面向优雅的 Python 编程

很早就想整理一篇关于如何让 Python 代码风格更加优雅的博客，以供查阅。Python 的设计理念是 “优雅”、“简单” 和 “明确”， 引用一下 Python 之禅：

The Zen of Python, by Tim Peters

Beautiful is better than ugly.

Explicit is better than implicit.

Simple is better than complex.

Complex is better than complicated.

Flat is better than nested.

Sparse is better than dense.

Readability counts.

Special cases aren’t special enough to break the rules.

Although practicality beats purity.

Errors should never pass silently.

Unless explicitly silenced.

In the face of ambiguity, refuse the temptation to guess.

There should be one-- and preferably only one --obvious way to do it.

Although that way may not be obvious at first unless you’re Dutch.

Now is better than never.

Although never is often better than right now.

If the implementation is hard to explain, it’s a bad idea.

If the implementation is easy to explain, it may be a good idea.

Namespaces are one honking great idea – let’s do more of those!

编程规范

Python 编程风格指引
PEP 8: https://peps.python.org/pep-0008/

中文版： https://github.com/kernellmd/Knowledge/blob/master/Translation/PEP%208%20%E4%B8%AD%E6%96%87%E7%BF%BB%E8%AF%91.md

一些实践

1. 使用 with 关键字

在对文件等需要及时清理的对象进行操作时，使用 with 进行管理，能够在操作完成之后及时对对象进行关闭或清理，简化操作，例如：

with open('test.txt', 'w') as f:
  f.write('hello world!\n')

2. 使用 zip 关键字

zip 让我们能够同时取出多个可迭代对象中对应的元素，返回由这些元素组成的元组，例如：

x = [1, 2, 3]
y = ['a', 'b', 'c']
z = ['x', 'y', 'z']
for one_x, one_y, one_z in zip(x, y, z):
    print(one_x, one_y, one_z)

另外 zip 对于 numpy.array 和 list 对象的混合情况同样适用。

输出：

1 a x

2 b y

3 c z

3. 使用列表推导式

在代码中恰当地引入列表推导式可以大大简化和缩短代码，例如：

x = [[i, j] for i in range(10) for j in range(10)]
y = [[one_x[0]+10, one_x[1]-10] for one_x in x]

4. 使用 lambda 表达式

使用 lambda 可以简化函数定义，缩短代码，例如：

fun = lambda a, b: '{} + {} = {}'.format(a, b, a+b)
fun(1, 2)

5. 使用 map 和 filter 函数

map 函数会根据传入的函数对指定可迭代对象（list, turple…）中的元素逐个进行操作，例如：

fun = lambda a, b: '{} + {} = {}'.format(a, b, a+b)
x = [i for i in range(5)]
y = [i+2 for i in x]
for i in map(fun, x, y):
    print(i)

输出：

0 + 2 = 2

1 + 3 = 4

2 + 4 = 6

3 + 5 = 8

4 + 6 = 10

filter 和 map 功能类似，不同的是 filter 是对符合符合要求的元素进行过滤操作，例如：

fun = lambda x: x>0
x = [i for i in range(-3, 3)]
for i in filter(fun, x):
    print(i)

输出：

1

2

6. 错误处理

错误处理在 Python 编程中也非常重要，主要用到的是 try、except、finally 和 raise 关键字，Python 中提供了非常多的标准异常：

C 名称	Python 名称	备注
PyExc_BaseException	BaseException	[1]
PyExc_Exception	Exception	[1]
PyExc_ArithmeticError	ArithmeticError	[1]
PyExc_AssertionError	AssertionError
PyExc_AttributeError	AttributeError
PyExc_BlockingIOError	BlockingIOError
PyExc_BrokenPipeError	BrokenPipeError
PyExc_BufferError	BufferError
PyExc_ChildProcessError	ChildProcessError
PyExc_ConnectionAbortedError	ConnectionAbortedError
PyExc_ConnectionError	ConnectionError
PyExc_ConnectionRefusedError	ConnectionRefusedError
PyExc_ConnectionResetError	ConnectionResetError
PyExc_EOFError	EOFError
PyExc_FileExistsError	FileExistsError
PyExc_FileNotFoundError	FileNotFoundError
PyExc_FloatingPointError	FloatingPointError
PyExc_GeneratorExit	GeneratorExit
PyExc_ImportError	ImportError
PyExc_IndentationError	IndentationError
PyExc_IndexError	IndexError
PyExc_InterruptedError	InterruptedError
PyExc_IsADirectoryError	IsADirectoryError
PyExc_KeyError	KeyError
PyExc_KeyboardInterrupt	KeyboardInterrupt
PyExc_LookupError	LookupError	[1]
PyExc_MemoryError	MemoryError
PyExc_ModuleNotFoundError	ModuleNotFoundError
PyExc_NameError	NameError
PyExc_NotADirectoryError	NotADirectoryError
PyExc_NotImplementedError	NotImplementedError
PyExc_OSError	OSError	[1]
PyExc_OverflowError	OverflowError
PyExc_PermissionError	PermissionError
PyExc_ProcessLookupError	ProcessLookupError
PyExc_RecursionError	RecursionError
PyExc_ReferenceError	ReferenceError
PyExc_RuntimeError	RuntimeError
PyExc_StopAsyncIteration	StopAsyncIteration
PyExc_StopIteration	StopIteration
PyExc_SyntaxError	SyntaxError
PyExc_SystemError	SystemError
PyExc_SystemExit	SystemExit
PyExc_TabError	TabError
PyExc_TimeoutError	TimeoutError
PyExc_TypeError	TypeError
PyExc_UnboundLocalError	UnboundLocalError
PyExc_UnicodeDecodeError	UnicodeDecodeError
PyExc_UnicodeEncodeError	UnicodeEncodeError
PyExc_UnicodeError	UnicodeError
PyExc_UnicodeTranslateError	UnicodeTranslateError
PyExc_ValueError	ValueError
PyExc_ZeroDivisionError	ZeroDivisionError

以上内容引用自官方文档。

例如：

def x_greater_than_100(x):
  if x > 100:
    return x
  else:
    raise ValueError('x is not greater than 100: {}'.format(x))
x_greater_than_100(50)

输出：

ValueError: x is not greater than 100: 50

这里我们可以通过 try 来对错误进行处理，例如：

x = 3
while(x<100):
  try:
    x = x_greater_than_100(x)
  except ValueError:
    x = x + 10
print(x)

输出：

103

7. 构造函数时灵活使用可变参数和字典参数

在构造函数时，Python 提供了非常灵活的参数传入机制，其中包括可变参数和字典参数，恰当使用可以大大增加代码的灵活性，例如,

对于可变参数：

def enumerate_args(*args):
    for i, arg in enumerate(args):
        print('#{}: '.format(i), arg)
enumerate_args(*[1, 2, 3])           ### 传入可迭代对象
enumerate_args(1, 2, 3)         ### 传入多个参数

对于字典参数：

def enumerate_kwargs(**kwargs):
    for key, item in kwargs.items():
        print('{}: {}'.format(key, item))
enumerate_kwargs(**{'dog': 1, 'cat': 2, 'fish': 3})         ### 传入可迭代对象
enumerate_kwargs(dog=1, cat=2, fish=3)          ### 传入多个参数