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by contravariant9 hours ago |
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upvoteby est7 hours ago|
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    import mmap, codecs

    from collections import Counter

    def word_count(filepath):

        freq = Counter()
    
        decode = codecs.getincrementaldecoder('utf-8')().decode
    
        with open(filepath, 'rb') as f, mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ) as mm:
        
                for chunk in iter(lambda: mm.read(65536), b''):
            
                        freq.update(decode(chunk).split())
            
                    freq.update(decode(b'', final=True).split())
        
                return freq
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upvoteby zahlman6 hours ago|
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Sure, but making one string from the file contents is surely much better than having a separate string per word in the original data.

... Ah, but I suppose the existing code hasn't avoided that anyway. (It's also creating regex match objects, but those get disposed each time through the loop.) I don't know that there's really a way around that. Given the file is barely a KB, I rather doubt that the illustrated techniques are going to move the needle.

In fact, it looks as though the entire data structure (whether a dict, Counter etc.) should a relatively small part of the total reported memory usage. The rest seems to be internal Python stuff.

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