python标准库Itertools和collections实用技巧

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发布于 2019-07-31 15:52:45

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发布于 2019-07-31 15:52:45

文章被收录于专栏：机器学习与python集中营机器学习与python集中营

Itertools技巧

▍1、Flatten iterables

>>> a = [[1, 2], [3, 4], [5, 6]]
>>> list(itertools.chain.from_iterable(a))
[1, 2, 3, 4, 5, 6]

▍2、从iterables创建笛卡尔积

>>> for p in itertools.product([1, 2, 3], [4, 5]):
>>>      print(''.join(str(x) for x in p))

(1, 4)
(1, 5)
(2, 4)
(2, 5)
(3, 4)
(3, 5)

▍3、从iterable创建排列

>>> for p in itertools.permutations([1, 2, 3, 4]):
>>>      print(''.join(str(x) for x in p))
123
132
213
231
312
321

▍4、从iterable创建ngram

>>> from itertools import islice
>>> def n_grams(a, n):
...          z = (islice(a, i, None) for i in range(n))
...          return zip(*z)
...
>>> a = [1, 2, 3, 4, 5, 6]
>>> n_grams(a, 3)
[(1, 2, 3), (2, 3, 4), (3, 4, 5), (4, 5, 6)]
>>> n_grams(a, 2)
[(1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]
>>> n_grams(a, 4)
[(1, 2, 3, 4), (2, 3, 4, 5), (3, 4, 5, 6)]

▍5、使用填充组合元组的两个迭代器或使用填充pivot嵌套迭代

>>> import itertools as it
>>> x = [1, 2, 3, 4, 5]
>>> y = ['a', 'b', 'c']
>>> list(zip(x, y))
[(1, 'a'), (2, 'b'), (3, 'c')]

>>> list(it.zip_longest(x, y))
[(1, 'a'), (2, 'b'), (3, 'c'), (4, None), (5, None)]

▍6、从一个iterable n中创建k个组合

>>> import itertools
>>> bills = [20, 20, 20, 10, 10, 10, 10, 10, 5, 5, 1, 1, 1, 1, 1]
>>> list(itertools.combinations(bills, 3))
[(20, 20, 20), (20, 20, 10), (20, 20, 10), ... ]

▍7、在给定函数情况下创建一个迭代的累积结果

>>> import itertools
>>> list(itertools.accumulate([9, 21, 17, 5, 11, 12, 2, 6], min))
[9, 9, 9, 5, 5, 5, 2, 2]

▍8、创建一个迭代器，只要谓词为True，就从iterable返回元素

>>> import itertools
>>> itertools.takewhile(lambda x: x < 3, [0, 1, 2, 3, 4])
[0, 1, 2]

>>> it.dropwhile(lambda x: x < 3, [0, 1, 2, 3, 4])
[3, 4]

▍9、创建一个迭代器，它从iterable中过滤元素，只返回谓词为False的元素

>>> import itertools
# keeping only false values
>>> list(itertools.filterfalse(bool, [None, False, 1, 0, 10]))
[None, False, 0]

10、使用从迭代的迭代中获得的参数来计算函数

>>> import itertools
>>> import operator
>>> a = [(2, 6), (8, 4), (7, 3)]
>>> list(itertools.starmap(operator.mul, a))
[12, 32, 21]

collections技巧

▍11、设置基本操作

>>> A = {1, 2, 3, 3}
>>> A
set([1, 2, 3])
>>> B = {3, 4, 5, 6, 7}
>>> B
set([3, 4, 5, 6, 7])
>>> A | B
set([1, 2, 3, 4, 5, 6, 7])
>>> A & B
set([3])
>>> A - B
set([1, 2])
>>> B - A
set([4, 5, 6, 7])
>>> A ^ B
set([1, 2, 4, 5, 6, 7])
>>> (A ^ B) == ((A - B) | (B - A))
True

▍12、计数器数据结构（无序集合，其中元素存储为字典键，其计数存储为字典值）

import collections

>>> A = collections.Counter([1, 1, 2, 2, 3, 3, 3, 3, 4, 5, 6, 7])
>>> A
Counter({3: 4, 1: 2, 2: 2, 4: 1, 5: 1, 6: 1, 7: 1})
>>> A.most_common(1)
[(3, 4)]
>>> A.most_common(3)
[(3, 4), (1, 2), (2, 2)]

▍13、默认字典结构（字典的子类，在访问不存在的键时检索默认值）

>>> import collections
>>> m = collections.defaultdict(int)
>>> m['a']
0

>>> m = collections.defaultdict(str)
>>> m['a']
''
>>> m['b'] += 'a'
>>> m['b']
'a'

>>> m = collections.defaultdict(lambda: '[default value]')
>>> m['a']
'[default value]'
>>> m['b']
'[default value]'

>>> m = collections.defaultdict(list)
>>> m['a']
[]

▍14、有序的dict结构（保持有序字典的子类）

>>> from collections import OrderedDict

>>> d = OrderedDict.fromkeys('abcde')
>>> d.move_to_end('b')
>>> ''.join(d.keys())
'acdeb'

>>> d.move_to_end('b', last=False)
>>> ''.join(d.keys())
'bacde'

▍15、Deques结构（Deques是堆栈和队列的概括）

>>> import collection
>>> Q = collections.deque()
>>> Q.append(1)
>>> Q.appendleft(2)
>>> Q.extend([3, 4])
>>> Q.extendleft([5, 6])
>>> Q
deque([6, 5, 2, 1, 3, 4])
>>> Q.pop()
4
>>> Q.popleft()
6
>>> Q
deque([5, 2, 1, 3])
>>> Q.rotate(3)
>>> Q
deque([2, 1, 3, 5])
>>> Q.rotate(-3)
>>> Q
deque([5, 2, 1, 3])

>>> last_three = collections.deque(maxlen=3)
>>> for i in range(4):
...         last_three.append(i)
...         print ', '.join(str(x) for x in last_three)
...
0
0, 1
0, 1, 2
1, 2, 3
2, 3, 4

▍16、命名元组结构（创建类元组的对象，这些对象的字段可通过属性查找访问，也可索引和迭代）

>>> import collections
>>> Point = collections.namedtuple('Point', ['x', 'y'])
>>> p = Point(x=1.0, y=2.0)
>>> p
Point(x=1.0, y=2.0)
>>> p.x
1.0
>>> p.y
2.0

▍17、使用字典来存储Switch

>>> func_dict = {'sum': lambda x, y: x + y, 'subtract': lambda x, y: x - y}
>>> func_dict['sum'](9,3)
12
>>> func_dict['subtract'](9,3)
6

▍18、数据类结构

>>> from dataclasses import dataclass

>>> @dataclass
>>> class DataClassCard:
>>>     rank: str
>>>      suit: str

>>> queen_of_hearts = DataClassCard('Q', 'Hearts')
>>> queen_of_hearts.rank
'Q'
>>> queen_of_hearts
DataClassCard(rank='Q', suit='Hearts')
>>> queen_of_hearts == DataClassCard('Q', 'Hearts')
True

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原始发表：2019-07-26，如有侵权请联系 cloudcommunity@tencent.com 删除

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