原文:https://git.io/pytips
0x01 介绍了迭代器的概念,即定义了 __iter__() 和 __next__() 方法的对象,或者通过 yield 简化定义的“可迭代对象”,而在一些函数式编程语言(见 0x02 Python 中的函数式编程)中,类似的迭代器常被用于产生特定格式的列表(或序列),这时的迭代器更像是一种数据结构而非函数(当然在一些函数式编程语言中,这两者并无本质差异)。Python 借鉴了 APL, Haskell, and SML 中的某些迭代器的构造方法,并在 itertools 中实现(该模块是通过 C 实现,源代码:/Modules/itertoolsmodule.c)。
itertools 模块提供了如下三类迭代器构建工具:
无限迭代
整合两序列迭代
组合生成器
1. 无限迭代
所谓无限(infinite)是指如果你通过 for...in... 的语法对其进行迭代,将陷入无限循环,包括:
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count(start, [step])
cycle(p)
repeat(elem [,n])
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从名字大概可以猜出它们的用法,既然说是无限迭代,我们自然不会想要将其所有元素依次迭代取出,而通常是结合 map/zip 等方法,将其作为一个取之不尽的数据仓库,与有限长度的可迭代对象进行组合操作:
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from itertools import cycle, count, repeat
print (count.__doc__)
count(start = 0 , step = 1 ) - - > count object
Return a count object whose .__next__() method returns consecutive values.
Equivalent to:
def count(firstval = 0 , step = 1 ):
x = firstval
while 1 :
yield x
x + = step
counter = count()
print ( next (counter))
print ( next (counter))
print ( list ( map ( lambda x, y: x + y, range ( 10 ), counter)))
odd_counter = map ( lambda x: 'Odd#{}' . format (x), count( 1 , 2 ))
print ( next (odd_counter))
print ( next (odd_counter))
0
1
[ 2 , 4 , 6 , 8 , 10 , 12 , 14 , 16 , 18 , 20 ]
Odd #1
Odd #3
print (cycle.__doc__)
cycle(iterable) - - > cycle object
Return elements from the iterable until it is exhausted.
Then repeat the sequence indefinitely.
cyc = cycle( range ( 5 ))
print ( list ( zip ( range ( 6 ), cyc)))
print ( next (cyc))
print ( next (cyc))
[( 0 , 0 ), ( 1 , 1 ), ( 2 , 2 ), ( 3 , 3 ), ( 4 , 4 ), ( 5 , 0 )]
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print (repeat.__doc__)
repeat( object [,times]) - > create an iterator which returns the object
for the specified number of times. If not specified, returns the object
endlessly.
print ( list (repeat( 'Py' , 3 )))
rep = repeat( 'p' )
print ( list ( zip (rep, 'y' * 3 )))
[ 'Py' , 'Py' , 'Py' ]
[( 'p' , 'y' ), ( 'p' , 'y' ), ( 'p' , 'y' )]
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2. 整合两序列迭代
所谓整合两序列,是指以两个有限序列为输入,将其整合操作之后返回为一个迭代器,最为常见的 zip 函数就属于这一类别,只不过 zip 是内置函数。这一类别完整的方法包括:
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accumulate()
chain() / chain.from_iterable()
compress()
dropwhile() / filterfalse() / takewhile()
groupby()
islice()
starmap()
tee()
zip_longest()
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这里就不对所有的方法一一举例说明了,如果想要知道某个方法的用法,基本通过 print(method.__doc__) 就可以了解,毕竟 itertools 模块只是提供了一种快捷方式,并没有隐含什么深奥的算法。这里只对下面几个我觉得比较有趣的方法进行举例说明。
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from itertools import cycle, compress, islice, takewhile, count
# 这三个方法(如果使用恰当)可以限定无限迭代
# print(compress.__doc__)
print ( list (compress(cycle( 'PY' ), [ 1 , 0 , 1 , 0 ])))
# 像操作列表 l[start:stop:step] 一样操作其它序列
# print(islice.__doc__)
print ( list (islice(cycle( 'PY' ), 0 , 2 )))
# 限制版的 filter
# print(takewhile.__doc__)
print ( list (takewhile( lambda x: x < 5 , count())))
[ 'P' , 'P' ]
[ 'P' , 'Y' ]
[ 0 , 1 , 2 , 3 , 4 ]
from itertools import groupby
from operator import itemgetter
print (groupby.__doc__)
for k, g in groupby( 'AABBC' ):
print (k, list (g))
db = [ dict (name = 'python' , script = True ),
dict (name = 'c' , script = False ),
dict (name = 'c++' , script = False ),
dict (name = 'ruby' , script = True )]
keyfunc = itemgetter( 'script' )
db2 = sorted (db, key = keyfunc) # sorted by `script'
for isScript, langs in groupby(db2, keyfunc):
print ( ', ' .join( map (itemgetter( 'name' ), langs)))
groupby(iterable[, keyfunc]) - > create an iterator which returns
(key, sub - iterator) grouped by each value of key(value).
A [ 'A' , 'A' ]
B [ 'B' , 'B' ]
C [ 'C' ]
c, c + +
python, ruby
from itertools import zip_longest
# 内置函数 zip 以较短序列为基准进行合并,
# zip_longest 则以最长序列为基准,并提供补足参数 fillvalue
# Python 2.7 中名为 izip_longest
print ( list (zip_longest( 'ABCD' , '123' , fillvalue = 0 )))
[( 'A' , '1' ), ( 'B' , '2' ), ( 'C' , '3' ), ( 'D' , 0 )]
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3. 组合生成器
关于生成器的排列组合:
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product( * iterables, repeat = 1 ):两输入序列的笛卡尔乘积
permutations(iterable, r = None ):对输入序列的完全排列组合
combinations(iterable, r):有序版的排列组合
combinations_with_replacement(iterable, r):有序版的笛卡尔乘积
from itertools import product, permutations, combinations, combinations_with_replacement
print ( list (product( range ( 2 ), range ( 2 ))))
print ( list (product( 'AB' , repeat = 2 )))
[( 0 , 0 ), ( 0 , 1 ), ( 1 , 0 ), ( 1 , 1 )]
[( 'A' , 'A' ), ( 'A' , 'B' ), ( 'B' , 'A' ), ( 'B' , 'B' )]
print ( list (combinations_with_replacement( 'AB' , 2 )))
[( 'A' , 'A' ), ( 'A' , 'B' ), ( 'B' , 'B' )]
# 赛马问题:4匹马前2名的排列组合(A^4_2)
print ( list (permutations( 'ABCDE' , 2 )))
[( 'A' , 'B' ), ( 'A' , 'C' ), ( 'A' , 'D' ),
( 'A' , 'E' ), ( 'B' , 'A' ), ( 'B' , 'C' ),
( 'B' , 'D' ), ( 'B' , 'E' ), ( 'C' , 'A' ),
( 'C' , 'B' ), ( 'C' , 'D' ), ( 'C' , 'E' ),
( 'D' , 'A' ), ( 'D' , 'B' ), ( 'D' , 'C' ),
( 'D' , 'E' ), ( 'E' , 'A' ), ( 'E' , 'B' ), ( 'E' , 'C' ), ( 'E' , 'D' )]
# 彩球问题:4种颜色的球任意抽出2个的颜色组合(C^4_2)
print ( list (combinations( 'ABCD' , 2 )))
[( 'A' , 'B' ), ( 'A' , 'C' ), ( 'A' , 'D' ), ( 'B' , 'C' ), ( 'B' , 'D' ), ( 'C' , 'D' )]
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