News

NumPy 2.0 release date: June 16#

23 May, 2024 – We are excited to announce that NumPy 2.0 is planned to be released on June 16, 2024. This release has been over a year in the making, and is the first major release since 2006. Importantly, in addition to many new features and performance improvement, it contains breaking changes to the ABI as well as the Python and C APIs. It is likely that downstream packages and end user code needs to be adapted - if you can, please verify whether your code works with NumPy 2.0.0rc2. Please see the following for more details:

NumFOCUS end of the year fundraiser#

Dec 19, 2023 – NumFOCUS has teamed up with PyCharm during their EOY campaign to offer a 30% discount on first-time PyCharm licenses. All year-one revenue from PyCharm purchases from now until December 23rd, 2023 will go directly to the NumFOCUS programs.

Use unique URL that will allow to track purchases https://lp.jetbrains.com/support-data-science/ or a coupon code ISUPPORTDATASCIENCE 

NumPy 1.26.0 released#

Sep 16, 2023 – NumPy 1.26.0 is now available. The highlights of the release are:

  • Python 3.12.0 support.
  • Cython 3.0.0 compatibility.
  • Use of the Meson build system
  • Updated SIMD support
  • f2py fixes, meson and bind(x) support
  • Support for the updated Accelerate BLAS/LAPACK library

The NumPy 1.26.0 release is a continuation of the 1.25.x series that marks the transition to the Meson build system and provision of support for Cython 3.0.0. A total of 20 people contributed to this release and 59 pull requests were merged.

The Python versions supported by this release are 3.9-3.12.

numpy.org is now available in Japanese and Portuguese#

Aug 2, 2023 – numpy.org is now available in 2 additional languages: Japanese and Portuguese. This wouldn’t be possible without our dedicated volunteers:

Portuguese:

  • Melissa Weber Mendonça (melissawm)
  • Ricardo Prins (ricardoprins)
  • Getúlio Silva (getuliosilva)
  • Julio Batista Silva (jbsilva)
  • Alexandre de Siqueira (alexdesiqueira)
  • Alexandre B A Villares (villares)
  • Vini Salazar (vinisalazar)

Japanese:

  • Atsushi Sakai (AtsushiSakai)
  • KKunai
  • Tom Kelly (TomKellyGenetics)
  • Yuji Kanagawa (kngwyu)
  • Tetsuo Koyama (tkoyama010)

The work on the translation infrastructure is supported with funding from CZI.

Looking ahead, we’d love to translate the website into more languages. If you’d like to help, please connect with the NumPy Translations Team on Slack: https://join.slack.com/t/numpy-team/shared_invite/zt-1gokbq56s-bvEpo10Ef7aHbVtVFeZv2w. (Look for the #translations channel.) We are also building a Translations Team who will be working on localizing documentation and educational content across the Scientific Python ecosystem. If this piqued your interest, join us on the Scientific Python Discord: https://discord.gg/khWtqY6RKr. (Look for the #translation channel.)

NumPy 1.25.0 released#

Jun 17, 2023 – NumPy 1.25.0 is now available. The highlights of the release are:

  • Support for MUSL, there are now MUSL wheels.
  • Support for the Fujitsu C/C++ compiler.
  • Object arrays are now supported in einsum.
  • Support for the inplace matrix multiplication (@=).

The NumPy 1.25.0 release continues the ongoing work to improve the handling and promotion of dtypes, increase the execution speed, and clarify the documentation. There has also been preparatory work for the future NumPy 2.0.0, resulting in a large number of new and expired deprecations.

A total of 148 people contributed to this release and 530 pull requests were merged.

The Python versions supported by this release are 3.9-3.11.

Fostering an Inclusive Culture: Call for Participation#

May 10, 2023 – Fostering an Inclusive Culture: Call for Participation

How can we be better when it comes to diversity and inclusion? Read the report and find out how to get involved here.

NumPy documentation team leadership transition#

Jan 6, 2023 –- Mukulika Pahari and Ross Barnowski are appointed as the new NumPy documentation team leads replacing Melissa Mendonça. We thank Melissa for all her contributions to the NumPy official documentation and educational materials, and Mukulika and Ross for stepping up.

NumPy 1.24.0 released#

Dec 18, 2022 – NumPy 1.24.0 is now available. The highlights of the release are:

  • New “dtype” and “casting” keywords for stacking functions.
  • New F2PY features and fixes.
  • Many new deprecations, check them out.
  • Many expired deprecations,

The NumPy 1.24.0 release continues the ongoing work to improve the handling and promotion of dtypes, increase execution speed, and clarify the documentation. There are a large number of new and expired deprecations due to changes in dtype promotion and cleanups. It is the work of 177 contributors spread over 444 pull requests. The supported Python versions are 3.8-3.11.

Numpy 1.23.0 released#

Jun 22, 2022 – NumPy 1.23.0 is now available. The highlights of the release are:

  • Implementation of loadtxt in C, greatly improving its performance.
  • Exposure of DLPack at the Python level for easy data exchange.
  • Changes to the promotion and comparisons of structured dtypes.
  • Improvements to f2py.

The NumPy 1.23.0 release continues the ongoing work to improve the handling and promotion of dtypes, increase the execution speed, clarify the documentation, and expire old deprecations. It is the work of 151 contributors spread over 494 pull requests. The Python versions supported by this release 3.8-3.10. Python 3.11 will be supported when it reaches the rc stage.

NumFOCUS DEI research study: call for participation#

Apr 13, 2022 – NumPy is working with NumFOCUS on a research project funded by the Gordon & Betty Moore Foundation to understand the barriers to participation that contributors, particularly those from historically underrepresented groups, face in the open-source software community. The research team would like to talk to new contributors, project developers and maintainers, and those who have contributed in the past about their experiences joining and contributing to NumPy.

Interested in sharing your experiences?

Please complete this brief “Participant Interest” form which contains additional information on the research goals, privacy, and confidentiality considerations. Your participation will be valuable to the growth and sustainability of diverse and inclusive open-source software communities. Accepted participants will participate in a 30-minute interview with a research team member.

Numpy 1.22.0 release#

Dec 31, 2021 – NumPy 1.22.0 is now available. The highlights of the release are:

  • Type annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
  • A preliminary version of the proposed array API Standard is provided (see NEP 47). This is a step in creating a standard collection of functions that can be used across libraries such as CuPy and JAX.
  • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
  • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
  • The universal functions have been refactored to implement most of NEP 43. This also unlocks the ability to experiment with the future DType API.
  • A new configurable memory allocator for use by downstream projects.

NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. The Python versions supported by this release are 3.8-3.10.

Advancing an inclusive culture in the scientific Python ecosystem#

August 31, 2021 – We are happy to announce the Chan Zuckerberg Initiative has awarded a grant to support the onboarding, inclusion, and retention of people from historically marginalized groups on scientific Python projects, and to structurally improve the community dynamics for NumPy, SciPy, Matplotlib, and Pandas.

As a part of CZI’s Essential Open Source Software for Science program, this Diversity & Inclusion supplemental grant will support the creation of dedicated Contributor Experience Lead positions to identify, document, and implement practices to foster inclusive open-source communities. This project will be led by Melissa Mendonça (NumPy), with additional mentorship and guidance provided by Ralf Gommers (NumPy, SciPy), Hannah Aizenman and Thomas Caswell (Matplotlib), Matt Haberland (SciPy), and Joris Van den Bossche (Pandas).

This is an ambitious project aiming to discover and implement activities that should structurally improve the community dynamics of our projects. By establishing these new cross-project roles, we hope to introduce a new collaboration model to the Scientific Python communities, allowing community-building work within the ecosystem to be done more efficiently and with greater outcomes. We also expect to develop a clearer picture of what works and what doesn’t in our projects to engage and retain new contributors, especially from historically underrepresented groups. Finally, we plan on producing detailed reports on the actions executed, explaining how they have impacted our projects in terms of representation and interaction with our communities.

The two-year project is expected to start by November 2021, and we are excited to see the results from this work! You can read the full proposal here.

2021 NumPy survey#

July 12, 2021 – At NumPy, we believe in the power of our community. 1,236 NumPy users from 75 countries participated in our inaugural survey last year. The survey findings gave us a very good understanding of what we should focus on for the next 12 months.

It’s time for another survey, and we are counting on you once again. It will take about 15 minutes of your time. Besides English, the survey questionnaire is available in 8 additional languages: Bangla, French, Hindi, Japanese, Mandarin, Portuguese, Russian, and Spanish.

Follow the link to get started: https://berkeley.qualtrics.com/jfe/form/SV_aaOONjgcBXDSl4q.

Numpy 1.21.0 release#

Jun 23, 2021 – NumPy 1.21.0 is now available. The highlights of the release are:

  • continued SIMD work covering more functions and platforms,
  • initial work on the new dtype infrastructure and casting,
  • universal2 wheels for Python 3.8 and Python 3.9 on Mac,
  • improved documentation,
  • improved annotations,
  • new PCG64DXSM bitgenerator for random numbers.

This NumPy release is the result of 581 merged pull requests contributed by 175 people. The Python versions supported for this release are 3.7-3.9, support for Python 3.10 will be added after Python 3.10 is released.

2020 NumPy survey results#

Jun 22, 2021 – In 2020, the NumPy survey team in partnership with students and faculty from the University of Michigan and the University of Maryland conducted the first official NumPy community survey. Find the survey results here: https://numpy.org/user-survey-2020/.

Numpy 1.20.0 release#

Jan 30, 2021 – NumPy 1.20.0 is now available. This is the largest NumPy release to date, thanks to 180+ contributors. The two most exciting new features are:

  • Type annotations for large parts of NumPy, and a new numpy.typing submodule containing ArrayLike and DtypeLike aliases that users and downstream libraries can use when adding type annotations in their own code.
  • Multi-platform SIMD compiler optimizations, with support for x86 (SSE, AVX), ARM64 (Neon), and PowerPC (VSX) instructions. This yielded significant performance improvements for many functions (examples: sin/cos, einsum).

Diversity in the NumPy project#

Sep 20, 2020 – We wrote a statement on the state of, and discussion on social media around, diversity and inclusion in the NumPy project.

First official NumPy paper published in Nature!#

Sep 16, 2020 – We are pleased to announce the publication of the first official paper on NumPy as a review article in Nature. This comes 14 years after the release of NumPy 1.0. The paper covers applications and fundamental concepts of array programming, the rich scientific Python ecosystem built on top of NumPy, and the recently added array protocols to facilitate interoperability with external array and tensor libraries like CuPy, Dask, and JAX.

Python 3.9 is coming, when will NumPy release binary wheels?#

Sept 14, 2020 – Python 3.9 will be released in a few weeks. If you are an early adopter of Python versions, you may be dissapointed to find that NumPy (and other binary packages like SciPy) will not have binary wheels ready on the day of the release. It is a major effort to adapt the build infrastructure to a new Python version and it typically takes a few weeks for the packages to appear on PyPI and conda-forge. In preparation for this event, please make sure to

  • update your pip to version 20.1 at least to support manylinux2010 and manylinux2014
  • use --only-binary=numpy or --only-binary=:all: to prevent pip from trying to build from source.

Numpy 1.19.2 release#

Sep 10, 2020 – NumPy 1.19.2 is now available. This latest release in the 1.19 series fixes several bugs, prepares for the upcoming Cython 3.x release and pins setuptools to keep distutils working while upstream modifications are ongoing. The aarch64 wheels are built with the latest manylinux2014 release that fixes the problem of differing page sizes used by different linux distros.

The inaugural NumPy survey is live!#

Jul 2, 2020 – This survey is meant to guide and set priorities for decision-making about the development of NumPy as software and as a community. The survey is available in 8 additional languages besides English: Bangla, Hindi, Japanese, Mandarin, Portuguese, Russian, Spanish and French.

Please help us make NumPy better and take the survey here.

Jun 24, 2020 – NumPy now has a new logo:

NumPy logo

The logo is a modern take on the old one, with a cleaner design. Thanks to Isabela Presedo-Floyd for designing the new logo, as well as to Travis Vaught for the old logo that served us well for 15+ years.

NumPy 1.19.0 release#

Jun 20, 2020 – NumPy 1.19.0 is now available. This is the first release without Python 2 support, hence it was a “clean-up release”. The minimum supported Python version is now Python 3.6. An important new feature is that the random number generation infrastructure that was introduced in NumPy 1.17.0 is now accessible from Cython.

Season of Docs acceptance#

May 11, 2020 – NumPy has been accepted as one of the mentor organizations for the Google Season of Docs program. We are excited about the opportunity to work with a technical writer to improve NumPy’s documentation once again! For more details, please see the official Season of Docs site and our ideas page.

NumPy 1.18.0 release#

Dec 22, 2019 – NumPy 1.18.0 is now available. After the major changes in 1.17.0, this is a consolidation release. It is the last minor release that will support Python 3.5. Highlights of the release includes the addition of basic infrastructure for linking with 64-bit BLAS and LAPACK libraries, and a new C-API for numpy.random.

Please see the release notes for more details.

NumPy receives a grant from the Chan Zuckerberg Initiative#

Nov 15, 2019 – We are pleased to announce that NumPy and OpenBLAS, one of NumPy’s key dependencies, have received a joint grant for $195,000 from the Chan Zuckerberg Initiative through their Essential Open Source Software for Science program that supports software maintenance, growth, development, and community engagement for open source tools critical to science.

This grant will be used to ramp up the efforts in improving NumPy documentation, website redesign, and community development to better serve our large and rapidly growing user base, and ensure the long-term sustainability of the project. While the OpenBLAS team will focus on addressing sets of key technical issues, in particular thread-safety, AVX-512, and thread-local storage (TLS) issues, as well as algorithmic improvements in ReLAPACK (Recursive LAPACK) on which OpenBLAS depends.

More details on our proposed initiatives and deliverables can be found in the full grant proposal. The work is scheduled to start on Dec 1st, 2019 and continue for the next 12 months.

Releases#

Here is a list of NumPy releases, with links to release notes. Bugfix releases (only the z changes in the x.y.z version number) have no new features; minor releases (the y increases) do.

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