| #!/usr/bin/python2 | |
| # Copyright (C) 2016 Sixten Bergman | |
| # License WTFPL | |
| # | |
| # This program is free software. It comes without any warranty, to the extent | |
| # permitted by applicable law. | |
| # You can redistribute it and/or modify it under the terms of the Do What The | |
| # Fuck You Want To Public License, Version 2, as published by Sam Hocevar. See |
The goal of this example is to show how an existing C codebase for numerical computing (here c_code.c) can be wrapped in Cython to be exposed in Python.
The meat of the example is that the data is allocated in C, but exposed in Python without a copy using the PyArray_SimpleNewFromData numpy
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| import pandas as pd | |
| import itertools | |
| import time | |
| import multiprocessing | |
| from typing import Callable, Tuple, Union | |
| def groupby_parallel( | |
| groupby_df: pd.core.groupby.DataFrameGroupBy, | |
| func: Callable[[Tuple[str, pd.DataFrame]], Union[pd.DataFrame, pd.Series]], | |
| num_cpus: int = multiprocessing.cpu_count() - 1, |