一切皆对象
def hi(name="yasoob"):
return "hi " + name
print(hi())
# output: 'hi yasoob'
# 我们甚至可以将一个函数赋值给一个变量，比如
greet = hi
# 我们这里没有在使用小括号，因为我们并不是在调用hi函数
# 而是在将它放在greet变量里头。我们尝试运行下这个
print(greet())
# output: 'hi yasoob'
# 如果我们删掉旧的hi函数，看看会发生什么！
del hi
print(hi())
#outputs: NameError
print(greet())
#outputs: 'hi yasoob'
原始的装饰器
def a_new_decorator(a_func):
def wrapTheFunction():
print("I am doing some boring work before executing a_func()")
a_func()
print("I am doing some boring work after executing a_func()")
return wrapTheFunction
def a_function_requiring_decoration():
print("I am the function which needs some decoration to remove my foul smell")
a_function_requiring_decoration()
#outputs: "I am the function which needs some decoration to remove my foul smell"
a_function_requiring_decoration = a_new_decorator(a_function_requiring_decoration)
#now a_function_requiring_decoration is wrapped by wrapTheFunction()
a_function_requiring_decoration()
#outputs:I am doing some boring work before executing a_func()
# I am the function which needs some decoration to remove my foul smell
# I am doing some boring work after executing a_func()
使用@的装饰器
@a_new_decorator
def a_function_requiring_decoration():
"""Hey you! Decorate me!"""
print("I am the function which needs some decoration to "
"remove my foul smell")
a_function_requiring_decoration()
#outputs: I am doing some boring work before executing a_func()
# I am the function which needs some decoration to remove my foul smell
# I am doing some boring work after executing a_func()
#the @a_new_decorator is just a short way of saying:
a_function_requiring_decoration = a_new_decorator(a_function_requiring_decoration)
蓝本规范
from functools import wraps
def decorator_name(f):
# @wraps接受一个函数来进行装饰，并加入了复制函数名称、注释文档、参数列表等等的功能。
# 这可以让我们在装饰器里面访问在装饰之前的函数的属性。
@wraps(f)
def decorated(*args, **kwargs):
if not can_run:
return "Function will not run"
return f(*args, **kwargs)
return decorated
@decorator_name
def func():
return("Function is running")
can_run = True
print(func())
# Output: Function is running
can_run = False
print(func())
# Output: Function will not run
带参数的装饰器
from functools import wraps
def logit(logfile='out.log'):
def logging_decorator(func):
@wraps(func)
def wrapped_function(*args, **kwargs):
log_string = func.__name__ + " was called"
print(log_string)
# 打开logfile，并写入内容
with open(logfile, 'a') as opened_file:
# 现在将日志打到指定的logfile
opened_file.write(log_string + '\n')
return func(*args, **kwargs)
return wrapped_function
return logging_decorator
@logit()
def myfunc1():
pass
myfunc1()
# Output: myfunc1 was called
# 现在一个叫做 out.log 的文件出现了，里面的内容就是上面的字符串
@logit(logfile='func2.log')
def myfunc2():
pass
myfunc2()
# Output: myfunc2 was called
# 现在一个叫做 func2.log 的文件出现了，里面的内容就是上面的字符串
装饰器类
from functools import wraps
class logit(object):
def __init__(self, logfile='out.log'):
self.logfile = logfile
def __call__(self, func):
@wraps(func)
def wrapped_function(*args, **kwargs):
log_string = func.__name__ + " was called"
print(log_string)
# 打开logfile并写入
with open(self.logfile, 'a') as opened_file:
# 现在将日志打到指定的文件
opened_file.write(log_string + '\n')
# 现在，发送一个通知
self.notify()
return func(*args, **kwargs)
return wrapped_function
def notify(self):
# logit只打日志，不做别的
pass
class email_logit(logit):
'''
一个logit的实现版本，可以在函数调用时发送email给管理员
'''
def __init__(self, email='admin@myproject.com', *args, **kwargs):
self.email = email
super(email_logit, self).__init__(*args, **kwargs)
def notify(self):
# 发送一封email到self.email
# 这里就不做实现了
pass
# 在打日志的基础上，还会多发送一封邮件给管理员。
@email_logit()
def myfunc1():
pass
