Python weekly -- Things you’re probably not using in Python 3 – but should
作者:互联网
1. f-strings (3.6+)
相对format方法更加灵活的 f-strings
user = 'hello'
age = 008
say_something = f'user {user} has been lived {age} years'
print(say_something)
2. Pathlib (3.4+)
对文件路径更方便的抽象
# C:\lizude\temp\github\math\math_project\math_project\async_decorator.py
from pathlib import Path
root = Path('math_project')
path = root / 'async_decorator' # 绝对路径
print(path.resolve())
输出:C:\lizude\temp\github\math\math_project\math_project\async_decorator
3. Type hinting (3.5+)
类型指定,包括参数和函数return 结果
def sentence_has_animal(sentence: str) -> bool:
return 'animal' in sentence
sentence_has_animal('donald had a farm without animals')
4. Enumerations (3.4+)
通过 Enum 类可以更方便的写枚举
from enum import Enum, auto
class Monster(Enum):
ZOMBIE = auto()
WARRIOR = auto()
BEAR = auto()
print(Monster.ZOMBIE)
# Monster.ZOMBIE
for monster in Monster:
print(monster)
# Monster.ZOMBIE
# Monster.WARRIOR
# Monster.BEAR
5. Built-in LRU cache (3.2+)
缓存目前几乎是软件和硬件的水平切片
Python 3 makes using them very simple by exposing an LRU (Least Recently Used) cache as a decorator called lru_cache.
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
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
6. Extended iterable unpacking (3.0+)
解包的扩展
head, *body, tail = range(5)
print(head, body, tail)
# 0, [1,2,3], 4
py, filename, *cmds = "python3.7 script.py -n 5 -l 15".split()
print(py)
print(filename)
print(cmds)
# python3.7
# script.py
# ['-n', '5', '-l', '15']
first, _, third, *_ = range(8)
print(first, third)
# 0, 2
7. Data classes (3.7+)
数据类 , 官方描述为可改变的有默认值的命名元组
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>
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(6, 'common armor.', 2)
armor.power()
# 12
print(armor)
# Armor(armor=6, description='common armor.', level=2)
8. Implicit namespace packages (3.3+)
盲目的包的命名空间
定义一个包的方法是 init.py文件
在现在不用每个子文件夹都要 init.py文件
# 每个都有__init__.py
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
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
...
原文:https://datawhatnow.com/things-you-are-probably-not-using-in-python-3-but-should/
标签:return,Python,Things,self,py,number,but,armor,print 来源: https://www.cnblogs.com/bruspawn/p/10882607.html