• 迭代器和解析


    可迭代对象包括实际序列和按照需求计算的虚拟序列

    手动迭代:iter和next

    python3.0提供了一个内置函数next,它会自动调用一个对象的__next__方法,给定一个

    可迭代对象x。调用next(x)等同于x,next()

    列表以及其他对象不是自身的迭代器,他们可以调用iter来启动迭代

    l = [1, 2, 3]
    print(iter(l) is l)

    False

    print(l.next())

    AttributeError: 'list' object has no attribute 'next'

    l = [1, 2, 3]
    i = iter(l)
    print(next(i))

    1

    print(i.next())

    2

    l = [1, 2, 3]
    for x in l:
    print(x**2, end=' ')

    1 4 9

    l = [1, 2, 3]
    i = iter(l)
    while True:
    try:
    j = next(i)
    except StopIteration:
    break
    else:
    print(j ** 2, end=' ')

    1 4 9

    python2 中迭代方法是x.next, python3是x.next,但next函数确是都可用的。

    其他迭代器

    d = {'a':1, 'b':2, 'c':3}
    for k in d.keys():
    print(k, d[k])

    a 1

    b 2

    c 3

    python3中,字典自己有个迭代器

    i = iter(d)
    print(next(i))
    print(next(i))
    print(next(i))

    a

    b

    c

    因此我们不需要调用keys方法来遍历字典,for将使用迭代协议获取键。

    for k in d:
    print(k, d[k])

    a 1

    b 2

    c 3

    shelves和os.popen的结果也是可迭代的

    import os
    p = os.popen('dir')
    print(p.next())

    驱动器 F 中的卷没有标签。

    注意py2中popen对象支持p.next方法,py3中支持p.next()方法。

    迭代协议也是需要将结果包装到一个list中才能看到值。可迭代对象一次返回一

    个结果,而不是一个列表

    a = range(5)
    print(a)

    range(0, 5)

    i = iter(a)
    print(next(i))
    print(next(i))

    0

    1

    print(list(range(5)))

    [0, 1, 2, 3, 4]

    列表解析

    l = []
    for i in [1, 2, 3]:
    l.append(i+1)
    print(l)

    [2, 3, 4]

    相比普通的循环,列表解析也可以达到相同的目的,并且更加简洁,运行速度也比

    普通的循环快

    print([i+1 for i in [1, 2, 3]])

    [2, 3, 4]

    文件中的列表解析

    with open('some.py', 'w') as f:
    f.write('import os ')
    f.write('a = 1 ')
    f.write('b = 2 ')
    with open('some.py') as f:
    print(f.read())

    import os

    a = 1

    b = 2

    f = open('some.py')
    line = f.readlines()
    print(line)

    ['import os ', 'a = 1 ', 'b = 2 ']

    如果要去掉行末的换行符的话。

    print([l.rstrip() for l in line])

    ['import os', 'a = 1', 'b = 2']

    因为列表解析像for循环语句是一个迭代环境, 我们甚至不用提前打开文件。

    l = [line.rstrip() for line in open('some.py')]
    print(l)

    ['import os', 'a = 1', 'b = 2']

    除此之外。列表解析的表现力也很强,我们可以在迭代时在一个文件上运行任何的

    字符串操作

    print([line.upper() for line in open('some.py')])

    ['IMPORT OS ', 'A = 1 ', 'B = 2 ']

    列表解析也可以嵌套for循环和if

    lines = [line.rstrip() for line in open('some.py') if line[0] == 'a']
    print(lines)

    ['a = 1']

    print([x+y for x in 'abc' for y in 'lmn'])

    ['al', 'am', 'an', 'bl', 'bm', 'bn', 'cl', 'cm', 'cn']

    列表解析,in成员测试,map内置函数,sorted和zip都使用了迭代协议

    当应用文件时,会自动扫描

    upper = [line.upper() for line in open('some.py')]
    print(upper)

    ['IMPORT OS ', 'A = 1 ', 'B = 2 ']

    print(list(map(str.upper, open('some.py'))))

    ['IMPORT OS ', 'A = 1 ', 'B = 2 ']

    print('a = 1 ' in open('some.py'))

    True

    print(sorted(open('some.py')))

    ['a = 1 ', 'b = 2 ', 'import os ']

    print(list(zip(open('some.py'), open('some.py'))))

    [('import os ', 'import os '), ('a = 1 ', 'a = 1 '), ('b = 2 ', 'b = 2 ')]

    print(list(enumerate(open('some.py'))))

    [(0, 'import os '), (1, 'a = 1 '), (2, 'b = 2 ')]

    print(list(filter(bool, open('some.py'))))

    ['import os ', 'a = 1 ', 'b = 2 ']

    import functools, operator
    print(functools.reduce(operator.add, open('some.py')))

    import os

    a = 1

    b = 2

    print(sum([1, 2, 3, 4, 5]))

    15

    print(any(['spam', '', 'mi']))

    True

    print(all(['spam', '', 'mi']))

    False

    print(max([1, 2, 3, 4, 5]))

    5

    print(min([1, 2, 3, 4, 5]))

    1

    max 和min 也可以应用于文件

    print(max(open('some.py')))

    import os

    print(min(open('some.py')))

    a = 1

    迭代协议也可直接作用于文件

    print(list(open('some.py')))

    ['import os ', 'a = 1 ', 'b = 2 ']

    print(tuple(open('some.py')))

    ('import os ', 'a = 1 ', 'b = 2 ')

    print('&&'.join(open('some.py')))# (牛逼)

    import os

    &&a = 1

    &&b = 2

    a, *b = open('some.py')
    print(a)
    print(b)

    import os

    ['a = 1 ', 'b = 2 ']

    解析和集合

    print(set(open('some.py')))

    {'b = 2 ', 'a = 1 ', 'import os '}

    print({line for line in open('some.py')})

    {'a = 1 ', 'b = 2 ', 'import os '}

    print({ix: line for ix, line in enumerate(open('some.py'))})

    {0: 'import os ', 1: 'a = 1 ', 2: 'b = 2 '}

    print({line for line in open('some.py') if line[0] == 'a'})

    {'a = 1 '}

    print({ix: line for ix, line in enumerate(open('some.py')) if line[0] == 'a'})

    {1: 'a = 1 '}

    def f(a, b, c):
    print(a, b, c, sep = '&')

    f(1, 2, 3)

    1-2-3

    f(*open('some.py'))

    import os

    &a = 1

    &b = 2

    x , y = (1, 2), (3, 4)
    print(list(zip(x, y)))

    [(1, 3), (2, 4)]

    a, b = zip(*zip(x, y))
    print(a)
    print(b)

    (1, 2)

    (3, 4)

    range和其他迭代器不同,rang它不是自己的迭代器,并且他支持在结果上的多个迭代器

    他们会记住自己的位置

    r = range(3)
    i1 = iter(r)
    print(next(i1))

    0

    print(next(i1))

    1

    i2 = iter(r)
    print(next(i2))

    0

    print(next(i1))

    2

    而zip,map,filter不支持相同结果上的活跃迭代器

    z = zip((1, 2, 3), (10, 11, 12))
    i1 = iter(z)
    i2 = iter(z)
    print(next(i1))

    (1, 10)

    print(next(i1))

    (2, 11)

    print(next(i2))

    (3, 12)

    m = map(abs,(-1, 0, 1))
    i1 = iter(m)
    i2 = iter(m)
    print(next(i1)) # 1
    print(next(i1)) # 0
    print(next(i1)) # 1

    print(next(i2)) # StopIteration

    r = range(3)
    r1, r2 = iter(r), iter(r)
    print(next(r1)) # 0
    print(next(r1)) # 1
    print(next(r1)) # 2
    print(next(r2)) # 0

    通过iter返回一个新的对象来支持多个迭代器,单个迭代器返回自身。

    py3中字典中由于keys不在返回一个列表,所以应该首先用list来展示他

    或者使用sorted

    d = {'a':1, 'b':2, 'c':3}
    for k in sorted(d.keys()):
    print(k, d[k], end=' ')

    a 1 b 2 c 3

    for k in sorted(d):
    print(k, d[k], end = ' ')

    a 1 b 2 c 3

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  • 原文地址:https://www.cnblogs.com/jibandefeng/p/11204847.html
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