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[Solved] numba – TypingError: cannot determine Numba type of

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error numba – TypingError: cannot determine Numba type of <class ‘builtin_function_or_method‘> in python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How numba – TypingError: cannot determine Numba type of <class ‘builtin_function_or_method’> Error Occurs?

Today I get the following error numba – TypingError: cannot determine Numba type of <class ‘builtin_function_or_method‘> in python.

How To Solve numba – TypingError: cannot determine Numba type of <class ‘builtin_function_or_method’> Error ?

  1. How To Solve numba – TypingError: cannot determine Numba type of Error ?

    To Solve numba – TypingError: cannot determine Numba type of <class 'builtin_function_or_method'> Error Pandas and several other function calls in your code will not work with nopython=True.

  2. numba – TypingError: cannot determine Numba type of

    To Solve numba – TypingError: cannot determine Numba type of <class 'builtin_function_or_method'> Error Pandas and several other function calls in your code will not work with nopython=True.

Solution 1

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).

Solution 2

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 @jit decorator present, then to be future proof supply the keyword argument forceobj=True to ensure the function is always compiled in object mode.

Summery

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