An example of using numpy with pybind11

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iulusoy lkeegan

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Project description

pybind11-numpy-example

What

A simple example of how to use pybind11 with numpy and publish this as a library on PyPI and conda-forge.

This C++/Python library creates a std::vector of 16-bit ints, and provides a Python interface to the contents of this vector in a few different ways:

a Python List (copy the data)
a NumPy ndarray (copy the data).
a NumPy ndarray (move the data).

Why

Python Lists are great! However, when storing many small elements of the same type, a Numpy array is much faster and uses a lot less memory:

Memory used vs number of elements

Time used vs number of elements

How

The pybind11 code is in src/pybind11_numpy_example_python.cpp.

The python package is defined in pyproject.toml and uses scikit-build-core.

Each tagged commit triggers a GitHub action job which uses cibuildwheel to build and upload a new release including binary wheels for all platforms to PyPI.

The conda-forge package is generated from this recipe, and automatically updates when a new version is uploaded to PyPI.

The scripts used to generate the above plots are in scripts.

This repo was quickly set up using the SSC C++ Project Cookiecutter.

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This version

1.0.1

Sep 9, 2024

1.0.0

May 27, 2024

0.0.13

May 22, 2024

0.0.12

Apr 25, 2024

0.0.11

Jan 15, 2024

0.0.10

Jan 12, 2024

0.0.9

Jan 12, 2024

0.0.8

Jan 4, 2024

0.0.7

Sep 19, 2023

0.0.6

Aug 10, 2023

0.0.5

Mar 21, 2023

0.0.4

Aug 22, 2022

0.0.3

Aug 24, 2021

0.0.2

Jun 29, 2021

0.0.1

Jun 29, 2021

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pybind11-numpy-example 1.0.1

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Algorithm	Hash digest
SHA256	`5a1462a7a3440e1b5a75e42a55383072550f0691e5ab34cede8d04a0eb17dace`
MD5	`67d38e580c0e7f25c5df931fdc52ad31`
BLAKE2b-256	`9d3c35b1e05822124bee9072a02bf36ee6c7d11d1156301aac59f00ef090966e`

Algorithm	Hash digest
SHA256	`85e46f5a03b14e3c26bd90c7569ae08ed2d7bb143ef9f045c72ed42befb49513`
MD5	`506236b9ac588061483b5517e8248347`
BLAKE2b-256	`be759a7c252f741eb71fa840da68b7b4b6cbe96f4588c73ac52dda188c689869`

Algorithm	Hash digest
SHA256	`cfd2d05cbb6a756b2849ca26cdec6256bafb39609b20e7679d8ee784d5f41e1b`
MD5	`7148269dda5409ffab745f2ae6f1a5c3`
BLAKE2b-256	`81efc3ceaa0749771bb0c49d501a57462547eaa1641a5648d179809dfc10f8b0`

Algorithm	Hash digest
SHA256	`307e75af2956d4f6a8ed57c6043850056d4c3804b6c4cb8321e265cd2c5639d2`
MD5	`edd4f9a7a2066ab5be9a264e36def426`
BLAKE2b-256	`3d7eaa0ee541e368053fe5cca57c3972bb4b14fb1d659dcbe2816a9b99941b03`

Algorithm	Hash digest
SHA256	`bef2c2015cf01243230ffa16841410acd6c18d8a307a49c1554fd87d99fe787a`
MD5	`143d863fe9955ec872de2046c6097cad`
BLAKE2b-256	`a385b62f677f315a7b758ba17da4f714ed189fdf79b3a4e757314d134114f3f7`

Algorithm	Hash digest
SHA256	`ae94841c2db4e31a2cb4aea71a35e9745f3329a956621b8ab43310250ffd0fa8`
MD5	`bd9c4dde805170b6049e26fca71f0233`
BLAKE2b-256	`caadaabd8d07aca08d1d4b7e29c179cc9357f4163c4bd06cb5a060425a735bf1`

Algorithm	Hash digest
SHA256	`6d487dc4b2011ba9ac4cf98c12a041aa5887630e286894ff7c6347c66deccbbe`
MD5	`4c61a88f6f2ed8118dc9dc16e04fbf3e`
BLAKE2b-256	`ea15da5bfe9cf4f68c6526e2bd207d0b101729fd853588e27136fd923ff3f068`

Algorithm	Hash digest
SHA256	`9819f4897009f50c82bac2418a6cc4bb282f518b3bf6ce16e91ce0688954c588`
MD5	`7f833f472c325ba72e3108a962025555`
BLAKE2b-256	`ce1c492279597801d37403f5554c0c997b3f7b948f32ee53f2dedf8993fd1475`

Algorithm	Hash digest
SHA256	`ddc5eef9b724209f021ca594d2e9ddf5eae6857524b39b44ebc43a552fc7d006`
MD5	`c19576e7aee8909511e1e0bdade575ad`
BLAKE2b-256	`2693db53feaf9450bf78455cee0dfa3a3485280956da08b45db0148f04571d57`

Algorithm	Hash digest
SHA256	`7ec7b3508fc96855edea9bc40ec8b4e42e8bb3a2e98b4ad9b05df0ca45b69a78`
MD5	`f53cc933f09f5a1cfec7133912fdba7f`
BLAKE2b-256	`4e279b543537cf111f38e8e16f895d801d69e69400c9f38b33f7bcb2cad707be`