瞎比比
这篇文章其实早在一个月之前就写好了。奈何,加班猛如虎,真的怕了。直至今天才幸运地有了个双休,赶紧排版一下文章发布了。以下为正文。
源码地址:
https://github.com/zonezoen/blog/tree/master/Python/ target=_blank class=infotextkey>Python/logging_model
在初学 Python 的时候,我们使用
print("hello world")
输出了我们的第一行代码。在之后的日子里,便一直使用 print 进行调试(当然,还有 IDE 的 debug 模式)。但是,当你在线上运行 Python 脚本的时候,你并不可能一直守着你的运行终端。可是如果不守着的话,每当出现 bug ,错误又无从查起。这个时候,你需要对你的调试工具进行更新换代了,这里我推荐一个优雅的调试工具 logging。
与 print 相比 logging 有什么优势?
那既然我推荐这个工具,它凭什么要被推荐呢?且来看看它有什么优势:
基础用法
下面涉及到的代码我都省略了导包部分,详见源码(后台回复 logging 获取源码)
base_usage.py
logging.basicConfig(level=log_level, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s') logger = logging.getLogger(__name__) logger.info("Log level info") logger.debug("Log level debug") logger.warning("Log level warning") # 捕获异常,并打印出出错行数 try: raise Exception("my exception") except (SystemExit, KeyboardInterrupt): raise except Exception: logger.error("there is an error =>", exc_info=True)
level 为日志等级,分为:
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
foamat 可以格式化输出,其参数有如下:
%(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
捕获异常,以下两行代码都具有相同的作用
logger.exception(msg,_args) logger.error(msg,exc_info = True,_args)
保存到文件,并输出到命令行
这个用法直接 copy 使用就行
import logging # 写入文件 import logging logger = logging.getLogger(__name__) logger.setLevel(level=logging.INFO) handler = logging.FileHandler("info.log") handler.setLevel(logging.INFO) formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') handler.setFormatter(formatter) logger.addHandler(handler) logger.info("Log level info") logger.debug("Log level debug") logger.warning("Log level warning") # 写入文件,同时输出到屏幕 import logging logger = logging.getLogger(__name__) logger.setLevel(level = logging.INFO) handler = logging.FileHandler("info.log") 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("Log level info") logger.debug("Log level debug") logger.warning("Log level warning")
多模块使用 logging
被调用者的日志格式会与调用者的日志格式一样
main.py
# -*- coding: utf-8 -*- __auth__ = 'zone' __date__ = '2019/6/17 下午11:46' ''' 公众号:zone7 小程序:编程面试题库 ''' import os import logging from python.logging_model.code import sub_of_main logger = logging.getLogger("zone7Model") 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) sub = sub_of_main.SubOfMain() logger.info("main module log") sub.print_some_log()
sub_of_main.py
# -*- coding: utf-8 -*- __auth__ = 'zone' __date__ = '2019/6/17 下午11:47' ''' 公众号:zone7 小程序:编程面试题库 ''' import logging module_logger = logging.getLogger("zone7Model.sub.module") class SubOfMain(object): def __init__(self): self.logger = logging.getLogger("zone7Model.sub.module") self.logger.info("init sub class") def print_some_log(self): self.logger.info("sub class log is printed") def som_function(): module_logger.info("call function some_function")
使用配置文件配置 logging
这里分别给出了两种配置文件的使用案例,都分别使用了三种输出,输出到命令行、输出到文件、将错误信息独立输出到一个文件
log_cfg.json
{ "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_handler2"], "propagate":"no" } }, "root":{ "level":"INFO", "handlers":["console","info_file_handler","error_file_handler"] } }
通过 json 文件读取配置:
import json import logging.config import os def set_log_cfg(default_path="log_cfg.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 record_some_thing(): logging.info("Log level info") logging.debug("Log level debug") logging.warning("Log level warning") if __name__ == "__main__": set_log_cfg(default_path="log_cfg.json") record_some_thing()
log_cfg.yaml
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 文件读取配置:
import yaml import logging.config import os def set_log_cfg(default_path="log_cfg.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 record_some_thing(): logging.info("Log level info") logging.debug("Log level debug") logging.warning("Log level warning") if __name__ == "__main__": set_log_cfg(default_path="log_cfg.yaml") record_some_thing()