1、dispach

Python 天然支持多態，但使用 dispatch 可以讓你的代碼更加容易閱讀。

安裝：

pipinstallmultipledispatch

使用：

>>> from multipledispatch import dispatch

>>> @dispatch(int, int)
... def add(x, y):
...     return x + y

>>> @dispatch(object, object)
... def add(x, y):
...     return "%s + %s" % (x, y)

>>> add(1, 2)
3

>>> add(1, 'hello')
'1 + hello'

2、click

click 可以很方便地讓你實現命令行工具。

安裝：

pipinstallclick

使用：demo2.py :

import click

@click.command()
@click.option('--count', default=1, help='Number of greetings.')
@click.option('--name', prompt='Your name',
              help='The person to greet.')
def hello(count, name):
    """Simple program that greets NAME for a total of COUNT times."""
    for x in range(count):
        click.echo(f"Hello {name}!")

if __name__ == '__main__':
    hello()

運行結果：

? python demo2.py --count=3 --name=joih
Hello joih!
Hello joih!
Hello joih!
? python demo2.py --count=3
Your name: somenzz
Hello somenzz!
Hello somenzz!
Hello somenzz!

3、celery

分布式的任務隊列，非 Celery 莫屬。

from celery import Celery

app = Celery('tasks', broker='pyamqp://guest@localhost//')

@app.task
def add(x, y):
    return x + y

4、deprecated

這個相信大家在使用別的包時都遇到過，當要下線一個老版本的函數的時候就可以使用這個裝飾器。

安裝：

pipinstallDeprecated

使用：demo4.py

from deprecated import deprecated
@deprecated ("This function is deprecated, please do not use it")
def func1():
    pass

func1()

運行效果如下：

? python demo4.py
demo4.py:6: DeprecationWarning: Call to deprecated function (or staticmethod) func1. (This function is deprecated, please do not use it)
  func1()

5、deco.concurrent

安裝：

pipinstalldeco

使用 DECO 就像在 Python 程序中查找或創建兩個函數一樣簡單。我們可以用 @concurrent 裝飾需要并行運行的函數，用 @synchronized 裝飾調用并行函數的函數，使用舉例：

from deco import concurrent, synchronized 
@concurrent # We add this for the concurrent function
def process_url(url, data):
  #Does some work which takes a while
  return result

@synchronized # And we add this for the function which calls the concurrent function
def process_data_set(data):
  results = {}
  for url in urls:
    results[url] = process_url(url, data)
  return results

6、cachetools

緩存工具

安裝：

pipinstallcachetools

使用：

from cachetools import cached, LRUCache, TTLCache

# speed up calculating Fibonacci numbers with dynamic programming
@cached(cache={})
def fib(n):
    return n if n < 2 else fib(n - 1) + fib(n - 2)

# cache least recently used Python Enhancement Proposals
@cached(cache=LRUCache(maxsize=32))
def get_pep(num):
    url = 'http://www.python.org/dev/peps/pep-%04d/' % num
    with urllib.request.urlopen(url) as s:
        return s.read()

# cache weather data for no longer than ten minutes
@cached(cache=TTLCache(maxsize=1024, ttl=600))
def get_weather(place):
    return owm.weather_at_place(place).get_weather()

7、retry

重試裝飾器，支持各種各樣的重試需求。

安裝：

pipinstalltenacity

使用：

import random
from tenacity import retry

@retry
def do_something_unreliable():
    if random.randint(0, 10) > 1:
        raise IOError("Broken sauce, everything is hosed!!!111one")
    else:
        return "Awesome sauce!"

@retry(stop=stop_after_attempt(7))
def stop_after_7_attempts():
    print("Stopping after 7 attempts")
    raise Exception


@retry(stop=stop_after_delay(10))
def stop_after_10_s():
    print("Stopping after 10 seconds")
    raise Exception

@retry(stop=(stop_after_delay(10) | stop_after_attempt(5)))
def stop_after_10_s_or_5_retries():
    print("Stopping after 10 seconds or 5 retries")
    raise Exception

審核編輯：符乾江