logging&程序目录结构

0.知识点补充

1.字符串格式化

1. %s

   #方式1:%s与替换值相对性,构造元组
   msg = "我是%s,年龄%s" %('alex',19,)
   print(msg)
   
   #方式2:%s中间加一个变量,最后构造字典匹配值
   msg = "我是%(n1)s,年龄%(n2)s" % {'n1': 'alex', 'n2': 123, }
   print(msg)
   

2. format

   # v1 = "我是{0},年龄{1}".format('alex',19)
   v1 = "我是{0},年龄{1}".format(*('alex',19,))
   print(v1)
   
   # v2 = "我是{name},年龄{age}".format(name='alex',age=18)
   v2 = "我是{name},年龄{age}".format(**{'name':'alex','age':18})
   print(v2)
   

2.有序字典Orderedict

from collections import OrderedDict

info = OrderedDict()
info['k1'] = 123
info['k2'] = 456

print(info.keys())
print(info.values())
print(info.items())

3.栈和队列

class Stack(object):
    pass

class Queue(object):
    pass

4.反射

class Foo(object):
    def get(self):
        pass

obj = Foo()
# if hasattr(obj,'post'): 
#     getattr(obj,'post')

v1 = getattr(obj,'get',None) # 推荐
print(v1)

5.nametuple可命名元组

from collections import namedtuple   # 可命名元组
Course = namedtuple('Course',['name','price','teacher'])
python = Course('python',19800,'alex')
print(python)
print(python.name)
print(python.price)
    # 创建一个类，这个类没有方法，所有属性的值都不能修改

1.单例模式

• 单例模式: 无论实例化多少次,都用第一次实例化的对象.

• 标准格式

  • __new__创建一个实例化对象,并且在init之前执行

  class Singleton(object):
      instance= None
      def __new__ (cls,*args,**kwargs):
      	if not cls.instance:
              cls.instance= object.__new__(cls)
          return cls.instance
  

2.logging(日志模块)

• 快速编写格式(扩展性不强)

  import logging
  import requests
  
  # 日志配置
  logging.basicConfig(
      filename='log.log',
      format=' %(asctime)s - %(name)s - %(levelname)s -%(module)s:  %(message)s',
      datefmt='%Y-%m-%d %H:%M:%S %p',
      level=logging.ERROR)
  # 异常处理
  try:
      requests.get('http://www.xxx.com')
  except Exception  as e:
      mes = str(e)
      # 日志生成
      logging.error(mes, ext_info=True)    #ext_info=True保存堆栈信息
  

• 推荐编写方式

  import logging
  file_hander = logging.FileHandler(filename='log.log',mode='a',encoding='utf-8',)
  logging.basicConfig(
      format=%(asctime)s - %(name)s - %(levelname)s -%(module)s:  %(message)s',
      datafmt='%Y-%m-%d %H:%M:%S %p',
      handlers=[file_handler,],
      level=logging.ERROR
  )
  
  logging.error('你好')
  

• 更改调用机制:

  import logging
  
  def get_logger():
      file_hander = logging.FileHandler(filename='log.log',mode='a',encoding='utf-	8',)
      logging.basicConfig(
          format=%(asctime)s - %(name)s - %(levelname)s -%(module)s:  %(message)s',
          datafmt='%Y-%m-%d %H:%M:%S %p',
          handlers=[file_handler,],
          level=logging.ERROR
      )
  	return logging
  logger = get_logger()
  
  
  logging.error('你好')
  

• 推荐日志处理方式+日志切割

  import time
  import logging
  from logging import handlers
  
  file_handler = handlers.TimedRotatingFileHandler(filename='x3.log', when='s', interval=5, encoding='utf-8')
  logging.basicConfig(
      format='%(asctime)s - %(name)s - %(levelname)s -%(module)s:  %(message)s',
      datefmt='%Y-%m-%d %H:%M:%S %p',
      handlers=[file_handler,],
      level=logging.ERROR
  )
  
  for i in range(1,100000):
      time.sleep(1)
      logging.error(str(i))
  

• 注意事项

  # 在应用日志时，如果想要保留异常的堆栈信息。
  import logging
  import requests
  
  logging.basicConfig(
      filename='wf.log',
      format='%(asctime)s - %(name)s - %(levelname)s -%(module)s:  %(message)s',
      datefmt='%Y-%m-%d %H:%M:%S %p',
      level=logging.ERROR
  )
  
  try:
      requests.get('http://www.xxx.com')
  except Exception as e:
      msg = str(e) # 调用e.__str__方法
      logging.error(msg,exc_info=True)