从单个列表构建字典的最 Pythonic 方法 [英] Most Pythonic Way to Build Dictionary From Single List

问题描述

我有一个日期名称列表(通常是星期一至星期六，但适用特殊情况)，我想从中创建一个字典.我想将每一天的值初始化为零.

I have a list of day names (typically Monday-Saturday, though special cases apply) that I want to create a dictionary out of. I want to initialize the value of each day to zero.

如果我有一个与天数列表长度相同的零列表，这将是 zip() 的一个简单用例.但是，零列表是一种浪费空间，如果这是唯一的解决方案，我会尽快执行以下操作:

If I had a list of zeroes the same length of the list of days, this would be a simple use case of zip(). However, a list of zeroes is a waste of space, and if that were the only solution I'd just as soon do something like:

for day in weekList:
    dayDict[day] = 0

有没有更pythonic的方式?

Is there a more pythonic way?

推荐答案

除了 dict.fromkeys 你还可以使用 dict-comprehension，但是 fromkeys() 比字典推导要快:

Apart from dict.fromkeys you can also use dict-comprehension, but fromkeys() is faster than dict comprehensions:

In [27]: lis = ['a', 'b', 'c', 'd']

In [28]: dic = {x: 0 for x in lis}

In [29]: dic
Out[29]: {'a': 0, 'b': 0, 'c': 0, 'd': 0}

对于 2.6 及更早版本:

For 2.6 and earlier:

In [30]: dic = dict((x, 0) for x in lis)

In [31]: dic
Out[31]: {'a': 0, 'b': 0, 'c': 0, 'd': 0}

timeit 比较:

In [38]: %timeit dict.fromkeys(xrange(10000), 0)         # winner
1000 loops, best of 3: 1.4 ms per loop

In [39]: %timeit {x: 0 for x in xrange(10000)}
100 loops, best of 3: 2.08 ms per loop

In [40]: %timeit dict((x, 0) for x in xrange(10000))
100 loops, best of 3: 4.63 ms per loop

正如@Eumiro 和@mgilson 在评论中提到的，重要的是要注意 fromkeys() 和 dict-comprehensions 如果使用的值是可变的，则可能返回不同的对象对象:

As mentioned in comments by @Eumiro and @mgilson it is important to note that fromkeys() and dict-comprehensions may return different objects if the values used are mutable objects:

In [42]: dic = dict.fromkeys(lis, [])

In [43]: [id(x) for x in dic.values()]
Out[43]: [165420716, 165420716, 165420716, 165420716] # all point to a same object

In [44]: dic = {x: [] for x in lis}

In [45]: [id(x) for x in dic.values()]
Out[45]: [165420780, 165420940, 163062700, 163948812]  # unique objects

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