self.queue = queue self.queue_handler = QueueHandler(queue) self.logger = logging.getLogger(name) self.logger.addHandler(self.queue_handler) self.logger.setLevel(logging.DEBUG)
測試代碼如下：
import multi_process_logging import multiprocessing from time import sleep def worker(po): name = multiprocessing.current_process().name po = multi_process_logging.MulitProcessQueueLogger('test.log', q) print("In worker") for i in range(10): po.logger.info(f"Logging from {name} line {i}") po.queue.put(None) def main(): q = multiprocessing.Queue() lp = multi_process_logging.MultiProcessQueueLoggingListner('test.log', q) lp.start() p = multiprocessing.Process(target=worker, args=(q,)) p.start() p.join() lp.join() if __name__ == '__main__': main()總結
至此，大部分python打印日志的場景使用方式都講解到了，希望對讀者有所幫助。
