Python标准模块--logging


1 logging模块简介
logging模块是Python内置的标准模块,主要用于输出运行日志,可以设置输出日志的等级、日志保存路径、日志文件回滚等;相比print,具备如下优点:


可以通过设置不同的日志等级,在release版本中只输出重要信息,而不必显示大量的调试信息;
print将所有信息都输出到标准输出中,严重影响开发者从标准输出中查看其它数据;logging则可以由开发者决定将信息输出到什么地方,以及怎么输出;
2 logging模块使用
2.1 基本使用
配置logging基本的设置,然后在控制台输出日志,

import logging 

 logging.basicConfig(level = logging.INFO,format = '%(asctime)s - %(name)s - %(levelname)s - %(message)s') 

 logger = logging.getLogger(__name__) 



 ("Start print log") 

 logger.debug("Do something") 

 logger.warning("Something maybe fail.") 

 ("Finish") 

 运行时,控制台输出, 



 2016-10-09 19:11:19,434 - __main__ - INFO - Start print log 

 2016-10-09 19:11:19,434 - __main__ - WARNING - Something maybe fail. 

 2016-10-09 19:11:19,434 - __main__ - INFO - Finish 

 logging中可以选择很多消息级别,如debug、info、warning、error以及critical。通过赋予logger或者handler不同的级别,开发者就可以只输出错误信息到特定的记录文件,或者在调试时只记录调试信息。 



 例如,我们将logger的级别改为DEBUG,再观察一下输出结果, 



 logging.basicConfig(level = logging.DEBUG,format = '%(asctime)s - %(name)s - %(levelname)s - %(message)s') 

 控制台输出,可以发现,输出了debug的信息。 



 2016-10-09 19:12:08,289 - __main__ - INFO - Start print log 

 2016-10-09 19:12:08,289 - __main__ - DEBUG - Do something 

 2016-10-09 19:12:08,289 - __main__ - WARNING - Something maybe fail. 

 2016-10-09 19:12:08,289 - __main__ - INFO - Finish 

 logging.basicConfig函数各参数: 



 filename:指定日志文件名; 



 filemode:和file函数意义相同,指定日志文件的打开模式,'w'或者'a'; 



 format:指定输出的格式和内容,format可以输出很多有用的信息, 



 参数:作用 



 %(levelno)s:打印日志级别的数值 

 %(levelname)s:打印日志级别的名称 

 %(pathname)s:打印当前执行程序的路径,其实就是sys.argv[0] 

 %(filename)s:打印当前执行程序名 

 %(funcName)s:打印日志的当前函数 

 %(lineno)d:打印日志的当前行号 

 %(asctime)s:打印日志的时间 

 %(thread)d:打印线程ID 

 %(threadName)s:打印线程名称 

 %(process)d:打印进程ID 

 %(message)s:打印日志信息 

 datefmt:指定时间格式,同time.strftime(); 



 level:设置日志级别,默认为logging.WARNNING; 



 stream:指定将日志的输出流,可以指定输出到sys.stderr,sys.stdout或者文件,默认输出到sys.stderr,当stream和filename同时指定时,stream被忽略; 



 2.2 将日志写入到文件 

 2.2.1 将日志写入到文件 



 设置logging,创建一个FileHandler,并对输出消息的格式进行设置,将其添加到logger,然后将日志写入到指定的文件中, 



 import logging 

 logger = logging.getLogger(__name__) 

 logger.setLevel(level = logging.INFO) 

 handler = logging.FileHandler("log.txt") 

 handler.setLevel(logging.INFO) 

 formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') 

 handler.setFormatter(formatter) 

 logger.addHandler(handler) 



 ("Start print log") 

 logger.debug("Do something") 

 logger.warning("Something maybe fail.") 

 ("Finish") 

 log.txt中日志数据为, 



 2016-10-09 19:01:13,263 - __main__ - INFO - Start print log 

 2016-10-09 19:01:13,263 - __main__ - WARNING - Something maybe fail. 

 2016-10-09 19:01:13,263 - __main__ - INFO - Finish 

 2.2.2 将日志同时输出到屏幕和日志文件 



 logger中添加StreamHandler,可以将日志输出到屏幕上, 



 import logging 

 logger = logging.getLogger(__name__) 

 logger.setLevel(level = logging.INFO) 

 handler = logging.FileHandler("log.txt") 

 handler.setLevel(logging.INFO) 

 formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') 

 handler.setFormatter(formatter) 



 console = logging.StreamHandler() 

 console.setLevel(logging.INFO) 



 logger.addHandler(handler) 

 logger.addHandler(console) 



 ("Start print log") 

 logger.debug("Do something") 

 logger.warning("Something maybe fail.") 

 ("Finish") 

 可以在log.txt文件和控制台中看到, 



 2016-10-09 19:20:46,553 - __main__ - INFO - Start print log 

 2016-10-09 19:20:46,553 - __main__ - WARNING - Something maybe fail. 

 2016-10-09 19:20:46,553 - __main__ - INFO - Finish 

 可以发现,logging有一个日志处理的主对象,其他处理方式都是通过addHandler添加进去,logging中包含的handler主要有如下几种, 



 handler名称:位置;作用 



 StreamHandler:logging.StreamHandler;日志输出到流,可以是sys.stderr,sys.stdout或者文件 

 FileHandler:logging.FileHandler;日志输出到文件 

 BaseRotatingHandler:logging.handlers.BaseRotatingHandler;基本的日志回滚方式 

 RotatingHandler:logging.handlers.RotatingHandler;日志回滚方式,支持日志文件最大数量和日志文件回滚 

 TimeRotatingHandler:logging.handlers.TimeRotatingHandler;日志回滚方式,在一定时间区域内回滚日志文件 

 SocketHandler:logging.handlers.SocketHandler;远程输出日志到TCP/IP sockets 

 DatagramHandler:logging.handlers.DatagramHandler;远程输出日志到UDP sockets 

 SMTPHandler:logging.handlers.SMTPHandler;远程输出日志到邮件地址 

 SysLogHandler:logging.handlers.SysLogHandler;日志输出到syslog 

 NTEventLogHandler:logging.handlers.NTEventLogHandler;远程输出日志到Windows NT/2000/XP的事件日志 

 MemoryHandler:logging.handlers.MemoryHandler;日志输出到内存中的指定buffer 

 HTTPHandler:logging.handlers.HTTPHandler;通过"GET"或者"POST"远程输出到HTTP服务器 

 2.2.3 日志回滚 



 使用RotatingFileHandler,可以实现日志回滚, 



 import logging 

 from logging.handlers import RotatingFileHandler 

 logger = logging.getLogger(__name__) 

 logger.setLevel(level = logging.INFO) 

 #定义一个RotatingFileHandler,最多备份3个日志文件,每个日志文件最大1K 

 rHandler = RotatingFileHandler("log.txt",maxBytes = 1*1024,backupCount = 3) 

 rHandler.setLevel(logging.INFO) 

 formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') 

 rHandler.setFormatter(formatter) 



 console = logging.StreamHandler() 

 console.setLevel(logging.INFO) 

 console.setFormatter(formatter) 



 logger.addHandler(rHandler) 

 logger.addHandler(console) 



 ("Start print log") 

 logger.debug("Do something") 

 logger.warning("Something maybe fail.") 

 ("Finish") 

 可以在工程目录中看到,备份的日志文件, 



 2016/10/09  19:36               732 log.txt 

 2016/10/09  19:36               967 log.txt.1 

 2016/10/09  19:36               985 log.txt.2 

 2016/10/09  19:36               976 log.txt.3 

 2.3 设置消息的等级 

 可以设置不同的日志等级,用于控制日志的输出, 



 日志等级:使用范围 



 FATAL:致命错误 

 CRITICAL:特别糟糕的事情,如内存耗尽、磁盘空间为空,一般很少使用 

 ERROR:发生错误时,如IO操作失败或者连接问题 

 WARNING:发生很重要的事件,但是并不是错误时,如用户登录密码错误 

 INFO:处理请求或者状态变化等日常事务 

 DEBUG:调试过程中使用DEBUG等级,如算法中每个循环的中间状态 

 2.4 捕获traceback 

 Python中的traceback模块被用于跟踪异常返回信息,可以在logging中记录下traceback, 



 代码, 



 import logging 

 logger = logging.getLogger(__name__) 

 logger.setLevel(level = logging.INFO) 

 handler = logging.FileHandler("log.txt") 

 handler.setLevel(logging.INFO) 

 formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') 

 handler.setFormatter(formatter) 



 console = logging.StreamHandler() 

 console.setLevel(logging.INFO) 



 logger.addHandler(handler) 

 logger.addHandler(console) 



 ("Start print log") 

 logger.debug("Do something") 

 logger.warning("Something maybe fail.") 

 try: 

     open("sklearn.txt","rb") 

 except (SystemExit,KeyboardInterrupt): 

     raise 

 except Exception: 

     logger.error("Faild to open sklearn.txt from logger.error",exc_info = True) 



 ("Finish") 

 控制台和日志文件log.txt中输出, 



 Start print log 

 Something maybe fail. 

 Faild to open sklearn.txt from logger.error 

 Traceback (most recent call last): 

   File "G:\zhb7627\Code\Eclipse WorkSpace\PythonTest\test.py", line 23, in <module> 

     open("sklearn.txt","rb") 

 IOError: [Errno 2] No such file or directory: 'sklearn.txt' 

 Finish 

 也可以使用logger.exception(msg,_args),它等价于logger.error(msg,exc_info = True,_args), 



 将 



 logger.error("Faild to open sklearn.txt from logger.error",exc_info = True) 

 替换为, 



 logger.exception("Failed to open sklearn.txt from logger.exception") 

 控制台和日志文件log.txt中输出, 



 Start print log 

 Something maybe fail. 

 Failed to open sklearn.txt from logger.exception 

 Traceback (most recent call last): 

   File "G:\zhb7627\Code\Eclipse WorkSpace\PythonTest\test.py", line 23, in <module> 

     open("sklearn.txt","rb") 

 IOError: [Errno 2] No such file or directory: 'sklearn.txt' 

 Finish 

 2.5 多模块使用logging 

 主模块mainModule.py, 



 import logging 

 import subModule 

 logger = logging.getLogger("mainModule") 

 logger.setLevel(level = logging.INFO) 

 handler = logging.FileHandler("log.txt") 

 handler.setLevel(logging.INFO) 

 formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') 

 handler.setFormatter(formatter) 



 console = logging.StreamHandler() 

 console.setLevel(logging.INFO) 

 console.setFormatter(formatter) 



 logger.addHandler(handler) 

 logger.addHandler(console) 





 ("creating an instance of subModule.subModuleClass") 

 a = subModule.SubModuleClass() 

 ("calling subModule.subModuleClass.doSomething") 

 a.doSomething() 

 ("done with  subModule.subModuleClass.doSomething") 

 ("calling subModule.some_function") 

 subModule.som_function() 

 ("done with subModule.some_function") 

 子模块subModule.py, 



 import logging 



 module_logger = logging.getLogger("mainModule.sub") 

 class SubModuleClass(object): 

     def __init__(self): 

         self.logger = logging.getLogger("mainModule.sub.module") 

         self.("creating an instance in SubModuleClass") 

     def doSomething(self): 

         self.("do something in SubModule") 

         a = [] 

         a.append(1) 

         self.logger.debug("list a = " + str(a)) 

         self.("finish something in SubModuleClass") 



 def som_function(): 

     module_("call function some_function") 

 执行之后,在控制和日志文件log.txt中输出, 



 2016-10-09 20:25:42,276 - mainModule - INFO - creating an instance of subModule.subModuleClass 

 2016-10-09 20:25:42,279 - mainModule.sub.module - INFO - creating an instance in SubModuleClass 

 2016-10-09 20:25:42,279 - mainModule - INFO - calling subModule.subModuleClass.doSomething 

 2016-10-09 20:25:42,279 - mainModule.sub.module - INFO - do something in SubModule 

 2016-10-09 20:25:42,279 - mainModule.sub.module - INFO - finish something in SubModuleClass 

 2016-10-09 20:25:42,279 - mainModule - INFO - done with  subModule.subModuleClass.doSomething 

 2016-10-09 20:25:42,279 - mainModule - INFO - calling subModule.some_function 

 2016-10-09 20:25:42,279 - mainModule.sub - INFO - call function some_function 

 2016-10-09 20:25:42,279 - mainModule - INFO - done with subModule.some_function


首先在主模块定义了logger'mainModule',并对它进行了配置,就可以在解释器进程里面的其他地方通过getLogger('mainModule')得到的对象都是一样的,不需要重新配置,可以直接使用。定义的该logger的子logger,都可以共享父logger的定义和配置,所谓的父子logger是通过命名来识别,任意以'mainModule'开头的logger都是它的子logger,例如'mainModule.sub'。


实际开发一个application,首先可以通过logging配置文件编写好这个application所对应的配置,可以生成一个根logger,如'PythonAPP',然后在主函数中通过fileConfig加载logging配置,接着在application的其他地方、不同的模块中,可以使用根logger的子logger,如'PythonAPP.Core','PythonAPP.Web'来进行log,而不需要反复的定义和配置各个模块的logger。


3 通过JSON或者YAML文件配置logging模块
尽管可以在Python代码中配置logging,但是这样并不够灵活,最好的方法是使用一个配置文件来配置。在Python 2.7及以后的版本中,可以从字典中加载logging配置,也就意味着可以通过JSON或者YAML文件加载日志的配置。


3.1 通过JSON文件配置
JSON配置文件,

{ 

     "version":1, 

     "disable_existing_loggers":false, 

     "formatters":{ 

         "simple":{ 

             "format":"%(asctime)s - %(name)s - %(levelname)s - %(message)s" 

         } 

     }, 

     "handlers":{ 

         "console":{ 

             "class":"logging.StreamHandler", 

             "level":"DEBUG", 

             "formatter":"simple", 

             "stream":"ext://sys.stdout" 

         }, 

         "info_file_handler":{ 

             "class":"logging.handlers.RotatingFileHandler", 

             "level":"INFO", 

             "formatter":"simple", 

             "filename":"info.log", 

             "maxBytes":"10485760", 

             "backupCount":20, 

             "encoding":"utf8" 

         }, 

         "error_file_handler":{ 

             "class":"logging.handlers.RotatingFileHandler", 

             "level":"ERROR", 

             "formatter":"simple", 

             "filename":"errors.log", 

             "maxBytes":10485760, 

             "backupCount":20, 

             "encoding":"utf8" 

         } 

     }, 

     "loggers":{ 

         "my_module":{ 

             "level":"ERROR", 

             "handlers":["info_file_handler"], 

             "propagate":"no" 

         } 

     }, 

     "root":{ 

         "level":"INFO", 

         "handlers":["console","info_file_handler","error_file_handler"] 

     } 

 } 

 通过JSON加载配置文件,然后通过logging.dictConfig配置logging, 



 import json 

 import logging.config 

 import os 



 def setup_logging(default_path = "logging.json",default_level = logging.INFO,env_key = "LOG_CFG"): 

     path = default_path 

     value = os.getenv(env_key,None) 

     if value: 

         path = value 

     if os.path.exists(path): 

         with open(path,"r") as f: 

             config = json.load(f) 

             logging.config.dictConfig(config) 

     else: 

         logging.basicConfig(level = default_level) 



 def func(): 

     logging.info("start func") 



     logging.info("exec func") 



     logging.info("end func") 



 if __name__ == "__main__": 

     setup_logging(default_path = "logging.json") 

     func() 

 3.2 通过YAML文件配置 

 通过YAML文件进行配置,比JSON看起来更加简介明了, 



 version: 1 

 disable_existing_loggers: False 

 formatters: 

         simple: 

             format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s" 

 handlers: 

     console: 

             class: logging.StreamHandler 

             level: DEBUG 

             formatter: simple 

             stream: ext://sys.stdout 

     info_file_handler: 

             class: logging.handlers.RotatingFileHandler 

             level: INFO 

             formatter: simple 

             filename: info.log 

             maxBytes: 10485760 

             backupCount: 20 

             encoding: utf8 

     error_file_handler: 

             class: logging.handlers.RotatingFileHandler 

             level: ERROR 

             formatter: simple 

             filename: errors.log 

             maxBytes: 10485760 

             backupCount: 20 

             encoding: utf8 

 loggers: 

     my_module: 

             level: ERROR 

             handlers: [info_file_handler] 

             propagate: no 

 root: 

     level: INFO 

     handlers: [console,info_file_handler,error_file_handler] 

 通过YAML加载配置文件,然后通过logging.dictConfig配置logging, 



 import yaml 

 import logging.config 

 import os 



 def setup_logging(default_path = "logging.yaml",default_level = logging.INFO,env_key = "LOG_CFG"): 

     path = default_path 

     value = os.getenv(env_key,None) 

     if value: 

         path = value 

     if os.path.exists(path): 

         with open(path,"r") as f: 

             config = yaml.load(f) 

             logging.config.dictConfig(config) 

     else: 

         logging.basicConfig(level = default_level) 



 def func(): 

     logging.info("start func") 



     logging.info("exec func") 



     logging.info("end func") 



 if __name__ == "__main__": 

     setup_logging(default_path = "logging.yaml") 

     func()