NumPy C-API

.. _c-api:

########### NumPy C-API ###########

.. sectionauthor:: Travis E. Oliphant

| Beware of the man who won't be bothered with details. | --- William Feather, Sr.

| The truth is out there. | --- Chris Carter, The X Files

NumPy provides a C-API to enable users to extend the system and get access to the array object for use in other routines. The best way to truly understand the C-API is to read the source code. If you are unfamiliar with (C) source code, however, this can be a daunting experience at first. Be assured that the task becomes easier with practice, and you may be surprised at how simple the C-code can be to understand. Even if you don't think you can write C-code from scratch, it is much easier to understand and modify already-written source code than create it de novo.

Python extensions are especially straightforward to understand because they all have a very similar structure. Admittedly, NumPy is not a trivial extension to Python, and may take a little more snooping to grasp. This is especially true because of the code-generation techniques, which simplify maintenance of very similar code, but can make the code a little less readable to beginners. Still, with a little persistence, the code can be opened to your understanding. It is my hope, that this guide to the C-API can assist in the process of becoming familiar with the compiled-level work that can be done with NumPy in order to squeeze that last bit of necessary speed out of your code.

.. currentmodule:: numpy-c-api

.. toctree:: :maxdepth: 2

types-and-structures config dtype array iterator ufunc generalized-ufuncs strings coremath datetimes deprecations data_memory