numba - TypingError: cannot determine Numba type of <class 'builtin_function_or_method'>
numba - TypingError: cannot determine Numba type of
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Chapters
00:00 Question
01:23 Accepted answer (Score 23)
01:53 Answer 2 (Score 3)
02:50 Thank you
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Full question
https://stackoverflow.com/questions/5074...
Accepted answer links:
[here]: https://numba.pydata.org/numba-doc/dev/r...
Answer 2 links:
[deprecation recommendations]: https://numba.pydata.org/numba-doc/dev/r...
[vectorize the operation]: https://stackoverflow.com/a/45545111/454...
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Content licensed under CC BY-SA
https://meta.stackexchange.com/help/lice...
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Tags
#python #jit #numba
#avk47
ACCEPTED ANSWER
Score 32
Pandas and several other function calls in your code will not work with nopython=True. The available libraries that can be used with numba jit in nopython is fairly limited (pretty much only to numpy arrays and certain python builtin libraries). You can find more information here
ANSWER 2
Score 6
Per the deprecation recommendations, it's very reasonable that code which doesn't compile with @jit(nopython=True) could be faster without the decorator.
Anecdotally, I found the trivial example I landed here researching was notably faster when simply passing the Pandas columns directly to my function to vectorize the operation, rather than using numba and paying the method overhead of the columns for a numpy array.
However, it continues with the expected argument to clear this warning
If there is benefit to having the
@jitdecorator present, then to be future proof supply the keyword argumentforceobj=Trueto ensure the function is always compiled in object mode.