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(转)python logging模块

程序员文章站 2022-04-14 15:43:40
原文:http://www.cnblogs.com/dahu-daqing/p/7040764.html 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 ......

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:

  1. 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;
  2. 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,

(转)python logging模块
(转)python logging模块
import logging
logging.basicconfig(level = logging.info,format = '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getlogger(__name__)

logger.info("start print log")
logger.debug("do something")
logger.warning("something maybe fail.")
logger.info("finish")
(转)python logging模块
(转)python logging模块

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,

(转)python logging模块
(转)python logging模块
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)

logger.info("start print log")
logger.debug("do something")
logger.warning("something maybe fail.")
logger.info("finish")
(转)python logging模块
(转)python logging模块

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,

(转)python logging模块
(转)python logging模块
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)

logger.info("start print log")
logger.debug("do something")
logger.warning("something maybe fail.")
logger.info("finish")
(转)python logging模块
(转)python logging模块

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,

(转)python logging模块
(转)python logging模块
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)

logger.info("start print log")
logger.debug("do something")
logger.warning("something maybe fail.")
logger.info("finish")
(转)python logging模块
(转)python logging模块

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,

(转)python logging模块
(转)python logging模块
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)

logger.info("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)

logger.info("finish")
(转)python logging模块
(转)python logging模块

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),

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,

(转)python logging模块
(转)python logging模块
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)


logger.info("creating an instance of submodule.submoduleclass")
a = submodule.submoduleclass()
logger.info("calling submodule.submoduleclass.dosomething")
a.dosomething()
logger.info("done with  submodule.submoduleclass.dosomething")
logger.info("calling submodule.some_function")
submodule.som_function()
logger.info("done with submodule.some_function")
(转)python logging模块
(转)python logging模块

子模块submodule.py,

(转)python logging模块
(转)python logging模块
import logging

module_logger = logging.getlogger("mainmodule.sub")
class submoduleclass(object):
    def __init__(self):
        self.logger = logging.getlogger("mainmodule.sub.module")
        self.logger.info("creating an instance in submoduleclass")
    def dosomething(self):
        self.logger.info("do something in submodule")
        a = []
        a.append(1)
        self.logger.debug("list a = " + str(a))
        self.logger.info("finish something in submoduleclass")

def som_function():
    module_logger.info("call function some_function")
(转)python logging模块
(转)python logging模块

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,

(转)python logging模块
(转)python logging模块
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()
(转)python logging模块
(转)python logging模块

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,

(转)python logging模块
(转)python logging模块
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()
    
(转)python logging模块
(转)python logging模块

4 reference

每个 python 程序员都要知道的日志实践

python标准模块logging