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Comment by kortex | Hacker News Reader

But you are still wrong. As mentioned, Dicts are incredibly efficient data structures in Python (because they underpin everything) and the Counter class is pure python. That's 100% pure python. Saying dicts "don't count" because they are implemented in C would disqualify the entire language of CPython, as virtually everything under the hood is a PyObject struct pointer. It just so happens that "counting abstract objects" is the class of problem* CPython does basically all the time in normal VM execution anyways, so this task is easy and fast.

* looking up a reference of an attribute with a string key underpins the meat and potatoes of python's execution model

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I have no dog in this fight, but I do want to point out that’s it’s not exactly true that Counter is implemented in pure Python:

* it’s a subclass of dict

* its update method (used by the code in the post) dispatches to a C implementation on its fast path

Yes, that's exactly what I said. dict.update is in C, because it's a core feature of the python vm. It's pure CPython. What do you think "pure python" is? There's no python hardware ISA (afaik). All cpython is manipulating data structures in C via Python VM opcodes. It just so happens that whatever opcodes that are dispatched in the course of solving this problem are quite efficient.

If you say "it does not count as Real Python if you dispatch to C", then you literally cannot execute any CPython vm opcodes, because it's all dispatching to C under the hood.

“Pure Python” commonly means implemented using only the Python language. Something written in pure Python ought to be portable across Python implementations. I was merely pointing out that this line

https://github.com/python/cpython/blob/4395ff1e6a18fb26c7a66...

isn’t exactly pure Python, because, under a different runtime (eg PyPy), the code would take a different path (the “pure Python” implementation of _count_elements[1] instead of the C implementation[2][3]). Yes, it's hard to draw exact lines when it comes to Python, especially as the language is so tied to its implementation. However, I think in this case it's relatively clear that the code that specific line is calling is an optimization in CPython, specifically intended to get around some of the VM overhead. Said optimization comes into play in the OP.

[1]: https://github.com/python/cpython/blob/4395ff1e6a18fb26c7a66...

[2]: https://github.com/python/cpython/blob/4395ff1e6a18fb26c7a66...

[3]: https://github.com/python/cpython/blob/4395ff1e6a18fb26c7a66...

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