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154 lines
2.2 KiB
Markdown
154 lines
2.2 KiB
Markdown
# collections 模块：更多数据结构
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In [1]:
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```py
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import collections
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```
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## 计数器
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可以使用 `Counter(seq)` 对序列中出现的元素个数进行统计。
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例如，我们可以统计一段文本中出现的单词及其出现的次数：
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In [2]:
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```py
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from string import punctuation
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sentence = "One, two, three, one, two, tree, I come from China."
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words_count = collections.Counter(sentence.translate(None, punctuation).lower().split())
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print words_count
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```
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```py
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Counter({'two': 2, 'one': 2, 'from': 1, 'i': 1, 'tree': 1, 'three': 1, 'china': 1, 'come': 1})
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```
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## 双端队列
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双端队列支持从队头队尾出入队：
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In [3]:
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```py
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dq = collections.deque()
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for i in xrange(10):
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dq.append(i)
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print dq
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for i in xrange(10):
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print dq.pop(),
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print
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for i in xrange(10):
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dq.appendleft(i)
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print dq
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for i in xrange(10):
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print dq.popleft(),
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```
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```py
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deque([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
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9 8 7 6 5 4 3 2 1 0
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deque([9, 8, 7, 6, 5, 4, 3, 2, 1, 0])
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9 8 7 6 5 4 3 2 1 0
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```
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与列表相比，双端队列在队头的操作更快：
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In [4]:
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```py
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lst = []
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dq = collections.deque()
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%timeit -n100 lst.insert(0, 10)
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%timeit -n100 dq.appendleft(10)
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```
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```py
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100 loops, best of 3: 598 ns per loop
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100 loops, best of 3: 291 ns per loop
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```
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## 有序字典
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字典的 `key` 按顺序排列：
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In [5]:
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```py
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items = (
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('A', 1),
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('B', 2),
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('C', 3)
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)
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regular_dict = dict(items)
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ordered_dict = collections.OrderedDict(items)
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print 'Regular Dict:'
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for k, v in regular_dict.items():
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print k, v
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print 'Ordered Dict:'
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for k, v in ordered_dict.items():
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print k, v
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```
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```py
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Regular Dict:
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A 1
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C 3
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B 2
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Ordered Dict:
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A 1
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B 2
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C 3
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```
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## 带默认值的字典
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对于 `Python` 自带的词典 `d`，当 `key` 不存在的时候，调用 `d[key]` 会报错，但是 `defaultdict` 可以为这样的 `key` 提供一个指定的默认值，我们只需要在定义时提供默认值的类型即可，如果 `key` 不存在返回指定类型的默认值：
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In [6]:
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```py
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dd = collections.defaultdict(list)
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print dd["foo"]
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dd = collections.defaultdict(int)
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print dd["foo"]
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dd = collections.defaultdict(float)
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print dd["foo"]
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```
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```py
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[]
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0
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0.0
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``` |