Python 函數語言程式設計 -- itertools 模組
阿新 • • 發佈：2018-12-13
– Start
itertools 模組提供了非常多的方法。
Infinite iterators
| Iterator | Arguments | Results | Example |
|---|---|---|---|
| count() | start, [step] | start, start+step, start+2*step, … | count(10) --> 10 11 12 13 14 … |
| cycle() | p | p0, p1, … plast, p0, p1, … | cycle(‘ABCD’) --> A B C D A B C D … |
| repeat() | elem [,n] | elem, elem, elem, … endlessly or up to n times | repeat(10, 3) --> 10 10 10 |
import itertools as it
# count
count_iter = it.count(10)
print([next(count_iter) for i in range(5)])
# cycle
cycle_iter = it.cycle('ABCD')
print([next(cycle_iter) for i in range(8)])
# repeat
repeat_iter = it.repeat(10, 3)
print([next(repeat_iter) for i in range(3)])
Iterators terminating on the shortest input sequence
| Iterator | Arguments | Results | Example |
|---|---|---|---|
| accumulate() | p [,func] | p0, p0+p1, p0+p1+p2, … | accumulate([1,2,3,4,5]) --> 1 3 6 10 15 |
| chain() | p, q, … | p0, p1, … plast, q0, q1, … | chain(‘ABC’, ‘DEF’) --> A B C D E F |
| chain.from_iterable() | iterable | p0, p1, … plast, q0, q1, … | chain.from_iterable([‘ABC’, ‘DEF’]) --> A B C D E F |
| compress() | data, selectors | (d[0] if s[0]), (d[1] if s[1]), … | compress(‘ABCDEF’, [1,0,1,0,1,1]) --> A C E F |
| dropwhile() | pred, seq | seq[n], seq[n+1], starting when pred fails | dropwhile(lambda x: x<5, [1,4,6,4,1]) --> 6 4 1 |
| filterfalse() | pred, seq | elements of seq where pred(elem) is false | filterfalse(lambda x: x%2, range(10)) --> 0 2 4 6 8 |
| groupby() | iterable[, key] | sub-iterators grouped by value of key(v) | |
| islice() | seq, [start,] stop [, step] | elements from seq[start:stop:step] | islice(‘ABCDEFG’, 2, None) --> C D E F G |
| starmap() | func, seq | func(*seq[0]), func(*seq[1]), … | starmap(pow, [(2,5), (3,2), (10,3)]) --> 32 9 1000 |
| takewhile() | pred, seq | seq[0], seq[1], until pred fails | takewhile(lambda x: x<5, [1,4,6,4,1]) --> 1 4 |
| tee() | it, n | it1, it2, … itn splits one iterator into n | |
| zip_longest() | p, q, … | (p[0], q[0]), (p[1], q[1]), … | zip_longest(‘ABCD’, ‘xy’, fillvalue=’-’) --> Ax By C- D- |
import itertools as it
# accumulate
print(list(it.accumulate([1, 2, 3, 4, 5])))
# chain
print(list(it.chain('ABC', 'DEF')))
# chain.from_iterable
print(list(it.chain.from_iterable(['ABC', 'DEF'])))
# compress
print(list(it.compress('ABCDEF', [1, 0, 1, 0, 1, 1])))
# dropwhile
print(list(it.dropwhile(lambda x: x < 5, [1, 4, 6, 4, 1])))
# filterfalse
print(list(it.filterfalse(lambda x: x % 2, range(10))))
# groupby
print([list(g) for k, g in it.groupby('AAAABBBCCD')])
# islice
print(list(it.islice('ABCDEFG', 2, None)))
# starmap
print(list(it.starmap(pow, [(2,5), (3,2), (10,3)])))
# takewhile
print(list(it.takewhile(lambda x: x < 5, [1, 4, 6, 4, 1])))
# takewhile
print(list(it.takewhile(lambda x: x < 5, [1, 4, 6, 4, 1])))
# tee
my_iter = iter(range(10))
it1, it2 = it.tee(my_iter, 2)
print(list(it1))
print(list(it2))
# zip_longest
print(list(it.zip_longest('ABCD', 'xy', fillvalue='-')))
Combinatoric iterators
| Iterator | Arguments | Results |
|---|---|---|
| product() | p, q, … [repeat=1] | cartesian product, equivalent to a nested for-loop |
| permutations() | p[, r] | r-length tuples, all possible orderings, no repeated elements |
| combinations() | p, r | r-length tuples, in sorted order, no repeated elements |
| combinations_with_replacement() | p, r | r-length tuples, in sorted order, with repeated elements |
| product(‘ABCD’, repeat=2) | AA AB AC AD BA BB BC BD CA CB CC CD DA DB DC DD | |
| permutations(‘ABCD’, 2) | AB AC AD BA BC BD CA CB CD DA DB DC | |
| combinations(‘ABCD’, 2) | AB AC AD BC BD CD | |
| combinations_with_replacement(‘ABCD’, 2) | AA AB AC AD BB BC BD CC CD DD |
import itertools as it
# product
print(list(it.product('ABCD', repeat=2)))
# permutations
# n! / (n-r)!
print(list(it.permutations('ABCD', 2)))
# combinations
# n! / r! / (n-r)!
print(list(it.combinations('ABCD', 2)))
# combinations_with_replacement
# (n+r-1)! / r! / (n-1)!
print(list(it.combinations_with_replacement('ABCD', 2)))
自定義函式
儘管 Python 提供了大量的函式為函數語言程式設計服務，有時候我們還是需要自定義函式，一是為了實現特殊功能，二是為了封裝已有函式使可讀性更好。如，我們想實現類似 SQL 取前 10 條資料的功能，我們可以這樣寫。
list(islice(iterable, n))
為了可讀性更好，我們可以定義一個函式來封裝它。
def top(n, iterable):
return list(islice(iterable, n))
自定義函式要遵循 currying 原則，一個函式只實現一個功能，每次只處理一個元素，避免消耗記憶體，返回一個可迭代物件。
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– Last Updated on 2018-10-05
– Written by ShangBo on 2018-10-04
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