你大概不知道的30个Python语言的特点能力(3)
从我开始进修Python时我就抉择维护一个常常利用的“窍门”列表。岂论何时当我看到一段让我以为“酷,这样也行!”的代码时(在一个例子中、在StackOverflow、在开源码软件中,等等),我会实验它直到领略它,然后把它添加到列表中。这篇文章是清理过列表的一部门。假如你是一个有履历的Python措施员,尽量你大概已经知道一些,但你仍能发明一些你不知道的。假如你是一个正在进修Python的C、C++或Java措施员,可能刚开始进修编程,那么你会像我一样发明它们中的许多很是有用。
每个窍门或语言特性只能通过实例来验证,无需过多表明。固然我已极力使例子清晰,但它们中的一些仍会看起来有些巨大,这取决于你的熟悉水平。所以假如看过例子后还不清楚的话,标题可以或许提供足够的信息让你通过Google获取具体的内容。
列表按难度排序,常用的语言特征和能力放在前面。
1.30 最大最小元素 (heapq.nlargest和heapq.nsmallest)
>>> a = [random.randint(0, 100) for __ in xrange(100)]
>>> heapq.nsmallest(5, a)
[3, 3, 5, 6, 8]
>>> heapq.nlargest(5, a)
[100, 100, 99, 98, 98]
1.31 笛卡尔乘积 (itertools.product)
>>> for p in itertools.product([1, 2, 3], [4, 5]):
(1, 4)
(1, 5)
(2, 4)
(2, 5)
(3, 4)
(3, 5)
>>> for p in itertools.product([0, 1], repeat=4):
… print ''.join(str(x) for x in p)
…
0000
0001
0010
0011
0100
0101
0110
0111
1000
1001
1010
1011
1100
1101
1110
1111
1.32 组合的组合和置换 (itertools.combinations 和 itertools.combinations_with_replacement)
>>> for c in itertools.combinations([1, 2, 3, 4, 5], 3):
… print ''.join(str(x) for x in c)
…
123
124
125
134
135
145
234
235
245
345
>>> for c in itertools.combinations_with_replacement([1, 2, 3], 2):
… print ''.join(str(x) for x in c)
…
11
12
13
22
23
33
1.33 排序 (itertools.permutations)
>>> for p in itertools.permutations([1, 2, 3, 4]):
… print ''.join(str(x) for x in p)
…
1234
1243
1324
1342
1423
1432
2134
2143
2314
2341
2413
2431
3124
3142
3214
3241
3412
3421
4123
4132
4213
4231
4312
4321
1.34 链接的迭代 (itertools.chain)
>>> a = [1, 2, 3, 4]
>>> for p in itertools.chain(itertools.combinations(a, 2), itertools.combinations(a, 3)):
… print p
…
(1, 2)
(1, 3)
(1, 4)
(2, 3)
(2, 4)
(3, 4)
(1, 2, 3)
(1, 2, 4)
(1, 3, 4)
(2, 3, 4)
>>> for subset in itertools.chain.from_iterable(itertools.combinations(a, n) for n in range(len(a) + 1))
… print subset
…
()
(1,)
(2,)
(3,)
(4,)
(1, 2)
(1, 3)
(1, 4)
(2, 3)
(2, 4)
(3, 4)
(1, 2, 3)
(1, 2, 4)
(1, 3, 4)
(2, 3, 4)
(1, 2, 3, 4)
1.35 按给定值分组行 (itertools.groupby)
>>> from operator import itemgetter
>>> import itertools
>>> with open('contactlenses.csv', 'r') as infile:
… data = [line.strip().split(',') for line in infile]
…
>>> data = data[1:]
>>> def print_data(rows):
… print '\n'.join('\t'.join('{: <16}'.format(s) for s in row) for row in rows)
…
>>> print_data(data)
young myope no reduced none
young myope no normal soft
#p#分页标题#e#
young myope yes reduced none
young myope yes normal hard
young hypermetrope no reduced none
young hypermetrope no normal soft
young hypermetrope yes reduced none
young hypermetrope yes normal hard
pre-presbyopic myope no reduced none
pre-presbyopic myope no normal soft
pre-presbyopic myope yes reduced none
pre-presbyopic myope yes normal hard
pre-presbyopic hypermetrope no reduced none
pre-presbyopic hypermetrope no normal soft
pre-presbyopic hypermetrope yes reduced none
pre-presbyopic hypermetrope yes normal none
presbyopic myope no reduced none
presbyopic myope no normal none
presbyopic myope yes reduced none
presbyopic myope yes normal hard
presbyopic hypermetrope no reduced none
presbyopic hypermetrope no normal soft
#p#分页标题#e#
presbyopic hypermetrope yes reduced none
presbyopic hypermetrope yes normal none
>>> data.sort(key=itemgetter(-1))
>>> for value, group in itertools.groupby(data, lambda r: r[-1]):
… print '———–'
… print 'Group: ' + value
… print_data(group)
…
———–
Group: hard
young myope yes normal hard
young hypermetrope yes normal hard
pre-presbyopic myope yes normal hard
presbyopic myope yes normal hard
———–
Group: none
young myope no reduced none
young myope yes reduced none
young hypermetrope no reduced none
young hypermetrope yes reduced none
pre-presbyopic myope no reduced none
pre-presbyopic myope yes reduced none
pre-presbyopic hypermetrope no reduced none
pre-presbyopic hypermetrope yes reduced none
pre-presbyopic hypermetrope yes normal none
presbyopic myope no reduced none
presbyopic myope no normal none
presbyopic myope yes reduced none
#p#分页标题#e#
presbyopic hypermetrope no reduced none
presbyopic hypermetrope yes reduced none
presbyopic hypermetrope yes normal none
———–
Group: soft
young myope no normal soft
young hypermetrope no normal soft
pre-presbyopic myope no normal soft
pre-presbyopic hypermetrope no normal soft
presbyopic hypermetrope no normal soft