GitHub - scikit-hep/boost-histogram: Python bindings for the C++14 Boost::Histogram library

#NameDownloadsVersionReleaseLast CommitI/PStars packaging 1,774,380,229/mo 26.224 days ago2026-04-24T20:15:22Z3 days ago2026-05-15T03:29:15Z76/23 728 ★ cibuildwheel 664,556/mo 3.4.11 month ago2026-04-02T13:58:59Z49 minutes ago2026-05-18T23:47:31Z80/11 2,235 ★ build 145,477,982/mo 1.5.018 days ago2026-04-30T03:18:23Z5 hours ago2026-05-18T19:24:47Z9/3 846 ★ pipx 6,177,361/mo 1.12.012 days ago2026-05-06T17:54:11Z12 days ago2026-05-06T17:53:10Z101/7 12,794 ★ dependency-groups 6,131,074/mo 1.3.11 year ago2025-05-02T00:34:27Z2 months ago2026-03-01T23:59:52Z3/1 14 ★ pyproject-metadata 14,812,607/mo 0.11.03 months ago2026-02-09T19:12:49Z3 months ago2026-02-09T19:04:10Z8/5 45 ★ scikit-build-core 10,500,235/mo 0.12.22 months ago2026-03-05T18:25:56Z12 days ago2026-05-06T04:07:15Z137/27 468 ★ scikit-build 1,356,743/mo 0.19.02 months ago2026-03-03T16:20:14Z14 days ago2026-05-04T19:59:09Z166/21 533 ★ cmake (on PyPI) 17,683,357/mo 4.3.225 days ago2026-04-23T21:50:16Z25 days ago2026-04-23T19:02:11Z23/3 133 ★ ninja (on PyPI) 31,523,944/mo 1.13.09 months ago2025-08-11T15:09:50Z19 days ago2026-04-29T05:29:55Z7/2 87 ★ moderncmakedomain 21,874/mo 3.29.01 year ago2024-05-22T04:14:55Z1 month ago2026-04-12T21:40:27Z3/3 32 ★ nox 5,439,195/mo 2026.4.101 month ago2026-04-10T17:42:40Z21 days ago2026-04-27T04:51:45Z69/7 1,522 ★ validate-pyproject 239,632/mo 0.253 months ago2026-02-02T17:31:05Z14 days ago2026-05-04T16:55:44Z8/4 206 ★ validate-pyproject-schema-store 57,612/mo 2026.5.1812 hours ago2026-05-18T11:55:57Z12 hours ago2026-05-18T11:55:06Z4/1 6 ★ pybind11 26,459,991/mo 3.0.429 days ago2026-04-19T03:08:14Z6 hours ago2026-05-18T18:31:19Z632/100 17,863 ★ pybind/python_example1 month ago2026-03-24T21:08:55Z17/1 531 ★ pybind/scikit_build_example1 month ago2026-04-12T06:00:52Z9/3 145 ★ meson-python 15,679,538/mo 0.19.04 months ago2026-01-15T13:52:43Z2 months ago2026-03-02T21:27:42Z45/15 179 ★ boost-histogram 1,465,388/mo 1.7.21 month ago2026-04-11T02:18:34Z5 days ago2026-05-13T17:57:40Z29/7 16

Overview of all pages with the category #Azure DevOps, such as: Azure DevOps: Python Wheels

Python 3.8 is out, with new features and changes. The themes for this release have been performance, ABI/internals, and static typing, along with a smattering of new syntax. Given the recent community statement on Python support, we should be staying up to date with the current changes in Python. As Python 2 sunsets, we are finally in an era where we can hope to someday use the features we see coming out of Python release again!

Bound version constraints (upper caps) are starting to show up in the Python ecosystem. This is causing real world problems with libraries following this recommendation, and is likely to continue to get worse; this practice does not scale to large numbers of libraries or large numbers of users. In this discussion I would like to explain why always providing an upper limit causes far more harm than good even for true SemVer libraries, why libraries that pin upper limits require more frequent updates rather than less, and why it is not scalable. After reading this, hopefully you will always consider every cap you add, you will know the (few) places where pinning an upper limit is reasonable, and will possibly even avoid using libraries that pin upper limits needlessly until the author updates them to remove these pins. If this 10,000 word behemoth is a bit long for you, then skip around using the table of contents, or see the TL;DR section at the end, or read version numbers by Bernát Gábor, which is shorter but is a fantastic read with good examples and cute dog pictures. Or Hynek’s Semantic Versioning Will Not Save You Be sure to check at least the JavaScript project analysis before you leave! Also be warned, I pick on Poetry quite a bit. The rising popularity of Poetry is likely due to the simplicity of having one tool vs. many for packaging, but it happens to also have a special dependency solver, a new upper bound syntax, and a strong recommendation to always limit upper versions - in direct opposition to members of the Python core developer team and PyPA developers. Not all libraries with excessive version capping are Poetry projects (like TensorFlow), but many, many of them are. To be clear, Poetry doesn’t force version pinning on you, but it does push you really, really hard to always version cap, and it’s targeting new Python users that don’t know any better yet than to accept bad recommendations. And these affect the whole ecosystem, including users who do n

This is the second post in a series about Azure DevOps. This one is about release pipelines; if you use Azure to build packages (like binaries, etc.), how do you push them to a final endpoint? In this example, we will be building a simple pure Python package, and pushing the result to Test-PyPI. You can adapt it to your situation, however. The third post will cover building Python binaries. This series was developed to update the testing and releasing of Python packages for Scikit-HEP. Several of the projects in SciKit-HEP are using release pipelines, include boost-histogram and Particle. Note: I now highly recommend GitHub Actions, which is almost “Azure 2.0”. You can read my tutorials on GitHub Actions on the Scikit-HEP developer pages. The release process, in particular, is simpler, and you still get the benefit of artifacts.

Note: I now highly recommend cibuildwheel instead of custom binary wheels. See GHA Pure Python Wheels and GHA Binary Wheels for modern methods to produce wheels on GitHub Actions (directly applicable to Azure, as well, with minor changes; cibuildwheel works on all most major CI providers). See my new posts on cibuildwheel! This is the third post in a series about Azure DevOps. This one is about making Python wheels. If you want to play nice with Python users, or you have a complex build, this will make your package far more accessible to users. They are faster to install and to use and more secure. We will quickly cover making universal wheels, then we will move on to fully compiled binaries, including C++14, manylinux2010, and other hot topics. This series was developed to update the testing and releasing of Python packages for Scikit-HEP. The results of this tutorial can be seen in the boost-histogram repository, under the .ci folder.

The foundational histogramming package for Python, boost-histogram, hit beta status with version 0.6! This is a major update to the new Boost.Histogram bindings. Since I have not written about boost-histogram yet here, I will introduce the library in its current state. Version 0.6.2 was based on the recently released Boost C++ Libraries 1.72 Histogram package. Feel free to visit the docs, or keep reading this post. This Python library is part of a larger picture in the Scikit-HEP ecosystem of tools for Particle Physics and is funded by DIANA/HEP and IRIS-HEP. It is the core library for making and manipulating histograms. Other packages are under development to provide a complete set of tools to work with and visualize histograms. The Aghast package is designed to convert between popular histogram formats, and the Hist package will be designed to make common analysis tasks simple, like plotting via tools such as the mplhep package. Hist and Aghast will be initially driven by HEP (High Energy Physics and Particle Physics) needs, but outside issues and contributions are welcome and encouraged.