你应该使用Python3里的这些新特性

发布时间:2019-10-18 09:07:03编辑:auto阅读(533)

    概述

    由于Python2的官方维护期即将结束,越来越多的Python项目从Python2切换到了Python3。可是,在实际的工作中,我发现好多人都是在用Python2的思维去写Python3的代码,Python3给我们提供了很多新的、很方便的特性,可以帮助我们快速的编写代码。

    f-strings (3.6+)

    在Python里面,我们经常使用format函数来格式化字符串,例如:

    user = "Jane Doe"
    action = "buy"
    
    log_message = 'User {} has logged in and did an action {}.'.format(
      user,
      action
    )
    
    print(log_message)
    输出:User Jane Doe has logged in and did an action buy.

    Python3里面提供了一个更加灵活方便的方法来格式化字符串,叫做f-strings。上面的代码可以这样实现:

    user = "Jane Doe"
    action = "buy"
    
    log_message = f'User {user} has logged in and did an action {action}.'
    print(log_message)
    输出: User Jane Doe has logged in and did an action buy.

    Pathlib (3.4+)

    f-strings这个功能太方便了,但是对于文件路劲这样的字符串,Python还提供了更加方便的处理方法。Pathlib是Python3提供的一个处理文件路劲的库。例如:

    from pathlib import Path
    
    root = Path('post_sub_folder')
    print(root)
    输出结果: post_sub_folder
    
    path = root / 'happy_user'
    
    # 输出绝对路劲
    print(path.resolve())
    输出结果:/root/post_sub_folder/happy_user

    Type hinting (3.5+)

    静态与动态类型是软件工程中的一个热门话题,每个人都有不同的看法,Python作为一个动态类型语言,在Python3中也提供了Type hinting功能,例如:

    def sentence_has_animal(sentence: str) -> bool:
      return "animal" in sentence
    
    sentence_has_animal("Donald had a farm without animals")
    # True

    Enumerations (3.4+)

    Python3提供的Enum类让你很容就能实现一个枚举类型:

    from enum import Enum, auto
    
    class Monster(Enum):
        ZOMBIE = auto()
        WARRIOR = auto()
        BEAR = auto()
        
    print(Monster.ZOMBIE)
    输出: Monster.ZOMBIE

    Python3的Enum还支持比较和迭代。

    for monster in Monster:
        print(monster)
    
    输出: Monster.ZOMBIE
         Monster.WARRIOR
         Monster.BEAR

    Built-in LRU cache (3.2+)

    缓存是现在的软件领域经常使用的技术,Python3提供了一个lru_cache装饰器,来让你更好的使用缓存。下面有个实例:

    import time
    
    def fib(number: int) -> int:
        if number == 0: return 0
        if number == 1: return 1
        
        return fib(number-1) + fib(number-2)
    
    start = time.time()
    fib(40)
    print(f'Duration: {time.time() - start}s')
    # Duration: 30.684099674224854s

    现在我们可以使用lru_cache来优化我们上面的代码,降低代码执行时间。

    from functools import lru_cache
    
    @lru_cache(maxsize=512)
    def fib_memoization(number: int) -> int:
        if number == 0: return 0
        if number == 1: return 1
        
        return fib_memoization(number-1) + fib_memoization(number-2)
    
    start = time.time()
    fib_memoization(40)
    print(f'Duration: {time.time() - start}s')
    # Duration: 6.866455078125e-05s

    Extended iterable unpacking (3.0+)

    废话不多说,直接上代码,文档在这

    head, *body, tail = range(5)
    print(head, body, tail)
    输出: 0 [1, 2, 3] 4
    
    py, filename, *cmds = "python3.7 script.py -n 5 -l 15".split()
    print(py)
    print(filename)
    print(cmds)
    输出:python3.7
         script.py
         ['-n', '5', '-l', '15']
    
    first, _, third, *_ = range(10)
    print(first, third)
    输出: 0 2

    Data classes (3.7+)

    Python3提供data class装饰器来让我们更好的处理数据对象,而不用去实现 init__() 和 __repr() 方法。假设如下的代码:

    class Armor:
        
        def __init__(self, armor: float, description: str, level: int = 1):
            self.armor = armor
            self.level = level
            self.description = description
                     
        def power(self) -> float:
            return self.armor * self.level
        
    armor = Armor(5.2, "Common armor.", 2)
    armor.power()
    # 10.4
    
    print(armor)
    # <__main__.Armor object at 0x7fc4800e2cf8>

    使用data class实现上面功能的代码,这么写:

    from dataclasses import dataclass
    
    @dataclass
    class Armor:
        armor: float
        description: str
        level: int = 1
        
    
        def power(self) -> float:
            return self.armor * self.level
        
    armor = Armor(5.2, "Common armor.", 2)
    armor.power()
    # 10.4
    
    print(armor)
    # Armor(armor=5.2, description='Common armor.', level=2)

    Implicit namespace packages (3.3+)

    通常情况下,Python通过把代码打成包(在目录中加入__init__.py实现)来复用,官方给的示例如下:

    sound/                          Top-level package
          __init__.py               Initialize the sound package
          formats/                  Subpackage for file format conversions
                  __init__.py
                  wavread.py
                  wavwrite.py
                  aiffread.py
                  aiffwrite.py
                  auread.py
                  auwrite.py
                  ...
          effects/                  Subpackage for sound effects
                  __init__.py
                  echo.py
                  surround.py
                  reverse.py
                  ...
          filters/                  Subpackage for filters
                  __init__.py
                  equalizer.py
                  vocoder.py
                  karaoke.py

    在Python2里,如上的目录结构,每个目录都必须有__init__.py文件,一遍其他模块调用目录下的python代码,在Python3里,通过 Implicit Namespace Packages可是不使用__init__.py文件

    sound/                          Top-level package
          __init__.py               Initialize the sound package
          formats/                  Subpackage for file format conversions
                  wavread.py
                  wavwrite.py
                  aiffread.py
                  aiffwrite.py
                  auread.py
                  auwrite.py
                  ...
          effects/                  Subpackage for sound effects
                  echo.py
                  surround.py
                  reverse.py
                  ...
          filters/                  Subpackage for filters
                  equalizer.py
                  vocoder.py
                  karaoke.py

    结语

    这篇文章只列出了一下部分Python3的新功能,我希望这篇文章向您展示了部分您以前不知道的Python 3新功能,并且希望能帮助您编写更清晰,更直观的代码。

关键字