Python Decorator Example Analysis

Overview

An adorner is essentially a Python function that allows other functions to add extra functionality without any code changes, and the return value of the adorner is also a function object.

We need a decorator that can test the run time of the function, which can be defined as follows:

def timer(func):    def wrapper(*args, **kwargs):        start_time = time.time()        res = func(*args, **kwargs)        end_time = time.time()        print("Run time is: %s" % (end_time - start_time))        return res    return wrapper

Because it is a decorator, it takes a function as an argument and returns a function. We will use the Python @ syntax to place the decorator at the definition of the function:

@timerdef fun():    time.sleep(1)    print("This is a test")    return "OK"

The result of the operation is:

This is a testRun time is: 1.0000572204589844OK

Putting @timer in Fun () is equivalent to executing a statement:

fun = timer(fun)

If the decorator itself needs to pass in parameters, it is necessary to write a higher-order function that returns decorator, such as a name:

def timer(name):    def decorator(func):        def wrapper(*args, **kwargs):            start_time = time.time()            res = func(*args, **kwargs)            end_time = time.time()            print("Name is: %s ; Run time is: %s" % (name, (end_time - start_time)))            return res        return wrapper    return decorator

The call and the results are displayed as follows:

@timer("Lance#")def fun():    time.sleep(1)    print("This is a test")    return "OK"

This is a testName is: Lance# ; Run time is: 1.0000572204589844OK

Compared to the two-layer nested decorator, the three-layer nesting effect is this:

fun = timer("Lance#")(fun)

Because a function is also an object, it also has properties such as __name__.
In the fun () function before the adorner, calling the fun __name__ property results in ' fun ', but after the decorator decoration function, their __name__ has changed from the original ' fun ' to ' wrapper '

Therefore, it is necessary to copy the original function's __name__ and other properties into the wrapper () function, otherwise, some code that relies on the function signature will be executed in error.

Python's built-in Functools.wraps can accomplish this task, so a complete decorator is written as follows:

import functoolsdef timer(func):    @functools.wraps(func)    def wrapper(*args, **kwargs):        start_time = time.time()        res = func(*args, **kwargs)        end_time = time.time()        print("Run time is: %s" % (end_time - start_time))        return res    return wrapper

The overall code is as follows:

__Author__ = "Lance#"# -*- coding = utf-8 -*-import timeimport functoolsdef timer(name):    def decorator(func):        @functools.wraps(func)        def wrapper(*args, **kwargs):            start_time = time.time()            res = func(*args, **kwargs)            end_time = time.time()            print("Name is: %s ; Run time is: %s" % (name, (end_time - start_time)))            return res        return wrapper    return decorator@timer("Lance#")def fun():    time.sleep(1)    print("This is a test")    return "OK"if __name__ == '__main__':    print(fun())

Python Decorator Example Analysis