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Comment by ims | Hacker News Reader

I think the example in #4 misses the point of using a Counter. He could have done the very same for-loop business if mycounter was a defaultdict(int).

The nice thing about a Counter is that it will take a collection of things and... count them:

    >>> from random import randrange
    >>> from collections import Counter
    >>> mycounter = Counter(randrange(10) for _ in range(100))
    >>> mycounter
    Counter({1: 15, 5: 14, 3: 11, 4: 11, 6: 11, 7: 11, 9: 8, 8: 7, 0: 6, 2: 6})

Docs: https://docs.python.org/2/library/collections.html#counter-o...

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I recently had a use case for this where I needed a naively created bag of words along with the frequency of words. Having Counter made this extremely easy as I could simply split the string on whitespaces and pass the result to a Counter object. Another useful feature is that you can take the intersection of two Counter objects. It's a really nice data structure to have!

Python noob here. What does the _ mean in "...for _ in range(100))"?

It's just a name of a variable. There's nothing special about it (in this context), but it's conventionally used when you don't care about the value assigned to it.

Normally you would place a variable there, such as x or y. But in this case, the variable doesn't matter. You aren't using it in the function call. You're telling the programming the variable for the for loop that it doesn't matter.

To add to specifics:

_ in python is commonly used as a variable name for values you want to throw away. For example, let's say you have a log file split on newlines, with records like this:

    logline = "127.0.0.1 localhost.example.com GET /some/url 404 12413"

You want to get all the URLs that are 404s, but you don't care about who requested them, etc. You could do this:

    _, _, _, url, returncode, _ = logline.split(' ')

There's no special behaviour for _ in this case; in fact, normally in the interactive interpreter it's used to store the result of the last evaluated line, like so:

    >>> SomeModel.objects.all()
    [SomeModel(…), SomeModel(…), SomeModel(…), …]
    >>> d = _
    >>> print d
    [SomeModel(…), SomeModel(…), SomeModel(…), …]

Which I think is basically the same behaviour; you run some code, you don't assign it, so the interpreter dumps it into _ and goes on about its day.

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