Home Backend Development Python Tutorial Python装饰器使用示例及实际应用例子

Python装饰器使用示例及实际应用例子

Jun 10, 2016 pm 03:17 PM
python Usage example Practical application Decorator

测试1

deco运行,但myfunc并没有运行

复制代码 代码如下:

def deco(func):
    print 'before func'
    return func

def myfunc():
    print 'myfunc() called'
 
myfunc = deco(myfunc)

测试2

需要的deco中调用myfunc,这样才可以执行

复制代码 代码如下:

def deco(func):
    print 'before func'
    func()
    print 'after func'
    return func

def myfunc():
    print 'myfunc() called'
 
myfunc = deco(myfunc)

测试3

@函数名 但是它执行了两次

复制代码 代码如下:

def deco(func):
    print 'before func'
    func()
    print 'after func'
    return func

@deco
def myfunc():
    print 'myfunc() called'

myfunc()

测试4

这样装饰才行

复制代码 代码如下:

def deco(func):
    def _deco():
        print 'before func'
        func()
        print 'after func'
    return _deco

@deco
def myfunc():
    print 'myfunc() called'
 
myfunc()

测试5

@带参数,使用嵌套的方法

复制代码 代码如下:

def deco(arg):
    def _deco(func):
        print arg
        def __deco():
            print 'before func'
            func()
            print 'after func'
        return __deco
    return _deco

@deco('deco')
def myfunc():
    print 'myfunc() called'
 
myfunc()

测试6

函数参数传递

复制代码 代码如下:

def deco(arg):
    def _deco(func):
        print arg
        def __deco(str):
            print 'before func'
            func(str)
            print 'after func'
        return __deco
    return _deco

@deco('deco')
def myfunc(str):
    print 'myfunc() called ', str
 
myfunc('hello')

测试7

未知参数个数

复制代码 代码如下:

def deco(arg):
    def _deco(func):
        print arg
        def __deco(*args, **kwargs):
            print 'before func'
            func(*args, **kwargs)
            print 'after func'
        return __deco
    return _deco

@deco('deco1')
def myfunc1(str):
    print 'myfunc1() called ', str

@deco('deco2')
def myfunc2(str1,str2):
    print 'myfunc2() called ', str1, str2
 
myfunc1('hello')
 
myfunc2('hello', 'world')

测试8

class作为修饰器

复制代码 代码如下:

class myDecorator(object):
 
    def __init__(self, fn):
        print "inside myDecorator.__init__()"
        self.fn = fn
 
    def __call__(self):
        self.fn()
        print "inside myDecorator.__call__()"
 
@myDecorator
def aFunction():
    print "inside aFunction()"
 
print "Finished decorating aFunction()"
 
aFunction()

测试9

复制代码 代码如下:

class myDecorator(object):
 
    def __init__(self, str):
        print "inside myDecorator.__init__()"
        self.str = str
        print self.str
 
    def __call__(self, fn):
        def wrapped(*args, **kwargs):
            fn()
            print "inside myDecorator.__call__()"
        return wrapped
 
@myDecorator('this is str')
def aFunction():
    print "inside aFunction()"
 
print "Finished decorating aFunction()"
 
aFunction()

实例

给函数做缓存 --- 斐波拉契数列

复制代码 代码如下:

from functools import wraps
def memo(fn):
    cache = {}
    miss = object()
    
    @wraps(fn)
    def wrapper(*args):
        result = cache.get(args, miss)
        if result is miss:
            result = fn(*args)
            cache[args] = result
        return result
 
    return wrapper
 
@memo
def fib(n):
    if n         return n
    return fib(n - 1) + fib(n - 2)

print fib(10)

注册回调函数 --- web请求回调

复制代码 代码如下:

class MyApp():
    def __init__(self):
        self.func_map = {}
 
    def register(self, name):
        def func_wrapper(func):
            self.func_map[name] = func
            return func
        return func_wrapper
 
    def call_method(self, name=None):
        func = self.func_map.get(name, None)
        if func is None:
            raise Exception("No function registered against - " + str(name))
        return func()
 
app = MyApp()
 
@app.register('/')
def main_page_func():
    return "This is the main page."
 
@app.register('/next_page')
def next_page_func():
    return "This is the next page."
 
print app.call_method('/')
print app.call_method('/next_page')

mysql封装 -- 很好用

复制代码 代码如下:

import umysql
from functools import wraps
 
class Configuraion:
    def __init__(self, env):
        if env == "Prod":
            self.host    = "coolshell.cn"
            self.port    = 3306
            self.db      = "coolshell"
            self.user    = "coolshell"
            self.passwd  = "fuckgfw"
        elif env == "Test":
            self.host   = 'localhost'
            self.port   = 3300
            self.user   = 'coolshell'
            self.db     = 'coolshell'
            self.passwd = 'fuckgfw'
 
def mysql(sql):
 
    _conf = Configuraion(env="Prod")
 
    def on_sql_error(err):
        print err
        sys.exit(-1)
 
    def handle_sql_result(rs):
        if rs.rows > 0:
            fieldnames = [f[0] for f in rs.fields]
            return [dict(zip(fieldnames, r)) for r in rs.rows]
        else:
            return []
 
    def decorator(fn):
        @wraps(fn)
        def wrapper(*args, **kwargs):
            mysqlconn = umysql.Connection()
            mysqlconn.settimeout(5)
            mysqlconn.connect(_conf.host, _conf.port, _conf.user, \
                              _conf.passwd, _conf.db, True, 'utf8')
            try:
                rs = mysqlconn.query(sql, {})     
            except umysql.Error as e:
                on_sql_error(e)
 
            data = handle_sql_result(rs)
            kwargs["data"] = data
            result = fn(*args, **kwargs)
            mysqlconn.close()
            return result
        return wrapper
 
    return decorator
 
 
@mysql(sql = "select * from coolshell" )
def get_coolshell(data):
    ... ...
    ... ..

线程异步

复制代码 代码如下:

from threading import Thread
from functools import wraps
 
def async(func):
    @wraps(func)
    def async_func(*args, **kwargs):
        func_hl = Thread(target = func, args = args, kwargs = kwargs)
        func_hl.start()
        return func_hl
 
    return async_func
 
if __name__ == '__main__':
    from time import sleep
 
    @async
    def print_somedata():
        print 'starting print_somedata'
        sleep(2)
        print 'print_somedata: 2 sec passed'
        sleep(2)
        print 'print_somedata: 2 sec passed'
        sleep(2)
        print 'finished print_somedata'
 
    def main():
        print_somedata()
        print 'back in main'
        print_somedata()
        print 'back in main'
 
    main()
Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

Java Tutorial
1664
14
PHP Tutorial
1266
29
C# Tutorial
1239
24
PHP and Python: Different Paradigms Explained PHP and Python: Different Paradigms Explained Apr 18, 2025 am 12:26 AM

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

Choosing Between PHP and Python: A Guide Choosing Between PHP and Python: A Guide Apr 18, 2025 am 12:24 AM

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

PHP and Python: A Deep Dive into Their History PHP and Python: A Deep Dive into Their History Apr 18, 2025 am 12:25 AM

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

Python vs. JavaScript: The Learning Curve and Ease of Use Python vs. JavaScript: The Learning Curve and Ease of Use Apr 16, 2025 am 12:12 AM

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

How to run sublime code python How to run sublime code python Apr 16, 2025 am 08:48 AM

To run Python code in Sublime Text, you need to install the Python plug-in first, then create a .py file and write the code, and finally press Ctrl B to run the code, and the output will be displayed in the console.

Where to write code in vscode Where to write code in vscode Apr 15, 2025 pm 09:54 PM

Writing code in Visual Studio Code (VSCode) is simple and easy to use. Just install VSCode, create a project, select a language, create a file, write code, save and run it. The advantages of VSCode include cross-platform, free and open source, powerful features, rich extensions, and lightweight and fast.

Golang vs. Python: Performance and Scalability Golang vs. Python: Performance and Scalability Apr 19, 2025 am 12:18 AM

Golang is better than Python in terms of performance and scalability. 1) Golang's compilation-type characteristics and efficient concurrency model make it perform well in high concurrency scenarios. 2) Python, as an interpreted language, executes slowly, but can optimize performance through tools such as Cython.

How to run python with notepad How to run python with notepad Apr 16, 2025 pm 07:33 PM

Running Python code in Notepad requires the Python executable and NppExec plug-in to be installed. After installing Python and adding PATH to it, configure the command "python" and the parameter "{CURRENT_DIRECTORY}{FILE_NAME}" in the NppExec plug-in to run Python code in Notepad through the shortcut key "F6".

See all articles