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144 changes: 67 additions & 77 deletions content/en/news.md
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---
title: News
title: "News Title"
sidebar: false
newsHeader: "NumPy 2.2.0 released!"
date: 2024-12-8
date: 2024-12-30
---

### NumPy 2.2.0 released

_8 Dec, 2024_ -- The NumPy 2.2.0 release is a quick release that brings us back
into sync with the usual twice yearly release cycle. There have been a number
of small cleanups, improvements to the StringDType, and better support for free
threaded Python. Highlights are:
threaded Python. Highlights are:

* New functions ``matvec`` and ``vecmat``,
* Many improved annotations,
* Improved support for the new StringDType,
* Improved support for free threaded Python,
* Fixes for f2py.
- New functions `matvec` and `vecmat`,
- Many improved annotations,
- Improved support for the new StringDType,
- Improved support for free threaded Python,
- Fixes for f2py.

This release supports Python versions 3.10-3.13.


### NumPy 2.1.0 released

_18 Aug, 2024_ -- NumPy 2.1.0 provides support for Python 3.13 and
Expand All @@ -29,20 +28,19 @@ updated Python support, it helps get NumPy back to its usual release
cycle after the extended development of 2.0. The highlights for this
release are:

- Support for Python 3.13.
- Preliminary support for free threaded Python 3.13.
- Support for the array-api 2023.12 standard.
- Support for Python 3.13.
- Preliminary support for free threaded Python 3.13.
- Support for the array-api 2023.12 standard.

Python versions 3.10-3.13 are supported by this release.


### NumPy 2.0.0 released

_16 Jun, 2024_ -- NumPy 2.0.0 is the first major release since 2006. It is the
result of 11 months of development since the last feature release and is the
work of 212 contributors spread over 1078 pull requests. It contains a large
number of exciting new features as well as changes to both the Python and C
APIs. It includes breaking changes that could not happen in a regular minor
APIs. It includes breaking changes that could not happen in a regular minor
release - including an ABI break, changes to type promotion rules, and API
changes which may not have been emitting deprecation warnings in 1.26.x. Key
documents related to how to adapt to changes in NumPy 2.0 include:
Expand All @@ -54,7 +52,6 @@ documents related to how to adapt to changes in NumPy 2.0 include:
The blog post ["NumPy 2.0: an evolutionary milestone"](https://blog.scientific-python.org/numpy/numpy2/)
tells a bit of the story about how this release came together.


### NumPy 2.0 release date: June 16

_23 May, 2024_ -- We are excited to announce that NumPy 2.0 is planned to be
Expand All @@ -69,26 +66,26 @@ works with NumPy `2.0.0rc2`. **Please see the following for more details:**
- The [2.0.0 release notes](https://numpy.org/devdocs/release/2.0.0-notes.html)
- Announcement issue for status updates: [numpy#24300](https://github.com/numpy/numpy/issues/24300)


### 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 
_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](https://numpy.org/doc/stable/release/1.26.0-notes.html)
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
- 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.
Expand All @@ -99,44 +96,46 @@ 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:
_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)

- 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)

- 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
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](https://numpy.org/doc/stable/release/1.25.0-notes.html)
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 (``@=``).
- 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
Expand Down Expand Up @@ -168,10 +167,10 @@ and Mukulika and Ross for stepping up.
_Dec 18, 2022_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html)
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,
- 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.
Expand All @@ -184,10 +183,10 @@ dtype promotion and cleanups. It is the work of 177 contributors spread over
_Jun 22, 2022_ -- [NumPy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html)
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.
- 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,
Expand Down Expand Up @@ -220,24 +219,24 @@ with a research team member.
_Dec 31, 2021_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html)
is now available. The highlights of the release are:

* Type annotations of the main namespace are essentially complete. Upstream is
- 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
- A preliminary version of the proposed
[array API Standard](https://data-apis.org/array-api/latest/) is provided
(see [NEP 47](https://numpy.org/neps/nep-0047-array-api-standard.html)).
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
- 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
- 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
- The universal functions have been refactored to implement most of
[NEP 43](https://numpy.org/neps/nep-0043-extensible-ufuncs.html).
This also unlocks the ability to experiment with the future DType API.
* A new configurable memory allocator for use by downstream projects.
- 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
Expand Down Expand Up @@ -290,7 +289,6 @@ 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](https://numpy.org/doc/stable/release/1.21.0-notes.html)
Expand All @@ -301,26 +299,25 @@ is now available. The highlights of the release are:
- universal2 wheels for Python 3.8 and Python 3.9 on Mac,
- improved documentation,
- improved annotations,
- new ``PCG64DXSM`` bitgenerator for random numbers.
- 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
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](https://numpy.org/doc/stable/release/1.20.0-notes.html)
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.
Expand All @@ -334,7 +331,6 @@ contributors. The two most exciting new features are:

_Sep 20, 2020_ -- We wrote a [statement on the state of, and discussion on social media around, diversity and inclusion in the NumPy project](/diversity_sep2020).


### First official NumPy paper published in Nature!

_Sep 16, 2020_ -- We are pleased to announce the publication of
Expand All @@ -345,7 +341,6 @@ the rich scientific Python ecosystem built on top of NumPy, and the recently add
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
Expand All @@ -354,12 +349,12 @@ early adopter of Python versions, you may be dissapointed to find that NumPy
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`](https://pip.pypa.io/en/stable/reference/pip_install/#cmdoption-only-binary) or `--only-binary=:all:` to prevent `pip` from
trying to build from source.


### Numpy 1.19.2 release

_Sep 10, 2020_ -- [NumPy
Expand All @@ -381,7 +376,6 @@ Bangla, Hindi, Japanese, Mandarin, Portuguese, Russian, Spanish and French.
Please help us make NumPy better and take the survey
[here](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl).


### NumPy has a new logo!

_Jun 24, 2020_ -- NumPy now has a new logo:
Expand All @@ -396,7 +390,6 @@ 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
Expand All @@ -405,7 +398,6 @@ 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
Expand All @@ -415,17 +407,15 @@ details, please see
[the official Season of Docs site](https://developers.google.com/season-of-docs/) and our
[ideas page](https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2020-Project-Ideas).


### 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``.
infrastructure for linking with 64-bit BLAS and LAPACK libraries, and a new C-API for `numpy.random`.

Please see the [release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0) 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](https://chanzuckerberg.com/eoss/) that supports software maintenance, growth, development, and community engagement for open source tools critical to science.
Expand All @@ -434,8 +424,8 @@ This grant will be used to ramp up the efforts in improving NumPy documentation,

More details on our proposed initiatives and deliverables can be found in the [full grant proposal](https://figshare.com/articles/Proposal_NumPy_OpenBLAS_for_Chan_Zuckerberg_Initiative_EOSS_2019_round_1/10302167). The work is scheduled to start on Dec 1st, 2019 and continue for the next 12 months.


<a name="releases"></a>

## Releases

Here is a list of NumPy releases, with links to release notes. Bugfix
Expand Down
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