python入门

Posted 2020-10-20 Merrys

Slice(切片)

>>> L = [‘Michael‘, ‘Sarah‘, ‘Tracy‘, ‘Bob‘, ‘Jack‘]
>>> L[0:3]
[‘Michael‘, ‘Sarah‘, ‘Tracy‘]
>>> L[:3]
[‘Michael‘, ‘Sarah‘, ‘Tracy‘]
>>> L[1:3]
[‘Sarah‘, ‘Tracy‘]


>>> L[-2:]
[‘Bob‘, ‘Jack‘]
>>> L[-2:-1]
[‘Bob‘]

>>> L = list(range(100))
>>> L
[0, 1, 2, 3, ..., 99]
>>> L[:]
[0, 1, 2, 3, ..., 99]
>>> L[:10:2]
[0, 2, 4, 6, 8]
>>> L[::5]
[0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95]

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>>> (0, 1, 2, 3, 4, 5)[:3]
(0, 1, 2)

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>>> ‘ABCDEFG‘[:3]
‘ABC‘
>>> ‘ABCDEFG‘[::2]
‘ACEG‘

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For ... in ...(迭代)

默认情况下，dict迭代的是key。如果要迭代value，可以用for value in d.values()，如果要同时迭代key和value，可以用for k, v in d.items()。

>>> d = {‘a‘: 1, ‘b‘: 2, ‘c‘: 3}
>>> for key in d:
...     print(key)
...
a
c
b

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>>> for ch in ‘ABC‘:
...     print(ch)
...
A
B
C

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 判断可迭代对象

>>> from collections import Iterable
>>> isinstance(‘abc‘, Iterable) # str是否可迭代
True
>>> isinstance([1,2,3], Iterable) # list是否可迭代
True
>>> isinstance(123, Iterable) # 整数是否可迭代
False

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>>> for i, value in enumerate([‘A‘, ‘B‘, ‘C‘]):
...     print(i, value)
...
0 A
1 B
2 C

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>>> for x, y in [(1, 1), (2, 4), (3, 9)]:
...     print(x, y)
...
1 1
2 4
3 9

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列表生成式

>>> list(range(1, 11))
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

>>> [x * x for x in range(1, 11)]
[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

>>> [x * x for x in range(1, 11) if x % 2 == 0]
[4, 16, 36, 64, 100]

>>> [m + n for m in ‘ABC‘ for n in ‘XYZ‘]
[‘AX‘, ‘AY‘, ‘AZ‘, ‘BX‘, ‘BY‘, ‘BZ‘, ‘CX‘, ‘CY‘, ‘CZ‘]

>>> d = {‘x‘: ‘A‘, ‘y‘: ‘B‘, ‘z‘: ‘C‘ }
>>> [k + ‘=‘ + v for k, v in d.items()]
[‘y=B‘, ‘x=A‘, ‘z=C‘]

>>> L = [‘Hello‘, ‘World‘, ‘IBM‘, ‘Apple‘]
>>> [s.lower() for s in L]
[‘hello‘, ‘world‘, ‘ibm‘, ‘apple‘]

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 生成器

>>> g = (x * x for x in range(10))
>>> g
<generator object <genexpr> at 0x1022ef630>

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>>> next(g)
0
>>> next(g)
1
>>> next(g)
4
>>> next(g)
9
>>> next(g)
16
>>> next(g)
25
>>> next(g)
36
>>> next(g)
49
>>> next(g)
64
>>> next(g)
81
>>> next(g)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration

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generator保存的是算法，每次调用next(g)，就计算出g的下一个元素的值，直到计算到最后一个元素，没有更多的元素时，抛出StopIteration的错误。

>>> g = (x * x for x in range(10))
>>> for n in g:
...     print(n)
... 
0
1
4
9
16
25
36
49
64
81

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如果一个函数定义中包含yield关键字，那么这个函数就不再是一个普通函数，而是一个generator。generator的函数，在每次调用next()的时候执行，遇到yield语句返回，再次执行时从上次返回的yield语句处继续执行。

def odd():
    print(‘step 1‘)
    yield 1
    print(‘step 2‘)
    yield(3)
    print(‘step 3‘)
    yield(5)


>>> o = odd()
>>> next(o)
step 1
1
>>> next(o)
step 2
3
>>> next(o)
step 3
5
>>> next(o)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration

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 map

>>> def f(x):
...     return x * x
...
>>> r = map(f, [1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> list(r)
[1, 4, 9, 16, 25, 36, 49, 64, 81]

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reduce

>>> from functools import reduce
>>> def add(x, y):
...     return x + y
...
>>> reduce(add, [1, 3, 5, 7, 9])
25

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>>> from functools import reduce
>>> def fn(x, y):
...     return x * 10 + y
...
>>> reduce(fn, [1, 3, 5, 7, 9])
13579

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filter

def is_odd(n):
    return n % 2 == 1

list(filter(is_odd, [1, 2, 4, 5, 6, 9, 10, 15]))
# 结果: [1, 5, 9, 15]

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def not_empty(s):
    return s and s.strip()

list(filter(not_empty, [‘A‘, ‘‘, ‘B‘, None, ‘C‘, ‘  ‘]))
# 结果: [‘A‘, ‘B‘, ‘C‘]

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sorted

>>> sorted([36, 5, -12, 9, -21])
[-21, -12, 5, 9, 36]

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>>> sorted([36, 5, -12, 9, -21], key=abs)
[5, 9, -12, -21, 36]

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>>> sorted([‘bob‘, ‘about‘, ‘Zoo‘, ‘Credit‘])
[‘Credit‘, ‘Zoo‘, ‘about‘, ‘bob‘]

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>>> sorted([‘bob‘, ‘about‘, ‘Zoo‘, ‘Credit‘], key=str.lower)
[‘about‘, ‘bob‘, ‘Credit‘, ‘Zoo‘]

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L = [(‘Bob‘, 75), (‘Adam‘, 92), (‘Bart‘, 66), (‘Lisa‘, 88)]
list(sorted(L,key=lambda x :x[1]))

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 闭包

def count():
    fs = []
    for i in range(1, 4):
        def f():
             return i*i
        fs.append(f)
    return fs

f1, f2, f3 = count()

>>> f1()
9
>>> f2()
9
>>> f3()
9

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def count():
    def f(j):
        def g():
            return j*j
        return g
    fs = []
    for i in range(1, 4):
        fs.append(f(i)) # f(i)立刻被执行，因此i的当前值被传入f()
    return fs


>>> f1, f2, f3 = count()
>>> f1()
1
>>> f2()
4
>>> f3()
9

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匿名函数 lambda

只能有一个表达式，不用写return，返回值就是该表达式的结果。

>>> f = lambda x: x * x
>>> f
<function <lambda> at 0x101c6ef28>
>>> f(5)
25


def build(x, y):
    return lambda: x * x + y * y

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装饰器

代码运行期间动态增加功能的方式，称之为“装饰器”（Decorator）。

偏函数

>>> import functools
>>> int2 = functools.partial(int, base=2)
>>> int2(‘1000000‘)
64
>>> int2(‘1010101‘)
85


>>> int2(‘1000000‘, base=10)
1000000

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no yuchuang.just shuxishuxi.