itertools.groupby()/itertools.compress() 笔记

关于itertools.groupby()

itertools.groupby()就是将相邻的并且相同的键值划分为同一组，相似功能可以看https://docs.python.org/3/library/itertools.html?highlight=groupby#itertools.groupby写的groupby类

>>> list_a
['A', 'A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'D', 'A', 'A', 'B', 'B', 'B']
>>> for date, items in groupby(list_a):
... print('date: {}'.format(date))
... for item in items:
... print(item, end=" ")
... print("\n==========")
...
date: A
A A A A
==========
date: B
B B B
==========
date: C
C C
==========
date: D
D
==========
date: A
A A
==========
date: B
B B B
==========

是不是发现上述例子还有可简化之处,毕竟A的分组要都归为一组(这是因为存在不相邻的A才出现的情况):

>>> list_a
['A', 'A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'D', 'A', 'A', 'B', 'B', 'B']
>>> list_a.sort(key=lambda list: list) # 经过lambda匿名函数排序后,将相邻的元素放在一起
>>> list_a
['A', 'A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B', 'B', 'C', 'C', 'D']
>>> for date, items in groupby(list_a):
... print('date: {}'.format(date))
... for item in items:
... print(item, end=" ")
... print("\n==========")
...
date: A
A A A A A A
==========
date: B
B B B B B B
==========
date: C
C C
==========
date: D
D
==========

除了使用lambda匿名函数之外,还可以使用operator.itemgetter()函数，效率比lambda更快一些，具体可以看《Python Cookbook》

关于itertools.compress(data, selectors)

根据传递进去的选择器进行判断是否保留数据

>>> list1 = [1, 4, 7, 2, 98, 3, 6, 2]
>>> list_TF = [0,1,0,1,1,1,0,0]
>>> list_TF = [n ==1 for n in list_TF]
>>> list_TF
[False, True, False, True, True, True, False, False]
>>> from itertools import compress
>>> list(compress(list1, list_TF))
[4, 2, 98, 3]

其实通过教程我们还可以发现compress是大致如下：

>>> list1
[1, 4, 7, 2, 98, 3, 6, 2]
>>> list_TF
[False, True, False, True, True, True, False, False]
>>> [n for n,s in zip(list1, list_TF) if s]
[4, 2, 98, 3]

如果觉得慢,还可以使用生成器来代替