Python Decorator and Threading Combined to Improve Interface Access Efficiency Methods

def outer(fun):
    def inner(*args,**kwargs):
        return fun(*args,**kwargs)
    return inner
# Decorate the two functions with decorators
@outer
def num1():
    print('a')
@outer
def num2():
    print('b')
if __name__ == '__main__':
    print(num1.__name__)
    print(num2.__name__)
The output of the above code：
inner
inner
Characteristics of the decorator:Using a custom decorator changes the function name of the decorated function，Generally decorators don't have to take this into account，But if more than one function is decorated by two decorators it will report an error，Because the function name is the same

import functools
def outer(fun):
    @(fun)
    def inner(*args,**kwargs):
        return fun(*args,**kwargs)
    return inner

def async_call(fun):
    def wrapper(*args, **kwargs):
        Thread(target=fun, args=args, kwargs=kwargs).start()
    return wrapper

import time
def coast_time(func):
    def fun(*args, **kwargs):
        t = time.perf_counter()
        result = func(*args, **kwargs)
        print(f'func {func.__name__} coast time:{time.perf_counter() - t:.8f} s')
        return result
    return fun

from time import sleep
from time import time
import time
from threading import Thread
# It's a decorator for counting time #
def coast_time(func):
    def fun(*args, **kwargs):
        t = time.perf_counter()
        result = func(*args, **kwargs)
        print(f'func {func.__name__} coast time:{time.perf_counter() - t:.8f} s')
        return result
    return fun
# This is a decorator to create threads, if you are interested you can save it and use it directly!
def async_call(fun):
    def wrapper(*args, **kwargs):
        Thread(target=fun, args=args, kwargs=kwargs).start()
    return wrapper
@coast_time
@async_call
def hello():
    print('start')
    sleep(2)
    print('end')
    return
if __name__ == "__main__":
    hello()