Python 开发中高级技巧

列表推导式

>>> chars = [ c for c in 'python' ]

>>> chars

['p', 'y', 't', 'h', 'o', 'n']

字典推导式

>>> dict1 = {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}

>>> double_dict1 = {k:v*2 for (k,v) in dict1.items()}

>>> double_dict1

{'a': 2, 'b': 4, 'c': 6, 'd': 8, 'e': 10}

集合推导式

>>> set1 = {1,2,3,4}

>>> double_set = {i*2 for i in set1}

>>> double_set

{8, 2, 4, 6}

合并字典

>>> x = {'a':1,'b':2}

>>> y = {'c':3, 'd':4}

>>> z = {**x, **y}

>>> z

{'a': 1, 'b': 2, 'c': 3, 'd': 4}

复制列表

>>> nums = [1,2,3]

>>> nums[::]

[1, 2, 3]

>>> copy_nums = nums[::]

>>> copy_nums

[1, 2, 3]

反转列表

>>> reverse_nums = nums[::-1]

>>> reverse_nums

[3, 2, 1]

变量交换

>>> a,b = 1, 2

>>> a ,b = b,a

>>> a

2

>>> b

1

高级拆包

>>> a, *b = 1,2,3

>>> a

1

>>> b

[2, 3]

或者

>>> a, *b, c = 1,2,3,4,5

>>> a

1

>>> b

[2, 3, 4]

>>> c

5

函数返回多个值（其实是自动packing成元组）然后unpacking赋值给4个变量

>>> def f():

...     return 1, 2, 3, 4

...

>>> a, b, c, d = f()

>>> a

1

>>> d

4

列表合并成字符串

>>> " ".join(["I", "Love", "Python"])

'I Love Python'

链式比较

>>> if a > 2 and a < 5:

...     pass

...

>>> if 2<a<5:

...     pass

yield from

# 没有使用 field from

def dup(n):

    for i in range(n):

        yield i

        yield i

# 使用yield from

def dup(n):

    for i in range(n):

    yield from [i, i]

for i in dup(3):

    print(i)

>>>

0

0

1

1

2

2

in 代替 or

>>> if x == 1 or x == 2 or x == 3:

...     pass

...

>>> if x in (1,2,3):

...     pass

字典代替多个if else

def fun(x):

    if x == 'a':

        return 1

    elif x == 'b':

        return 2

    else:

        return None

def fun(x):

    return {"a": 1, "b": 2}.get(x)

有下标索引的枚举

>>> for i, e in enumerate(["a","b","c"]):

...     print(i, e)

...

0 a

1 b

2 c

生成器

注意区分列表推导式，生成器效率更高

>>> g = (i**2 for i in range(5))

>>> g

<generator object <genexpr> at 0x10881e518>

>>> for i in g:

...     print(i)

...

0

1

4

9

16

默认字典 defaultdict

>>> d = dict()

>>> d['nums']

KeyError: 'nums'

>>>

>>> from collections import defaultdict

>>> d = defaultdict(list)

>>> d["nums"]

[]

字符串格式化

>>> lang = 'python'

>>> f'{lang} is most popular language in the world'

'python is most popular language in the world'

列表中出现次数最多的元素

>>> nums = [1,2,3,3]

>>> max(set(nums), key=nums.count)

3

或者

from collections import Counter

>>> Counter(nums).most_common()[0][0]

3

读写文件

>>> with open("test.txt", "w") as f:

...     f.writelines("hello")

判断对象类型，可指定多个类型

>>> isinstance(a, (int, str))

True

类似的还有字符串的 startswith，endswith

>>> "http://foofish.net".startswith(('http','https'))

True

>>> "https://foofish.net".startswith(('http','https'))

True

__str__ 与 __repr__ 区别

>>> str(datetime.now())

'2018-11-20 00:31:54.839605'

>>> repr(datetime.now())

'datetime.datetime(2018, 11, 20, 0, 32, 0, 579521)'

前者对人友好，可读性更强，后者对计算机友好，支持 obj == eval(repr(obj))

使用装饰器

def makebold(f):

return lambda: "<b>" + f() + "</b>"

def makeitalic(f):

return lambda: "<i>" + f() + "</i>"

@makebold

@makeitalic

def say():

return "Hello"

>>> say()

<b><i>Hello</i></b>

不使用装饰器，可读性非常差

def say():

return "Hello"

>>> makebold(makeitalic(say))()

<b><i>Hello</i></b>