python logger 使用技巧集锦
1. 简单使用
import logging
# 基本设置
# 如果没有设置，则可以使用该设置用于显示
logging.basicConfig(level='DEBUG', datefmt='%Y-%m-%d %H:%M:%S',
format='%(asctime)s [%(name)s] %(levelname)s %(message)s')
logger = logging.getLogger('simple_use')
2. 为所有 logger 设置 level
2.1. 使用 disable
import logging
# 关闭所有 INFO 以及 INFO 以下的日志输出
logging.disable(logging.INFO)
# 取消上面的设置
logging.disable(logging.NOTSET)
2.2. 使用 root
import logging
logging.root.setLevel(logging.INFO)
设置 root 的 logger 会影响到所有继承的 logger（基本代表了所有的 logger）。
2.3. 参考
Set global minimum logging level across all loggers in Python/Django - Stack Overflow
3. 错误信息追踪
3.1. exc_info 参数解释
关于 logger 的记录方法都带有参数 exc_info，该值默认为空，可为布尔值。官方解释为：
If exc_info does not evaluate as false, it causes exception information to be added to the logging message. If an exception tuple (in the format returned by
sys.exc_info()) or an exception instance is provided, it is used; otherwise,sys.exc_info()is called to get the exception information.
对于 sys.exc_info() 的解释为：
This function returns a tuple of three values that give information about the exception that is currently being handled. The information returned is specific both to the current thread and to the current stack frame. If the current stack frame is not handling an exception, the information is taken from the calling stack frame, or its caller, and so on until a stack frame is found that is handling an exception. Here, “handling an exception” is defined as “executing an except clause.” For any stack frame, only information about the exception being currently handled is accessible.
If no exception is being handled anywhere on the stack, a tuple containing three
Nonevalues is returned. Otherwise, the values returned are(type, value, traceback). Their meaning is: type gets the type of the exception being handled (a subclass ofBaseException); value gets the exception instance (an instance of the exception type); traceback gets a traceback object which encapsulates the call stack at the point where the exception originally occurred.
简单来说，就是默认从当前环境的栈中自动读取（如果有错误），该方法会返回一个包含三个元素的元组，如果没有错误，三个元素皆为 None ；如果有则依次为：错误类型，错误对象，错误追踪对象。
比如：
import logging
import sys
try:
1 / 0
except ZeroDivisionError:
print(sys.exc_info())
输出为：
(<class 'ZeroDivisionError'>, ZeroDivisionError('division by zero'), <traceback object at 0x000001A0FEE53608>)
如果该参数为 True，模块会自动调用 sys.exc_info() 方法获取错误信息，但有时候我们需要手动传入错误信息记录，因此，也可自己构造 exc_info 参数所需的信息，比如：
import logging
logging.basicConfig(level='DEBUG', datefmt='%Y-%m-%d %H:%M:%S',
format='%(asctime)s [%(name)s] %(levelname)s %(message)s')
try:
1 / 0
except ZeroDivisionError as e:
err = ValueError('The denominator cannot be 0!')
logging.info('division wrong: ',
exc_info=(ValueError, err, e.__traceback__))
输出为：
2020-10-21 15:19:28 [root] INFO division wrong:
Traceback (most recent call last):
File "D:/OneDrive/works-tmp/gyyenterprise/gyyspider/spiders/products/hc.py", line 13, in <module>
1 / 0
ValueError: The denominator cannot be 0!
当然，如果不需要自定义错误信息，也可使用 logging.execption(e) 方法将捕获的错误传入直接记录。
4. 带有文件和屏幕双向输出的 logger
自定义格式（加入自定义的参数）- 文件和屏幕的双向输出：
import logging
import os
import time
import weakref
from lzz.settings import BASE_DIR
_handlers = weakref.WeakValueDictionary()
log_fmt = '%(asctime)s [%(name)s] %(levelname)s %(message)s'
date_fmt = '%Y-%m-%d %H:%M:%S'
def get_logger(name, level='DEBUG', folder=None, filename_fmt=None):
formatter = logging.Formatter(
fmt=log_fmt,
datefmt=date_fmt,
)
logger = logging.getLogger(name)
logger.setLevel(level)
if 'stream' not in _handlers:
stream = logging.StreamHandler()
stream.setFormatter(formatter)
_handlers['stream'] = stream
logger.addHandler(_handlers['stream'])
if folder:
if 'file' not in _handlers:
par = os.path.join(BASE_DIR, r'logs\upload\{}'.format(folder))
if not os.path.exists(par):
os.makedirs(par)
filename = f"{time.strftime(filename_fmt or '%Y%m%d')}.log"
path = os.path.join(par, filename)
file_handler = logging.FileHandler(filename=path, encoding='utf-8')
_handlers['file'] = file_handler
logger.addHandler(_handlers['file'])
return logger
