From e0c7183748aa4c9591faa4787d1e0b84aa6f1782 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:34 +0100 Subject: [PATCH 01/17] New translations news.md (French) --- content/fr/news.md | 322 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 content/fr/news.md diff --git a/content/fr/news.md b/content/fr/news.md new file mode 100644 index 0000000000..7a7aba23fe --- /dev/null +++ b/content/fr/news.md @@ -0,0 +1,322 @@ +--- +title: News +sidebar: false +newsHeader: "NumPy 2.2.0 released!" +date: 2024-12-8 +--- + +### 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: + +* 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 drops support for Python 3.9. In addition to the usual bug fixes and 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. + +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 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: + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) + +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 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:** + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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  + +### 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 + +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](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 (`@=`). + +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](https://contributor-experience.org/docs/posts/dei-report/). + +### 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](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, + +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](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. + +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](http://numfocus.org/) on a [research project](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) funded by the [Gordon & Betty Moore Foundation](https://www.moore.org/) 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](https://numfocus.typeform.com/to/WBWVJSqe) 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](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 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](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 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](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. + +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](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 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](https://chanzuckerberg.com/eoss/), this [Diversity & Inclusion supplemental grant](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 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](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). + +### 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](https://numpy.org/doc/stable/release/1.21.0-notes.html) 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](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. +- 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](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). + +### 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](/diversity_sep2020). + + +### First official NumPy paper published in Nature! + +_Sep 16, 2020_ -- We are pleased to announce the publication of [the first official paper on NumPy](https://www.nature.com/articles/s41586-020-2649-2) 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`](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 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) is now available. This latest release in the 1.19 series fixes several bugs, prepares for the [upcoming Cython 3.x release](http://docs.cython.org/en/latest/src/changes.html) 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](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). + + +### NumPy has a new logo! + +_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](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`. + +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. + +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](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. + + + + +## 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. + +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. +- NumPy 1.26.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 Nov 2023_. +- NumPy 1.26.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 Oct 2023_. +- NumPy 1.26.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 Sep 2023_. +- NumPy 1.25.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 Jul 2023_. +- NumPy 1.25.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 Jul 2023_. +- NumPy 1.24.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 Jun 2023_. +- NumPy 1.25.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 Jun 2023_. +- NumPy 1.24.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 Apr 2023_. +- NumPy 1.24.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 Feb 2023_. +- NumPy 1.24.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 Dec 2022_. +- NumPy 1.24.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 Dec 2022_. +- NumPy 1.23.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _19 Nov 2022_. +- NumPy 1.23.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 Oct 2022_. +- NumPy 1.23.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 Sep 2022_. +- NumPy 1.23.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 Aug 2022_. +- NumPy 1.23.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 Jul 2022_. +- NumPy 1.23.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 Jun 2022_. +- NumPy 1.22.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 May 2022_. +- NumPy 1.21.6 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 Apr 2022_. +- NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. +- NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. +- NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. +- NumPy 1.22.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 Dec 2021_. +- NumPy 1.21.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 Dec 2021_. +- NumPy 1.21.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 Jun 2021_. +- NumPy 1.20.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 May 2021_. +- NumPy 1.20.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 Jan 2021_. +- NumPy 1.19.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 Jan 2021_. +- NumPy 1.19.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 Jun 2020_. +- NumPy 1.18.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 May 2020_. +- NumPy 1.17.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 Jan 2020_. +- NumPy 1.18.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 Dec 2019_. +- NumPy 1.17.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 Jul 2019_. +- NumPy 1.16.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. +- NumPy 1.15.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 Jul 2018_. +- NumPy 1.14.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 Jan 2018_. From 09a27a3d3e2748b729a4d43dc1d259a69311494f Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:36 +0100 Subject: [PATCH 02/17] New translations news.md (Spanish) --- content/es/news.md | 24 ++++++++++++++++++++---- 1 file changed, 20 insertions(+), 4 deletions(-) diff --git a/content/es/news.md b/content/es/news.md index 1e34cd9fcf..209ea5b9da 100644 --- a/content/es/news.md +++ b/content/es/news.md @@ -5,6 +5,19 @@ newsHeader: "¡NumPy 2.0 ha sido lanzado!" date: 2024-06-17 --- +### 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: + +* 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. + + ### Lanzamiento de NumPy 2.1.0 _18 de agosto 2024_ -- NumPy 2.1.0 provides support for Python 3.13 and drops support for Python 3.9. Además de las habituales correcciones de errores y soporte actualizado de Python, ayuda a que NumPy vuelva a su ciclo de publicación habitual después del extenso desarrollo de 2.0. Los aspectos más destacados son: @@ -20,8 +33,8 @@ Esta versión es compatible con las versiones 3.10-3.13 de Python. _16 de junio de 2024_ -- NumPy 2.0.0 es el primer lanzamiento importante desde 2006. Es el resultado de 11 meses de desarrollo desde el último lanzamiento de características y es el trabajo de 212 colaboradores distribuidos entre 1078 solicitudes de incorporación de cambios. Contiene un gran número de nuevas características interesantes, así como cambios en las APIs de Python y C. Incluye cambios importantes que no podrían producirse en un lanzamiento menor regular, como una ruptura de ABI, cambios en las reglas de promoción de tipos y cambios en la API que podrían no haber estado emitiendo advertencias de obsolescencia en la versión 1.26.x. Los documentos clave relacionados con cómo adaptarse a los cambios en NumPy 2.0 incluyen: -- La [Guía de migración de NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- Las [notas de lanzamiento 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) +- La [guía de migración a NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- Las [ notas del lanzamiento 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) - Emisión de anuncios para actualizaciones de estado: [numpy#24300](https://github.com/numpy/numpy/issues/24300) La publicación ["NumPy 2.0: an evolutionary milestone"](https://blog.scientific-python.org/numpy/numpy2/) cuenta un poco de la historia sobre cómo se llegó a este lanzamiento. @@ -31,8 +44,8 @@ La publicación ["NumPy 2.0: an evolutionary milestone"](https://blog.scientific _23 de mayo de 2024_ -- Estamos encantados de anunciar que NumPy 2.0 está previsto que sea lanzado el 16 de junio de 2024. Esta publicación lleva más de un año en proceso y es el primer lanzamiento importante desde 2006. Es importante destacar que, además de muchas nuevas características y mejoras en el rendimiento, contiene **cambios disruptivos** frente al ABI, como también a las APIs de Python y C. Es probable que los paquetes dependientes o downstream y código de usuario final necesiten ser adaptados - si puedes, por favor verifica que tu código funciona con NumPy `2.0.0rc2`. **Por favor, revisa lo siguiente para más detalles:** -- La [guía de migración a NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- Las [ notas del lanzamiento 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) +- La [Guía de migración de NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- Las [notas de lanzamiento 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) - Emisión de anuncios para actualizaciones de estado: [numpy#24300](https://github.com/numpy/numpy/issues/24300) @@ -261,6 +274,9 @@ Puede encontrar más detalles sobre nuestras iniciativas y entregables propuesto Esta es una lista de lanzamientos NumPy, con enlaces a notas de lanzamiento. Los lanzamientos de corrección de errores (solo cambia la `z` en el número de versión `x.y.z`) no tienen nuevas características; las versiones menores (aumenta la `y`) sí las tienen. +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. - NumPy 2.1.1 ([notas de lanzamiento](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 de septiembre 2024_. - NumPy 2.0.2 ([notas de lanzamiento](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 de agosto 2024_. - NumPy 2.1.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 de agosto de 2024_. From d78fbfb66a3a50e81accefecc83db2abe3018363 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:37 +0100 Subject: [PATCH 03/17] New translations news.md (Arabic) --- content/ar/news.md | 322 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 content/ar/news.md diff --git a/content/ar/news.md b/content/ar/news.md new file mode 100644 index 0000000000..08bd83d7f0 --- /dev/null +++ b/content/ar/news.md @@ -0,0 +1,322 @@ +--- +title: الأخبار +sidebar: false +newsHeader: "NumPy 2.2.0 released!" +date: 2024-12-8 +--- + +### 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: + +* 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 drops support for Python 3.9. In addition to the usual bug fixes and 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. + +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 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: + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) + +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 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:** + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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  + +### 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 + +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](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 (`@=`). + +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](https://contributor-experience.org/docs/posts/dei-report/). + +### 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](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, + +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](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. + +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](http://numfocus.org/) on a [research project](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) funded by the [Gordon & Betty Moore Foundation](https://www.moore.org/) 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](https://numfocus.typeform.com/to/WBWVJSqe) 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](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 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](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 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](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. + +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](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 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](https://chanzuckerberg.com/eoss/), this [Diversity & Inclusion supplemental grant](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 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](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). + +### 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](https://numpy.org/doc/stable/release/1.21.0-notes.html) 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](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. +- 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](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). + +### 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](/diversity_sep2020). + + +### First official NumPy paper published in Nature! + +_Sep 16, 2020_ -- We are pleased to announce the publication of [the first official paper on NumPy](https://www.nature.com/articles/s41586-020-2649-2) 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`](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 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) is now available. This latest release in the 1.19 series fixes several bugs, prepares for the [upcoming Cython 3.x release](http://docs.cython.org/en/latest/src/changes.html) 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](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). + + +### NumPy has a new logo! + +_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](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`. + +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. + +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](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. + + + + +## الإصدارات + +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. + +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. +- NumPy 1.26.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 Nov 2023_. +- NumPy 1.26.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 Oct 2023_. +- NumPy 1.26.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 Sep 2023_. +- NumPy 1.25.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 Jul 2023_. +- NumPy 1.25.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 Jul 2023_. +- NumPy 1.24.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 Jun 2023_. +- NumPy 1.25.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 Jun 2023_. +- NumPy 1.24.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 Apr 2023_. +- NumPy 1.24.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 Feb 2023_. +- NumPy 1.24.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 Dec 2022_. +- NumPy 1.24.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 Dec 2022_. +- NumPy 1.23.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _19 Nov 2022_. +- NumPy 1.23.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 Oct 2022_. +- NumPy 1.23.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 Sep 2022_. +- NumPy 1.23.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 Aug 2022_. +- NumPy 1.23.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 Jul 2022_. +- NumPy 1.23.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 Jun 2022_. +- NumPy 1.22.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 May 2022_. +- NumPy 1.21.6 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 Apr 2022_. +- NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. +- NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. +- NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. +- NumPy 1.22.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 Dec 2021_. +- NumPy 1.21.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 Dec 2021_. +- NumPy 1.21.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 Jun 2021_. +- NumPy 1.20.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 May 2021_. +- NumPy 1.20.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 Jan 2021_. +- NumPy 1.19.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 Jan 2021_. +- NumPy 1.19.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 Jun 2020_. +- NumPy 1.18.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 May 2020_. +- NumPy 1.17.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 Jan 2020_. +- NumPy 1.18.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 Dec 2019_. +- NumPy 1.17.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 Jul 2019_. +- NumPy 1.16.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. +- NumPy 1.15.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 Jul 2018_. +- NumPy 1.14.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 Jan 2018_. From 5d193cdd52d6fb6cf42ec11830573be78db77b06 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:38 +0100 Subject: [PATCH 04/17] New translations news.md (Catalan) --- content/ca/news.md | 322 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 content/ca/news.md diff --git a/content/ca/news.md b/content/ca/news.md new file mode 100644 index 0000000000..7a7aba23fe --- /dev/null +++ b/content/ca/news.md @@ -0,0 +1,322 @@ +--- +title: News +sidebar: false +newsHeader: "NumPy 2.2.0 released!" +date: 2024-12-8 +--- + +### 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: + +* 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 drops support for Python 3.9. In addition to the usual bug fixes and 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. + +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 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: + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) + +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 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:** + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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  + +### 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 + +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](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 (`@=`). + +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](https://contributor-experience.org/docs/posts/dei-report/). + +### 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](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, + +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](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. + +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](http://numfocus.org/) on a [research project](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) funded by the [Gordon & Betty Moore Foundation](https://www.moore.org/) 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](https://numfocus.typeform.com/to/WBWVJSqe) 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](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 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](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 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](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. + +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](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 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](https://chanzuckerberg.com/eoss/), this [Diversity & Inclusion supplemental grant](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 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](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). + +### 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](https://numpy.org/doc/stable/release/1.21.0-notes.html) 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](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. +- 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](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). + +### 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](/diversity_sep2020). + + +### First official NumPy paper published in Nature! + +_Sep 16, 2020_ -- We are pleased to announce the publication of [the first official paper on NumPy](https://www.nature.com/articles/s41586-020-2649-2) 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`](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 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) is now available. This latest release in the 1.19 series fixes several bugs, prepares for the [upcoming Cython 3.x release](http://docs.cython.org/en/latest/src/changes.html) 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](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). + + +### NumPy has a new logo! + +_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](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`. + +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. + +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](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. + + + + +## 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. + +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. +- NumPy 1.26.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 Nov 2023_. +- NumPy 1.26.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 Oct 2023_. +- NumPy 1.26.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 Sep 2023_. +- NumPy 1.25.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 Jul 2023_. +- NumPy 1.25.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 Jul 2023_. +- NumPy 1.24.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 Jun 2023_. +- NumPy 1.25.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 Jun 2023_. +- NumPy 1.24.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 Apr 2023_. +- NumPy 1.24.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 Feb 2023_. +- NumPy 1.24.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 Dec 2022_. +- NumPy 1.24.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 Dec 2022_. +- NumPy 1.23.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _19 Nov 2022_. +- NumPy 1.23.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 Oct 2022_. +- NumPy 1.23.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 Sep 2022_. +- NumPy 1.23.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 Aug 2022_. +- NumPy 1.23.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 Jul 2022_. +- NumPy 1.23.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 Jun 2022_. +- NumPy 1.22.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 May 2022_. +- NumPy 1.21.6 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 Apr 2022_. +- NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. +- NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. +- NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. +- NumPy 1.22.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 Dec 2021_. +- NumPy 1.21.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 Dec 2021_. +- NumPy 1.21.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 Jun 2021_. +- NumPy 1.20.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 May 2021_. +- NumPy 1.20.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 Jan 2021_. +- NumPy 1.19.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 Jan 2021_. +- NumPy 1.19.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 Jun 2020_. +- NumPy 1.18.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 May 2020_. +- NumPy 1.17.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 Jan 2020_. +- NumPy 1.18.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 Dec 2019_. +- NumPy 1.17.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 Jul 2019_. +- NumPy 1.16.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. +- NumPy 1.15.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 Jul 2018_. +- NumPy 1.14.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 Jan 2018_. From c2bb0e7b394a3ba40c92cdee46d2c2ec65607449 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:39 +0100 Subject: [PATCH 05/17] New translations news.md (Japanese) --- content/ja/news.md | 28 +++++++++++++++++++++------- 1 file changed, 21 insertions(+), 7 deletions(-) diff --git a/content/ja/news.md b/content/ja/news.md index 33c10a9546..acd02d628f 100644 --- a/content/ja/news.md +++ b/content/ja/news.md @@ -2,9 +2,22 @@ title: ニュース sidebar: false newsHeader: "NumPy 1.26.0 がリリースされました。" -date: 2024-08-18 +date: 2023-09-16 --- +### 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: + +* 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 1.26.0 がリリースされました。 _2024 Aug, 2024_ -- Numpy 2.1.0 は Python 3.13 をサポートし、Python 3.9をサポート外としました。 今回のリリースは通常のバグ修正やPythonサポートの更新に加えて、NumPyが2.0の長期開発を経て、通常のリリースサイクルに戻るためのリリースでもあります。 今回のリリースのハイライトは下記の通りです。 @@ -13,7 +26,7 @@ _2024 Aug, 2024_ -- Numpy 2.1.0 は Python 3.13 をサポートし、Python 3.9 - 多くの期限切れの非推奨(Deprecation)の削除 - Array-api 2023.12 標準のサポート -このリリースでは、Pythonのバージョン 3.10-3.13 がサポートされています。 +Python バージョン 3.10-3.13 か、このリリースでサポートされています。 ### 多くの新しい非推奨(Deprecation)の追加 @@ -21,8 +34,8 @@ _2024 Aug, 2024_ -- Numpy 2.1.0 は Python 3.13 をサポートし、Python 3.9 _2024年6月16日_ -- Numpy 2.0.0 は2006年以来のメジャーリリースです。 これは、前回の機能リリースから11か月間の開発の成果であり、1078件のプルリクエストにわたる212人の貢献者の成果となります。 このリリースには、大きく、エキサイティングな新機能と、PythonとCの両方のAPIへの変更が含まれています。 今回のリリースが、通常のマイナーリリースでは実施できなかった互換性を破壊する変更を含んでいます。これには、ABIの破壊、型昇格ルールの変更、および1.26.xでは非推奨警告が出されていなかった可能性のあるAPIの変更が含まれています。 NumPy 2.0の変更に対応する方法に関する主要なドキュメントは次のとおりです。 - [NumPy 2.0移行ガイド](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- [2.0.0 リリース ノート](https://numpy.org/devdocs/release/2.0.0-notes.html) -- ステータスアップデートお知らせに関する問題: [numpy#24300](https://github.com/numpy/numpy/issues/24300) +- [2.0.0 リリースノート](https://numpy.org/devdocs/release/2.0.0-notes.html) +- ステータス更新のお知らせイシューチケット: [numpy#24300](https://github.com/numpy/numpy/issues/24300) ブログ記事 ["NumPy 2.0: 進化のマイルストーン"](https://blog.scientific-python.org/numpy/numpy2/) は、今回のメジャーバージョンリリースがどのようにして決定されたかについてのストーリーを少し伝えています。 @@ -32,8 +45,8 @@ _2024年6月16日_ -- Numpy 2.0.0 は2006年以来のメジャーリリースで _ 2024年5月23日_ -- NumPy 2.0が2024年6月16日にリリースされる予定になりました！ このリリースは1年以上かけて我々が準備してきたもので、2006年以来のメジャーリリースとなります。 このリリースで重要なことは、多くの新機能とパフォーマンスの向上に加えて、 このリリースは、 **破壊的な変更** である Python と C API を含む、ABI への変更 が含まれています。 NumPyに依存しているパッケージやエンドユーザーのコードがこのは破壊的変更に適応する必要がある可能性があります。可能であれば、あなたのコードがNumPy `2.0.0rc2`で動作するかどうか確認をお願いします。 **詳細は下記をご覧ください:** - [NumPy 2.0移行ガイド](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- [2.0.0 リリースノート](https://numpy.org/devdocs/release/2.0.0-notes.html) -- ステータス更新のお知らせイシューチケット: [numpy#24300](https://github.com/numpy/numpy/issues/24300) +- [2.0.0 リリース ノート](https://numpy.org/devdocs/release/2.0.0-notes.html) +- ステータスアップデートお知らせに関する問題: [numpy#24300](https://github.com/numpy/numpy/issues/24300) ### NumFOCUSの年末の資金調達 @@ -261,7 +274,8 @@ _2019年11月15日_ -- NumPyと、NumPyの重要な依存ライブラリの1つ こちらは、より以前のNumPyリリースのリストで、各リリースノートへのリンクが記載されています。 全てのバグフィックスリリース(バージョン番号`x.y.z` の`z`だけが変更されたもの)は新しい機能追加はされず、マイナーリリース (`y` が増えたもの)は、新しい機能追加されています。 -- NumPy 2.1.3 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2024年11月2日_. +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. - NumPy 2.1.2 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _2024年10月5日_. - NumPy 2.1.1 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _2024年9月3日_. - NumPy 2.0.2 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _2024年8月26日_. From 3d11a5d0e474a90afd105ef181c181cf1775bf4c Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:41 +0100 Subject: [PATCH 06/17] New translations news.md (Korean) --- content/ko/news.md | 322 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 content/ko/news.md diff --git a/content/ko/news.md b/content/ko/news.md new file mode 100644 index 0000000000..4fb6664900 --- /dev/null +++ b/content/ko/news.md @@ -0,0 +1,322 @@ +--- +title: 소식 +sidebar: false +newsHeader: "NumPy 2.2.0 released!" +date: 2023-09-16 +--- + +### 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: + +* 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 drops support for Python 3.9. In addition to the usual bug fixes and 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. + +Python versions 3.10-3.13 are supported by this release. + + +### NumPy 2.0 출시일: 6월 16일 + +_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 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: + +- [NumPy 2.0 이주 가이드](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- [2.0.0 릴리즈 노트](https://numpy.org/devdocs/release/2.0.0-notes.html) +- 상태 업데이트 공지용 이슈: [numpy#24300](https://github.com/numpy/numpy/issues/24300) + +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 출시일: 6월 16일 + +_2024년 5월 23일_ -- NumPy 2.0이 2024년 6월 16일에 출시할 예정이라는 소식을 발표하게 되어 기쁩니다. 이 릴리즈를 제작하는 데 1년이 넘게 걸렸고, 2006년 이후 첫 번째 메인 릴리즈입니다. 중요한 건 많은 기능과 성능 개선 외에도, ABI와 Python, C API에 대한 **획기적인 변화**를 이뤄냈다는 것입니다. 아마 의존하는 패키지와 최종 사용자의 코드를 수정해야 할 겁니다. 가능하다면 코드가 `2.0.0rc2`에서 잘 작동하는지 검증해 주세요. **자세한 내용은 아래 항목들을 확인해 주세요.** + +- [NumPy 2.0 이주 가이드](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- [2.0.0 릴리즈 노트](https://numpy.org/devdocs/release/2.0.0-notes.html) +- 상태 업데이트 공지용 이슈: [numpy#24300](https://github.com/numpy/numpy/issues/24300) + + +### NumPy 1.26.0 출시 +_2023년 12월 19_ -- NumFOCUS에서 연말 캠페인 기간 동안 PyCharm과 협력해 최초 PyCharm 이용자의 라이선스를 30% 할인된 가격에 제공했습니다. 지금부터 2023년 12월 23일까지 PyCharm 구매로 발생한 모든 수익은 NumFOCUS 프로그램으로 직접 전달됩니다. + +구매를 추적할 수 있는 고유 URL을 이용하거나: https://lp.jetbrains.com/support-data-science/ 쿠폰 코드를 사용하세요: ISUPPORTDATASCIENCE  + +### NumPy 1.26.0 출시 + +_2023년 12월 16일_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html)이 출시되었습니다. 주요 기능들은 다음과 같습니다: + +* 파이썬 3.12.0 지원 +* Cython 3.0.0 호환 +* Meson 빌드 시스템 사용 +* 업데이트된 SIMD 지원 +* f2py 수정, meson 및 bind(x) 지원 +* 업데이트된 Accelerate BLAS/LAPACK 라이브러리 지원 + +NumPy 1.26.0 릴리스는 Meson 빌드 시스템으로의 전환과 Cython 3.0.0 지원을 표시하는 1.25.x 시리즈의 연장입니다. 총 20명의 사람들이 이 릴리스에 기여하였으며 59개의 풀 리퀘스트가 병합되었습니다. + +본 릴리즈에서 지원하는 Python 버전은 3.3.9-3.12입니다. + +### numpy.org은 이제 일본어와 포르투갈어로도 이용 가능합니다. + +_2023년 8월 2일_ - numpy.org은 이제 추가로 일본어와 포르투갈어로 이용 가능합니다. 이는 다음의 헌신적인 자원봉사자들의 노력 없이는 가능하지 않았을 것입니다: + +_포르투갈어_ +* 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) + +_일본어_ +* Atsushi Sakai (AtsushiSakai) +* KKunai +* Tom Kelly (TomKellyGenetics) +* Yuji Kanagawa (kngwyu) +* Tetsuo Koyama (tkoyama010) + +번역 인프라에 대한 작업은 CZI로부터의 자금 지원을 받아 진행되었습니다. + +나아가서 NumPy 웹사이트가 더 많은 언어로 번역되기를 바랍니다. 도움을 주시려면 다음 Slack 링크를 통해 NumPy Translations Team 에 연락을 주십시오: https://join.slack.com/t/numpy-team/shared_invite/zt-1gokbq56s-bvEpo10Ef7aHbVtVFeZv2w. (#translations 채널을 add 해주세요) 또한 과학적 파이썬 생태계 전반에서 문서 및 교육 콘텐츠를 지역화하는데 참여할 Translations Team을 구축하고 있습니다. 이에 흥미를 느낀다면 Scientific Python Discord에서 함께해 주세요: https://discord.gg/khWtqY6RKr. (#translation 채널을 찾아보세요) + +### NumPy 1.25.0 출시 + +_2023년 6월 17일_ -- 이제 [NumPy 1.25.0](https://numpy.org/doc/stable/release/1.25.0-notes.html)을 이용할 수 있습니다. 주요 기능들은 다음과 같습니다: + +* MUSL 지원, 이제 MUSL Wheel도 배포됩니다. +* Fujitsu C/C++ 컴파일러 지원 +* Einsum에서 객체 배열 지원 +* Inplace 행렬 곱셈 (`@=`) 지원 + +NumPy 1.25.0 릴리스에서는 dtype의 처리 및 형변환을 개선하고 실행 속도를 높이는 작업, 문서를 보다 명료하게 다듬는 작업을 계속하고 있습니다. 미래의 NumPy 2.0.0을 위한 준비 작업도 있었는데, 이로 인해 수많은 기능들이 지원 종료 예정에 새로 포함되거나 완전히 만료되었습니다. + +총 148명의 사람들이 이 릴리스에 기여하였으며 530개의 풀 리퀘스트가 병합되었습니다. + +본 릴리즈에서 지원하는 Python 버전은 3.9-3.11입니다. + +### 포용적인 문화 조성: 참여 요청 + +_2023년 5월 10일_ -- 포용적인 문화 조성: 참여 요청 + +다양성과 포용성의 측면에서 우리는 어떻게 더 나아질 수 있을까요? [여기](https://contributor-experience.org/docs/posts/dei-report/)에서 보고서를 읽고 함께 참여하는 방법을 알아보세요. + +### NumPy 문서 팀 리더 변경 + +_2023년 1월 6일_ –- Mukulika Pahari, Ross Barnowski가 Melissa Mendonça를 대신해 새 NumPy 문서 팀 리더로 임명되었습니다. NumPy 공식 문서와 교육 자료에 기여한 Melissa와 한 걸음 더 나아간 Mukulika, Ross에게 감사를 표합니다. + +### NumPy 1.24.0 출시 + +_2022년 12월 18일_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html)이 출시되었습니다. 주요 기능들은 다음과 같습니다: + +* 스태킹 함수를 위한 새 "dtype" 및 "casting" 키워드. +* 새 F2PY 기능 및 수정. +* 수많은 지원 종료 예정 기능, 확인하세요. +* 수많은 만료된 기능, + +NumPy 1.24.0 릴리스에서는 dtype의 처리 및 형변환을 개선하고 실행 속도를 높이는 작업, 문서를 보다 명료하게 다듬는 작업을 계속하고 있습니다. dtype의 형변환 및 정리를 변경하는 과정에서 수많은 기능들이 지원 종료 예정에 새로 포함되거나 완전히 만료되었습니다. 177명의 기여자가 생성한 444개의 풀 요청을 바탕으로 한 성과입니다. 지원하는 Python 버전은 3.8-3.11입니다. + +### NumPy 1.23.0 출시 + +_2022년 6월 22일_ -- [NumPy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html)이 출시되었습니다. 주요 기능들은 다음과 같습니다: + +* `loadtxt`를 C로 구현하여 성능이 크게 향상되었습니다. +* 데이터 교환을 쉽게 하기 위해 Python 수준에서 DLPack을 개방합니다. +* 구조화된 dtype의 형변환 및 비교 방법을 변경했습니다. +* f2py를 개선했습니다. + +NumPy 1.23.0 릴리스에서는 dtype의 처리 및 형변환을 개선하고 실행 속도를 높이는 작업, 문서를 보다 명료하게 다듬는 작업, 오래된 지원 종료 예정 기능을 완전히 만료시키는 작업을 계속하고 있습니다. 151명의 기여자가 생성한 494개의 풀 요청을 바탕으로 한 성과입니다. 본 릴리즈에서 지원하는 Python 버전은 3.8-3.10입니다. Python 3.11은 rc 단계에 다다르면 지원할 예정입니다. + +### NumFOCUS DEI 연구: 참여 요청 + +_2022년 4월 13일_ -- NumPy는 [NumFOCUS](http://numfocus.org/)와 협력하여 [Gordon & Betty Moore 재단](https://www.moore.org/)에서 기금을 제공하는 [연구 프로젝트](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c)를 진행합니다. 본 연구는 오픈 소스 소프트웨어 커뮤니티에 기여자, 특히 역사적으로 과소평가된 집단의 기여자가 참여할 때 직면하는 장벽을 이해하는 것을 목표로 합니다. 연구팀은 새 기여자, 프로젝트 개발자 및 유지관리자, 과거에 기여한 사람들과 NumPy에 참여하고 기여한 경험에 대해 이야기하고자 합니다. + +**경험을 공유하고 싶으신가요?** + +간단한 ["참여 희망" 양식](https://numfocus.typeform.com/to/WBWVJSqe)을 작성해주세요. 양식에서 연구 목표, 개인정보 보호, 기밀 유지 사항에 대한 추가 정보를 확인할 수 있습니다. 당신의 참여가 다양성과 포용성을 갖춘 오픈 소스 소프트웨어 커뮤니티의 성장과 지속 가능성에 도움이 될 것입니다. 승인된 참가자는 연구팀과 30분 면담을 진행하게 됩니다. + +### Numpy 1.22.0 출시 + +_2021년 12월 31일_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html)이 출시되었습니다. 주요 기능들은 다음과 같습니다: + +* 기본 네임스페이스에 대해 유형 주석의 지원을 거의 완료했습니다. 업스트림 코드는 항상 변하므로 추가 개선이 있을 수 있지만 주요 작업은 완료되었습니다. 아마도 이 릴리스에서 가장 체감되는 개선 사항일 것입니다. +* 제안된 [배열 API 표준의 예비 버전](https://data-apis.org/array-api/latest/)이 제공됩니다([NEP 47](https://numpy.org/neps/nep-0047-array-api-standard.html) 참조). 이는 CuPy 및 JAX와 같은 라이브러리에서 사용할 수 있는 표준 함수 모음을 만드는 단계입니다. +* NumPy가 DLPack 백엔드로 구동됩니다. DLPack은 배열(텐서) 데이터에 대한 공통 교환 형식을 제공합니다. +* `quantile`, `percentile` 관련 함수를 위한 새 메서드를 추가했습니다. 새 메서드를 이용해 문헌에서 일반적으로 쓰이는 처리를 진행할 수 있습니다. +* 범용 함수가 대부분의 [NEP 43](https://numpy.org/neps/nep-0043-extensible-ufuncs.html)을 구현하도록 리팩터링되었습니다. 이를 통해 미래의 DType API를 실험할 수 있는 능력도 갖췄습니다. +* 새 구성 가능한 메모리 할당자를 다운스트림 프로젝트에서 사용할 수 있습니다. + +NumPy 1.22.0은 153명의 기여자가 생성한 609개의 풀 요청을 바탕으로 만들어진 대형 릴리즈입니다. 본 릴리즈에서 지원하는 Python 버전은 3.8-3.10입니다. + +### 과학 Python 생태계에서 포용적 문화 발전 + +_2021년 8월 31일_ -- Chan Zuckerberg Initiative가 과학적 Python 프로젝트에서 역사적으로 소외된 그룹의 사람들을 온보딩, 포함 및 유지하고 NumPy, SciPy, Matplotlib 그리고 Pandas 의 커뮤니티 역학을 구조적으로 개선하기 위한 [보조금을 수여](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/)했음을 발표하게 되어 기쁩니다. + +[CZI의 Essential Open Source Software for Science 프로그램](https://chanzuckerberg.com/eoss/)의 일환으로 이 [Diversity & 포함 추가 보조금](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b)은 포괄적인 오픈 소스 커뮤니티를 육성하기 위한 관행을 식별, 문서화 및 구현하기 위한 전담 기여자 경험 리드 직책 생성을 지원합니다. 이 프로젝트는 Melissa Mendonça(NumPy) 님이 이끌고 Ralf Gommers(NumPy, SciPy), Hannah Aizenman, Thomas Caswell(Matplotlib), Matt Haberland(SciPy), Joris Van den Bossche(Pandas) 님이 추가 멘토링 및 지침을 제공합니다. + +이것은 프로젝트의 커뮤니티 역학을 구조적으로 개선해야 하는 활동을 발견하고 구현하는 것을 목표로 하는 야심 찬 프로젝트입니다. 새로운 교차 프로젝트 역할을 설정함으로써 과학적 Python 커뮤니티에 새로운 협업 모델을 도입하여 생태계 내에서 커뮤니티 구축 작업을 보다 효율적으로 수행하고 더 큰 결과를 얻을 수 있을 것으로 기대됩니다. 또한 특히 역사적으로 과소대표된 집단의 새로운 기여자를 참여시키고 유지하기 위해, 프로젝트에서 효과적인 것과 그렇지 않은 것에 대한 명확한 그림을 구축할 것으로 기대합니다. 마지막으로, 시행된 조치에 대해 자세한 보고서를 작성하여 커뮤니티와의 대표 및 상호 작용 측면에서 프로젝트에 어떤 영향을 미쳤는지 설명할 계획입니다. + +2개년 프로젝트가 2021년 11월부터 시작될 예정입니다. 프로젝트의 결과를 볼 날이 기대되네요! [여기에서 전체 제안서를 열람할 수 있습니다](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). + +### 2021년도 NumPy 설문조사 + +_2021년 7월 12일_ -- NumPy에서, 우리는 커뮤니티의 힘을 믿습니다. 작년에 75개국에서 1,236명의 NumPy 사용자가 첫 번째 설문조사에 참여했습니다. 설문 조사 결과를 통해 다음 12개월 동안 우리가 어떤 것에 집중해야 할지 아주 잘 이해할 수 있었습니다. + +이제 또다른 설문 조사를 진행할 시간이고, 여러분의 도움이 다시 한 번 필요합니다. 완료하는 데 약 15분 정도 소요될 겁니다. 설문지는 영어 외에도 8개 국어로 제공됩니다: 벵골어, 프랑스어, 힌디어, 일본어, 중국 관화, 포르투갈어, 러시아어, 스페인어. + +시작하려면 아래 링크를 눌러 주세요: https://berkeley.qualtrics.com/jfe/form/SV_aaOONjgcBXDSl4q. + + +### Numpy 1.21.0 출시 + +_2021년 9월 23일_ -- [NumPy 1.1.21](https://numpy.org/doc/stable/release/1.21.0-notes.html)이 출시되었습니다. 주요 기능들은 다음과 같습니다: + +- 더 많은 기능과 플랫폼을 다루는 지속적인 SIMD 작업, +- 새로운 dtype 인프라 및 캐스팅에 대한 초기 작업, +- Mac의 Python 3.8 및 Python 3.9용 universal2 휠, +- 문서화 향상, +- 주석 향상, +- 난수 생성에 이용되는 새 `PCG64DXSM` 비트 생성기. + +이번 NumPy 릴리즈는 175명이 기여해주신 581개의 풀 리퀘스트가 합쳐진 결과입니다. 본 릴리즈에서 지원하는 Python 버전은 3.7-3.9입니다. Python 3.10은 Python 3.10 릴리즈 이후 지원할 예정입니다. + + +### 2020년도 NumPy 설문조사 결과 + +_2021년 6월 22일_ -- 2020년에, NumPy 조사 팀은 조사방법론 학사 과정의 학생 및 교수와 협력하여 미시간 대학과 매릴렌드 대학이 공동으로 개최한 첫 공식 NumPy 커뮤니티 조사를 실시했습니다. 여기서 조사 결과를 확인하세요: https://numpy.org/user-survey-2020/. + + +### Numpy 1.20.0 출시 + +_2021년 9월 30일_ -- [NumPy 1.1.20](https://numpy.org/doc/stable/release/1.20.0-notes.html)이 출시되었습니다. 역대 최대의 NumPy 릴리즈입니다. 180명이 넘는 기여자분들께 감사드립니다. 다음은 이번 출시에서 가장 흥미로운 두가지 기능들 입니다. +- NumPy의 많은 부분에 대한 유형 주석 및 사용자와 다운스트림 라이브러리가 추가할 때 사용할 수 있는 `ArrayLike` 및 `DtypeLike` 별칭을 포함하는 새로운 `numpy.typing` 하위 모듈 자체 코드에 주석을 입력합니다. +- x86(SSE, AVX), ARM64(Neon) 및 PowerPC(VSX) 명령을 지원하는 다중 플랫폼 SIMD 컴파일러 최적화 입니다. 이는 많은 함수들의 상당한 성능향상을 가져왔습니다 (예: [sin/cos](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). + +### NumPy 프로젝트 내 다양성 + +_2020년 9월 20일_ -- 우리는 [NumPy 프로젝트 안에서의 다양성과 포용성에 관한 소셜 미디어의 상태 및 토론에 대한 성명서를 작성했습니다](/diversity_sep2020). + + +### Nature에 첫 공식 NumPy 논문 발표! + +_2020년 9월 16일_ -- [NumPy에 대한 첫 번째 공식 논문](https://www.nature.com/articles/s41586-020-2649-2)이 Nature에 리뷰 기사로 게재되었음을 발표하게 되어 기쁩니다. NumPy 1.0이 나온 지 14년 만입니다. 이 백서에서는 배열 프로그래밍의 응용 프로그램 및 기본 개념, NumPy 위에 구축된 풍부한 과학적 Python 생태계, CuPy, Dask 및 JAX와 같은 외부 배열 및 텐서 라이브러리와의 상호 운용성을 촉진하기 위해 최근에 추가된 배열 프로토콜을 다룹니다. + + +### Python 3.9가 곧 출시하는데, NumPy는 바이너리 Wheel을 언제 출시합니까? + +_2020년 9월 14일_ -- Python 3.9가 몇 주 내로 출시될 것입니다. 만약 Python 얼리어답터라면, NumPy (그리고 SciPy 등 다른 바이너리 패키지) 가 릴리즈 시일에 바이너리 Wheel을 준비하지 못한다는 것을 알고 실망했을 수 있습니다. 새로운 Python 버전에 빌드 환경을 맞추는 것은 많은 노력을 요하고, 패키지가 PyPI 및 conda-forge에 배포되는 데에는 일반적으로 몇 주가 걸립니다. 출시를 대비하려면 아래 요건을 충족하도록 하십시오. +- `pip` 버전을 최소 20.1로 업데이트하여 `manylinux2010` 및 `manylinux2014`를 지원하도록 합니다 +- [`--only-binary=numpy`](https://pip.pypa.io/en/stable/reference/pip_install/#cmdoption-only-binary)를 사용하거나 또는 `--only-binary=:all:`을 사용하여 `pip`가 소스에서 빌드하는 것을 막아주세요. + + +### NumPy 1.19.2 출시 + +_2020년 9월 10일_ -- [NumPy 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html)이 출시되었습니다. 1.19 시리즈의 이 최신 릴리스는 몇 가지 버그를 수정하고 [다가오는 Cython 3.x 릴리스](http://docs.cython.org/en/latest/src/changes.html)를 준비하며 setuptools를 고정하여 업스트림 수정이 진행되는 동안 distutils가 계속 작동하도록 합니다. aarch64 휠은 다양한 Linux 배포판에서 사용되는 다양한 페이지 크기 문제를 해결하는 최신 manylinux2014 릴리스로 제작되었습니다. + +### 최초의 NumPy 설문조사가 진행 중입니다! + +_2020년 7월 2일_ -- 본 설문조사는 소프트웨어 및 커뮤니티로서의 NumPy 개발에 대하여, 의사결정의 우선 순위를 안내하고 설정하기 위해 실시됩니다. 설문지는 영어 외에도 8개 국어로 제공됩니다: 벵골어, 프랑스어, 힌디어, 일본어, 중국 관화, 포르투갈어, 러시아어, 스페인어. + +NumPy를 개선하게 도와주시고 이를위해 설문조사에 참여해 주세요. [여기](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). + + +### NumPy에 새로운 로고가 생겼습니다! + +_2020년 6월 24일_ -- NumPy에 새로운 로고가 생겼습니다. + +NumPy 로고 + +이전 로고를 깔끔하고 현대적으로 다시 디자인했습니다. 새 로고를 만들어 주신 Isabela Presedo-Floyd님께 감사드립니다. 또 15년이 넘는 기간 동안 저희가 사용했던 로고를 만들어 주신 Travis Vaught님께도 감사의 말씀을 드립니다. + + +### NumPy 1.19.0 출시 + +_2020년 6월 20일_ -- NumPy 1.19.0이 출시되었습니다. Python 2의 지원을 중단한 첫 릴리즈라서 "정리 릴리즈"라고도 불립니다. 이제 지원하는 Python 최소 버전은 3.6입니다. 중요한 새 기능을 꼽자면, NumPy 1.17.0에 도입된 난수 생성 인프라를 Cython에서 접근할 수 있게 되었다는 것입니다. + + +### Season of Docs 승인 + +_2020년 5월 11일_ -- NumPy가 Google Season of Docs 프로그램의 선도 조직으로 승인되었습니다. 테크니컬 라이터와 협력해서 NumPy 문서를 다시 한 번 개선할 수 있는 기회를 갖게 되어 좋습니다! 이상 자세한 내용은 [공식 문서 시즌 사이트](https://developers.google.com/season-of-docs/) 및 [아이디어 페이지](https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2020-Project-Ideas) 를 참조하세요. + + +### NumPy 1.18.0 출시 + +_2019년 12월 22일_ -- NumPy 1.18.0이 출시되었습니다. 1.17.0에서의 주요 변경점을 통합하는 릴리즈입니다. 본 릴리즈는 Python 3.5를 지원하는 마지막 마이너 릴리즈입니다. 릴리즈의 주요 내용으로는, 64비트 BLAS 및 LAPACK 라이브러리와 연결하기 위한 환경 조성, `numpy.random`을 위한 새로운 C-API 등이 있습니다. + +자세한 내용은 [출시 노트](https://github.com/numpy/numpy/releases/tag/v1.18.0)를 참조하세요. + + +### NumPy가 Chan Zuckerberg Initiative에서 보조금을 받았습니다 + +_2019년 11월 15일_ -- NumPy의 주요 종속 패키지 중 하나인 NumPy와 OpenBLAS가 챈 저커버그 이니셔티브의 [과학 프로그램용 중요 오픈소스 소프트웨어](https://chanzuckerberg.com/eoss/) 지원을 통해 19만 5천 달러에 달하는 공동 보조금을 받았다는 소식을 전할 수 있어 기쁩니다. 이곳에서는 과학에 중요한 오픈소스 도구에 대해 유지 관리, 성장, 개발 및 커뮤니티 참여를 지원합니다. + +이 보조금은 NumPy 문서, 웹사이트 재설계 및 커뮤니티 개발을 개선하여 빠르게 성장하는 대규모 사용자 기반에 더 나은 서비스를 제공하고 프로젝트의 장기적인 지속 가능성을 보장하는 데 사용될 것입니다. OpenBLAS 팀은 OpenBLAS가 의존하는 ReLAPACK(Recursive LAPACK) 의 알고리즘 개선뿐만 아니라 특히 스레드 안전성, AVX-512 및 스레드 로컬 스토리지(TLS) 문제와 같은 일련의 핵심 기술 문제를 해결하는 데 집중할 것입니다. + +제안된 계획 및 결과물에 대한 자세한 내용은 [전체 보조금 제안](https://figshare.com/articles/Proposal_NumPy_OpenBLAS_for_Chan_Zuckerberg_Initiative_EOSS_2019_round_1/10302167)에서 확인할 수 있습니다. 2019년 12월 1일부터 작업을 시작하여 다음 12개월 동안 진행할 예정입니다. + + + + +## 릴리즈 + +NumPy 릴리즈의 목록입니다. 릴리즈 노트로 링크도 걸려 있습니다. 버그 수정 릴리즈(`x.y.z`에서 `z`만 바뀐 경우)에는 새로운 기능이 없습니다. 마이너 릴리즈(`y`가 증가한 경우)에는 새로운 기능이 있습니다. + +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _ 2024년 2월 5일_. +- NumPy 1.26.3 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2024년 1월 2일_. +- NumPy 1.26.2 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _2023년 1월 2일_. +- NumPy 1.26.1 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _2023년 10월 14일_. +- NumPy 1.26.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _2023년 16월 9일_. +- NumPy 1.25.2 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _2023년 7월 31일_. +- NumPy 1.25.1 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _2023년 7월 8일_. +- NumPy 1.24.4 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _2023년 6월 26일_. +- NumPy 1.25.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _2023년 6월 17일_. +- NumPy 1.24.3 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _2023년 4월 22일_. +- NumPy 1.24.2 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _2023년 2월 5일_. +- NumPy 1.24.1 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _2022년 12월 26일_. +- NumPy 1.24.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _2022년 12월 18일_. +- NumPy 1.23.5 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _2022년 11월 19일_. +- NumPy 1.23.4 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _2022년 10월 12일_. +- NumPy 1.23.3 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _2022년 9월 9일_. +- NumPy 1.23.2 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _2022년 8월 14일_. +- NumPy 1.23.1 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _2022년 7월 8일_. +- NumPy 1.23.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _2022년 6월 22일_. +- NumPy 1.22.4 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _2022년 5월 20일_. +- NumPy 1.21.6 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _2022년 4월 12일_. +- NumPy 1.22.3 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _2022년 3월 7일_. +- NumPy 1.22.2 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _2022년 2월 3일_. +- NumPy 1.22.1 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _2022년 1월 14일_. +- NumPy 1.22.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _2021년 12월 31일_. +- NumPy 1.21.5 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _2021년 12월 19일_. +- NumPy 1.21.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _2021년 6월 22일_. +- NumPy 1.20.3 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _2021년 5월 10일_. +- NumPy 1.20.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _2021년 1월 30일_. +- NumPy 1.19.5 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _2021년 1월 5일_. +- NumPy 1.19.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _2020년 6월 20일_. +- NumPy 1.18.4 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _2020년 5월 3일_. +- NumPy 1.17.5 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _2020년 1월 1일_. +- NumPy 1.18.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _2019년 12월 22일_. +- NumPy 1.17.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _2019년 7월 26일_. +- NumPy 1.16.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _2019년 1월 14일_. +- NumPy 1.15.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _2018년 7월 23일_. +- NumPy 1.14.0 ([릴리즈 노트](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _2018년 1월 7일_. From b23d296444e8500eab0982f75716a457695d3045 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:42 +0100 Subject: [PATCH 07/17] New translations news.md (Russian) --- content/ru/news.md | 322 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 content/ru/news.md diff --git a/content/ru/news.md b/content/ru/news.md new file mode 100644 index 0000000000..7a7aba23fe --- /dev/null +++ b/content/ru/news.md @@ -0,0 +1,322 @@ +--- +title: News +sidebar: false +newsHeader: "NumPy 2.2.0 released!" +date: 2024-12-8 +--- + +### 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: + +* 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 drops support for Python 3.9. In addition to the usual bug fixes and 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. + +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 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: + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) + +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 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:** + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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  + +### 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 + +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](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 (`@=`). + +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](https://contributor-experience.org/docs/posts/dei-report/). + +### 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](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, + +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](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. + +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](http://numfocus.org/) on a [research project](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) funded by the [Gordon & Betty Moore Foundation](https://www.moore.org/) 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](https://numfocus.typeform.com/to/WBWVJSqe) 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](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 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](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 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](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. + +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](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 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](https://chanzuckerberg.com/eoss/), this [Diversity & Inclusion supplemental grant](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 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](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). + +### 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](https://numpy.org/doc/stable/release/1.21.0-notes.html) 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](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. +- 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](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). + +### 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](/diversity_sep2020). + + +### First official NumPy paper published in Nature! + +_Sep 16, 2020_ -- We are pleased to announce the publication of [the first official paper on NumPy](https://www.nature.com/articles/s41586-020-2649-2) 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`](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 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) is now available. This latest release in the 1.19 series fixes several bugs, prepares for the [upcoming Cython 3.x release](http://docs.cython.org/en/latest/src/changes.html) 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](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). + + +### NumPy has a new logo! + +_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](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`. + +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. + +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](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. + + + + +## 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. + +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. +- NumPy 1.26.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 Nov 2023_. +- NumPy 1.26.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 Oct 2023_. +- NumPy 1.26.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 Sep 2023_. +- NumPy 1.25.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 Jul 2023_. +- NumPy 1.25.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 Jul 2023_. +- NumPy 1.24.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 Jun 2023_. +- NumPy 1.25.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 Jun 2023_. +- NumPy 1.24.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 Apr 2023_. +- NumPy 1.24.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 Feb 2023_. +- NumPy 1.24.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 Dec 2022_. +- NumPy 1.24.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 Dec 2022_. +- NumPy 1.23.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _19 Nov 2022_. +- NumPy 1.23.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 Oct 2022_. +- NumPy 1.23.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 Sep 2022_. +- NumPy 1.23.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 Aug 2022_. +- NumPy 1.23.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 Jul 2022_. +- NumPy 1.23.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 Jun 2022_. +- NumPy 1.22.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 May 2022_. +- NumPy 1.21.6 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 Apr 2022_. +- NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. +- NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. +- NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. +- NumPy 1.22.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 Dec 2021_. +- NumPy 1.21.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 Dec 2021_. +- NumPy 1.21.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 Jun 2021_. +- NumPy 1.20.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 May 2021_. +- NumPy 1.20.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 Jan 2021_. +- NumPy 1.19.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 Jan 2021_. +- NumPy 1.19.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 Jun 2020_. +- NumPy 1.18.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 May 2020_. +- NumPy 1.17.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 Jan 2020_. +- NumPy 1.18.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 Dec 2019_. +- NumPy 1.17.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 Jul 2019_. +- NumPy 1.16.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. +- NumPy 1.15.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 Jul 2018_. +- NumPy 1.14.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 Jan 2018_. From 361cf0880ef57d02c0aab9e94e2acdd5a7840145 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:43 +0100 Subject: [PATCH 08/17] New translations news.md (Chinese Simplified) --- content/zh/news.md | 322 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 content/zh/news.md diff --git a/content/zh/news.md b/content/zh/news.md new file mode 100644 index 0000000000..8f47d8b76c --- /dev/null +++ b/content/zh/news.md @@ -0,0 +1,322 @@ +--- +title: 社区快讯 +sidebar: false +newsHeader: "NumPy 2.2.0 released!" +date: 2024-12-8 +--- + +### 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: + +* 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 drops support for Python 3.9. In addition to the usual bug fixes and 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. + +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 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: + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) + +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 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:** + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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  + +### 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. 此次发布的重点是： + +* 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](https://numpy.org/doc/stable/release/1.25.0-notes.html) is now available. 此次发布的重点是： + +* 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](https://contributor-experience.org/docs/posts/dei-report/). + +### 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](https://numpy.org/doc/stable/release/1.24.0-notes.html) is now available. 此次发布的重点是： + +* 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](https://numpy.org/doc/stable/release/1.23.0-notes.html) is now available. 此次发布的重点是： + +* 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](http://numfocus.org/) on a [research project](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) funded by the [Gordon & Betty Moore Foundation](https://www.moore.org/) 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](https://numfocus.typeform.com/to/WBWVJSqe) 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 发布 + +_2021年6月31日_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) 正式发布。 此次发布的重点是： + +* 主命名空间的注释类型基本上已完成。 上游是个移动目标，所以很可能会有进一步的改进，但是主要的 项工作已经完成。 这可能是本次发布中用户最可见的增强功能。 +* 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)). 这是创建一个可以在 CuPy 和 JAX 等库中使用的函数的标准收藏的一个步骤。 +* NumPy 现在有一个 DLPack 后端。 DLPack提供了一个数组 (tensor) 数据的通用交换格式。 +* `量化`, `百分比`以及相关函数的新方法。 新的 方法提供了一整套常见于 文献中的方法。 +* 通用函数已被重新考虑，以实现大多数的 [NEP 43](https://numpy.org/neps/nep-0043-extensible-ufuncs.html) 这也会解锁实验未来DType API的能力。 +* 一个新的可配置内存分配器，供下游项目使用。 + +NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. 此版本支持的 Python 版本是 3.8-3.10。 + +### 促进Python科学生态系统中的包容性文化 + +_8月31日， 2021_ — 我们很高兴宣布Chan Zuckerberg倡议 [授予赠款](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 以支持历史上被边缘化群体的人在科学Python项目中的融入、包容和留存，并为NumPy、SciPy、Matplotlib和Pandas的社区动态进行结构性改善。 + +作为 [CZI 基本开放源码科学程序](https://chanzuckerberg.com/eoss/)的一部分， 这 个[多样性 & 包容性补充赠款](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 将支持创建专门的负责人职位，以确定、记录和实施促进包容性开源社区的实践。 这个项目将由Melissa Mendoncstima (NumPy) 领导，由Ralf Gommers (NumPy, SciPy) Hannah Aizenman and Thomas Caswell (Matplotlib), Matt Haberland (SciPy), and Joris Van den Bossche (Pandas)， 提供 额外的辅导和指导 + +这是一个雄心勃勃的项目，旨在发现和执行 应该从结构上改善我们项目的社区动态的活动。 通过 建立这些新的跨项目角色，我们希望在Scientific Python社区引进一个新的 协作模型。 使生态系统中的 社区建设工作能够更有效地开展， 取得更大的成果。 我们还希望在项目中了解什么有效，什么无效，以吸引和留住来自历史上未被代表的群体的新贡献者，建立更清晰的认知。 最后，我们计划制作详细的报告，说明我们采取的措施如何在代表性和与社区互动方面对我们的项目产生影响。 + +这个为期两年的项目预计将于2021年11月开始，我们很期待看到这项工作的成果! [您可以在这里阅读完整的提案](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063)。 + +### 2021 Numpy调查 + +_2021年7月12日_ -- 我们相信NumPy社区的力量。 来自75个国家的1236 名用户参加了我们去年的首次调查。 调查结果使我们对今后12个月应该集中注意的问题有了很好的了解。 + +现在是时候进行另一次调查了，我们将再度尋求您的合作。 这份调查将耗费您大约15分钟的时间。 除英文外，调查问卷还提供另外8种语文：孟加拉语、法语、印地语、日语、普通话、葡萄牙语、俄语和西班牙语。 + +点击链接开始：https://berkeley.qualtrics.com/jfe/form/SV_aOONjgcBXDSl4q。 + + +### NumPy 1.21.0 发布 + +_2021年6月23日_ -- [NumPy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) 正式发布。 此次发布的重点是： + +- 继续开展SIMD工作，涵盖更多的功能和平台 +- 新dtype的基础和型态转换初步工作 +- 适用于Mac平台的Python 3.8和Python 3.9的universal2 wheels +- 改进文档 +- 改进注释 +- 新的 `PCG64DXSM` 位元生成器，用于生成随机数字 + +这个NumPy版本包含175人所贡献的581个合并请求。 此发布版本支持Python 3.7-3.9，将在Python 3.10发布后添加Python 3.10支持。 + + +### 2020 Numpy调研结果结果 + +_2021年6月22日_ -- 在2020年, NumPy调研小组与密歇根大学和马里兰大学的学生和教职员工合作，进行了第一次官方NumPy社区调查。 在这里可以查看调研结果：https://numpy.org/user-survey-2020/。 + + +### NumPy 1.20.0 发布 + +_2021年1月30日_ -- [NumPy 1.20.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) 正式发布。 这是 NumPy到目前为止最大的一次版本更新，感谢180+位贡献者。 最令人振奋的两个特点是： +- 为大部分Numpy代码做了类型注解，並添加了一个全新的`numpy.typing` 子模块，其中包含 `ArrayLike` 和 `DtypeLike`别名 ，使得用户和下游依赖库可以为自己的代码添加类型注解。 +- 为多个架构进行SIMD编译优化，其支持X86(SSE、AVX)、ARM64(Neon) 和PowerPC(VSX) 指令集。 大幅提高许多函数的性能(例如： [sin/cos](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194))。 + +### NumPy项目的多样性 + +_2020年9月20日_ -- 我们就NumPy项目的社交媒体、多样性和包容性的现状以及相关的讨论撰写了一份[声明](/diversity_sep2020)。 + + +### NumPy官方第一次在Nature发表论文！ + +_2020年9月16日_ - 我们高兴地宣布 [Numpy的第一篇官方论文](https://www.nature.com/articles/s41586-020-2649-2)刊登在Nature的评论文章。 这离NumPy 1.0发布已经过去了整整14年。 这篇论文涵盖了数组编程的应用和基本概念，基于NumPy构建的丰富科学Python生态系统，以及最近添加的数组协议，以促进与外部数组和张量库（如CuPy、Dask和JAX）的互操作性。 + + +### Python 3.9 即将来临，新版本的NumPy 将在何时发布？ + +_2020年9月14日_ -- Python 3.9 将在几周后发布。 如果您是这个Python版本的早期采用者， 您可能会失望的发现NumPy(以及其他二进制软件包，如SciPy) 在Python新版发布当天还不会发布相应的版本。 构建兼容新的 Python 版本的基础设施需要付出重大努力，通常需要几周时间才能让新版本出现在 PyPI 和 conda-forge 上。 为了这次版本升级得以顺利进行，请确保： +- 将您的 `pip` 升级到 20.1 版本，至少要支持`manylinux2010` 和 `manylinux2014` +- 使用 [`--only-binary=numpy`](https://pip.pypa.io/en/stable/reference/pip_install/#cmdoption-only-binary) 或 `--only-binary=:all:` 选项来防止 `pip` 尝试从源码构建。 + + +### NumPy 1.19.2 发布 + +_2020年9月10日_ -- [NumPy 19.2.0](https://numpy.org/devdocs/release/1.19.2-notes.html) 正式发布。 这个最新版本修复了1.19 系列中的几个漏洞，为 [即将发布的Cython3.x](http://docs.cython.org/en/latest/src/changes.html) 做准备，並固定设置工具以在上游修改正在进行时保持 distutils 工作。 Aarch64架构的安装包是用最新的 manylinux2014 版本构建的，它修复了 linux 发行版之间使用不同大小内存页的问题。 + +### 首次NumPy调研即将开始！ + +_Jul 2, 2020_ - 本次调查旨在指导并确定 关于开发NumPy 作为软件和社区的决策重点。 除英文外，调查还提供了另外8种语言的版本：孟加拉语、印地语、日语、普通话、葡萄牙语、俄语、西班牙语和法语。 + +请帮助我们让 NumPy 变得更好，在[这里](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl)参与调查。 + + +### NumPy 有新标志了! + +_2020年7月24日_ -- NumPy 现在有一个新的标志： + +NumPy 标志 + +这个标志是对旧标志的现代化演绎，采用更加简洁的设计。 感谢Isabela Presedo-Floryd的设计方案， 同时感谢Travis Vaugh设计的旧图标为我们服务了15年以上。 + + +### NumPy 1.19.0 发布 + +_2020年6月20日_ -- NumPy 1.19.0 正式发布。 这是第一个不支持Python 2的版本，因此它是一个“清理版本”。 目前支持的最低Python 版本是 Python 3.6。 本版本拥有一个重要的新特性，NumPy 1.17.0引进的随机数字生成基础模块现在可以通过Cython访问。 + + +### 文档整改时段 + +_2020年5月11日_ -- NumPy 已成为Google Season 文档项目之一。 我们很高兴看到有机会和技术写作者一起再次改进NumPy的技术文档！ 更多详情，请参考 [文档整改时段官方网站](https://developers.google.com/season-of-docs/) 和我们的 [意见页面](https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2020-Project-Ideas)。 + + +### NumPy 1.18.0 发布 + +_2019年12月22日_ -- NumPy 1.18.0 正式发布。 在1.17.0发生重大变化后，这是一个合并版本。 这是最后一个支持 Python 3.5的小版本。 该版本的重要更新包括两个，添加了与64位 BLAS 和 LAPACK 库有关的底层更新， 添加 一个用于`numpy.random`的新C-API更新。 + +详情请看 [版本说明](https://github.com/numpy/numpy/releases/tag/v1.18.0)。 + + +### NumPy 从Chan Zuckerberg Initiative获得了一笔捐款 + +_2019年11月15日_ -- 我们高兴地宣布NumPy和 OpenBLAS (Numpy的一个核心依赖库)已经收到一笔19,5000美元的联合赠款。 捐款来自于Chan Zuckerberg Initiative通过的[基础开源科学计算软件项目](https://chanzuckerberg.com/eoss/)，用来支持对科学发展起到关键作用的开源软件的维护、增长、开发和社区参与。 + +这笔赠款将用来加速改进NumPy文档、网站重构和社区开发，进而更好地为我们庞大和迅速增长的用户基础服务，并确保项目的长期可持续性。 OpenBLAS 团队将侧重于处理几个关键技术问题，特别是线程安全问题、AVX-512和 thread-local 存储(TLS) 问题，以及OpenBLAS 依赖的 ReLAPACK (递归的LAPACK) 算法改进。 + +若想查看更多关于捐款的倡议和交付件的详情，可在 [全额赠款提案](https://figshare.com/articles/Proposal_NumPy_OpenBLAS_for_Chan_Zuckerberg_Initiative_EOSS_2019_round_1/10302167) 中找到。 项目开始于2019年12月1日，今后12个月将持续运作下去。 + + + + +## 版本发布 + +这是NumPy 版本列表，包含了对应版本发布说明的链接。 所有的 bug修复版本(即在 `x.y.z`格式版本号中只有 `z`改变)没有新功能；小版本更新(`y` 改变)有新功能。 + +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. +- NumPy 1.26.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 Nov 2023_. +- NumPy 1.26.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 Oct 2023_. +- NumPy 1.26.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 Sep 2023_. +- NumPy 1.25.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 Jul 2023_. +- NumPy 1.25.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 Jul 2023_. +- NumPy 1.24.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 Jun 2023_. +- NumPy 1.25.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 Jun 2023_. +- NumPy 1.24.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 Apr 2023_. +- NumPy 1.24.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 Feb 2023_. +- NumPy 1.24.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 Dec 2022_. +- NumPy 1.24.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 Dec 2022_. +- NumPy 1.23.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _19 Nov 2022_. +- NumPy 1.23.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 Oct 2022_. +- NumPy 1.23.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 Sep 2022_. +- NumPy 1.23.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 Aug 2022_. +- NumPy 1.23.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 Jul 2022_. +- NumPy 1.23.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 Jun 2022_. +- NumPy 1.22.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 May 2022_. +- NumPy 1.21.6 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 Apr 2022_. +- NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. +- NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. +- NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. +- NumPy1.22.0 (发行说明) -- _2021年12月31日_. +- NumPy1.21.5 (发行说明) -- _2021年12月19日_. +- NumPy1.21.0 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _2021年6月22日_. +- NumPy1.23.0 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _2021年5月10日_. +- NumPy1.20.0 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _2021年1月30日_. +- NumPy1.19.5 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _2021年1月5日_. +- NumPy1.19.0 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _2020年6月20日_. +- NumPy1.18.4 (发行说明) -- _2020年5月3日_. +- NumPy1.17.5 (发行说明) -- _2020年1月1日_. +- NumPy1.18.0 (发行说明) -- _2019年12月22日_. +- NumPy1.17.0 (发行说明) -- _2019年7月26日_. +- NumPy1.16.0 (发行说明) -- _2019年1月14日_. +- NumPy1.15.0 (发行说明) -- _2018年7月23日_. +- NumPy1.14.0 (发行说明) -- _2018年1月7日_. From 26434ad9e7e95032a24e6b683af1b0a67a233dc9 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:44 +0100 Subject: [PATCH 09/17] New translations news.md (Portuguese, Brazilian) --- content/pt/news.md | 89 ++++++++++++++++++++++++++++++++++++++-------- 1 file changed, 74 insertions(+), 15 deletions(-) diff --git a/content/pt/news.md b/content/pt/news.md index e972a74130..cfb217bcc7 100644 --- a/content/pt/news.md +++ b/content/pt/news.md @@ -5,11 +5,60 @@ newsHeader: "NumPy versão 1.26.0" date: 2023-09-16 --- +### 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: + +* 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. + + ### Lançado o NumPy versão 1.26.0 -_16 de setembro de 2023_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html) está disponível. Os destaques desta versão são: +_18 de agosto, 2024_ -- NumPy 2.1.0 fornece suporte para Python 3.13 e remove suporte para Python 3.9. Além das habituais correções de erros e suporte a Python atualizado, esta versão ajuda a trazer o NumPy de volta ao ciclo habitual de lançamento após o longo desenvolvimento da versão 2.0. Os destaques desta versão são: + +- Suporte ao Python 3.12.0. +- Suporte preliminar para Python 3.13 free threaded. +- Suporte para array-api 2023.12 standard. + +As versões 3.10-3.13 do Python são suportadas por esta versão. + + +### NumPy 2.0.0 lançada + +_16 de junho, 2024_ -- NumPy 2.0.0 é a primeira grande versão desde 2006. É o resultado de 11 meses de desenvolvimento desde a última feature release e é o trabalho de 212 contribuidores espalhado por 1078 pull requests. Esta versão contém um grande número de novas funcionalidades interessantes, bem como mudanças nas APIs Python e C. As mudanças incluem quebras de compatibilidade que não puderam acontecer em uma versão regular menor - incluindo uma quebra na ABI, mudanças nas regras de promoção de tipo e mudanças na API que poderiam não estar emitindo alertas de fim de suporte nas versões 1.26.x. Documentos-chave, relacionados a como se adaptar às mudanças em NumPy 2.0, incluem: + +- O [guia de migração NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- As [notas de lançamento da versão 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) +- Issue de anúncio para atualizações de estado: [numpy#24300](https://github.com/numpy/numpy/issues/24300) + +A postagem de blog ["NumPy 2.0: an evolutionary milestone"](https://blog.scientific-python.org/numpy/numpy2/) conta um pouco da história sobre como esta versão foi construída. + + +### Data de lançamento da NumPy 2.0: 16 de junho + +_23 de maio, 2024_ -- Estamos animados em anunciar que planejamos lançar a NumPy 2.0 em 16 de junho de 2024. Este lançamento está em desenvolvimento há mais de um ano, e é o primeiro grande lançamento desde 2006. Importante, além de muitas funcionalidades novas e melhoria de desempenho, esta versão contém **quebras de compatibilidade** com a ABI e com as APIs Python e C. É provável que os pacotes downstream e o código de usuário final precisem ser adaptados - se você puder, por favor, verifique se o seu código funciona com NumPy `2.0.0rc2`. **Por favor, veja o seguinte para mais detalhes:** + +- O [guia de migração NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- As [notas de lançamento da versão 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) +- Issue de anúncio para atualizações de estado: [numpy#24300](https://github.com/numpy/numpy/issues/24300) + + +### Lançado o NumPy versão 1.26.0 +_19 de dez, 2023_ -- O NumFOCUS se juntou ao PyCharm durante sua campanha de final de ano para oferecer 30% de desconto em licenças de PyCharm para novos usuários. Todas as receitas do primeiro ano das compras do PyCharm a partir de agora até 23 de dezembro, 2023 irão diretamente para os programas NumFOCUS. + +Use a URL única que permitirá rastrear as compras https://lp.jetbrains.com/support-data-science/ ou um código de cupom ISUPPORTDATASCIENCE  + +### NumPy versão 1.24.0 -* Suporte ao Python 3.12.0. +_17 de junho, 2023_ -- [NumPy 1.25.0](https://numpy.org/doc/stable/release/1.25.0-notes.html) está disponível agora. Os destaques desta versão são: + +* Suport ao Python 3.12.0. * Compatibilidade com Cython 3.0.0. * Utilização do sistema Meson para compilação * Suport a SIMD atualizado @@ -33,7 +82,7 @@ _Português:_ * Alexandre B A Villares (villares) * Vini Salazar (vinisalazar) -Japonês: +_Japonês:_ * Atsushi Sakai (AtsushiSakai) * KKunai * Tom Kelly (TomKellyGenetics) @@ -42,11 +91,11 @@ Japonês: O trabalho na infraestrutura de traduções é financiado pela CZI. -No futuro, adoraríamos traduzir o site para mais línguas. Se você quiser ajudar, por favor entre em contato com o time de traduções do NumPy no Slack: -https://join.slack.com/t/numpy-team/shared_invite/zt-1gokbq56s-bvEpo10Ef7aHbVtVFeZv2w. (Procure pelo canal #translations) -Também estamos organizando um time de tradutores que serão responsáveis por trabalhar na localização da documentação e conteúdo educacional para o ecossistema Scientific Python. Se esse trabalho te interessa, junte-se a nós no Discord do projeto Scientific Python: https://discord.gg/khWtqY6RKr. (Procure pelo canal #translation) +No futuro, adoraríamos traduzir o site para mais línguas. Se você quiser ajudar, por favor entre em contato com o time de traduções do NumPy no Slack: https://join.slack.com/t/numpy-team/shared_invite/zt-1gokbq56s-bvEpo10Ef7aHbVtVFeZv2w. (Procure pelo canal de #translations.) (Procure pelo canal #translations) Também estamos organizando um time de tradutores que serão responsáveis por trabalhar na localização da documentação e conteúdo educacional para o ecossistema Scientific Python. Se esse trabalho te interessa, junte-se a nós no Discord do projeto Scientific Python: https://discord.gg/khWtqY6RKr. (Procure pelo canal #translation) -_17 de junho, 2023_ -- [NumPy 1.25.0](https://numpy.org/doc/stable/release/1.25.0-notes.html) está disponível agora. Os destaques desta versão são: +### NumPy versão 1.22.0 + +_18 de dezembro de 2022_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html) está agora disponível. Os destaques desta versão são: * Suporte para MUSL, agora existem rodas MUSL. * Suporte para o compilador Fujitsu C/C++. @@ -69,9 +118,9 @@ Como podemos ser melhores quando se trata de diversidade e de inclusão? Leia o _6 de janeiro de 2023_ –- Mukulika Pahari e Ross Barnowski são nomeados como lideres do time de documentação do NumPy, substituindo Melissa Mendonça. Agradecemos a Melissa por todas suas contribuições para a documentação oficial do NumPy e materiais educacionais, e Mukulika e Ross por aceitarem o desafio. -### NumPy versão 1.24.0 +### NumPy versão 1.23.0 -_18 de dezembro de 2022_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html) está agora disponível. Os destaques desta versão são: +_31 de dezembro de 2021_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) está agora disponível. Os destaques desta versão são: * Novas palavras-chave "dtype" e "casting" para funções que atuam com stacking. * Novas funcionalidades e correções do F2PY. @@ -80,7 +129,7 @@ _18 de dezembro de 2022_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/ A versão 1.24.0 do NumPy continua o trabalho de melhorias no suporte e promoção de dtypes, na velocidade e execução, e na documentação. Há um grande número de depreciações novas e expiradas devido a mudanças na promoção de dtypes e limpezas no código. É o trabalho de 177 contribuidores espalhados em 444 pull requests. As versões suportadas do Python são 3.8-3.11. -### NumPy versão 1.23.0 +### NumPy versão 1.19.0 _22 de junho de 2022_ -- O [NumPy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html) está disponível. Os destaques desta versão são: @@ -99,9 +148,9 @@ _13 de abril de 2022_ -- O NumPy está trabalhando com a [NumFOCUS](http://numfo Por favor, preencha este breve formulário: ["Participant Interest form"](https://numfocus.typeform.com/to/WBWVJSqe) que contém informações adicionais sobre os objetivos da pesquisa, privacidade e considerações de confidencialidade. Sua participação será valiosa para o crescimento e sustentabilidade de comunidades de software open source diversas e inclusivas. Os participantes aceitos participarão de uma entrevista de 30 minutos com um membro da equipe de pesquisa. -### NumPy versão 1.22.0 +### NumPy versão 1.20.0 -_31 de dezembro de 2021_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) está agora disponível. Os destaques desta versão são: +_23 de junho de 2021_ -- O [NumPy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) está disponível. Os destaques desta versão são: * Anotações de tipo do namespace principal estão praticamente completas. Ainda há trabalho a se fazer no upstream, mas a maior parte do trabalho está feita. Esta é provavelmente a melhoria mais visível para os usuários nesta versão. * Uma versão preliminar da proposta do [array API Standard](https://data-apis.org/array-api/latest/) está disponível (veja [NEP 47](https://numpy.org/neps/nep-0047-array-api-standard.html)). Este é um passo na criação de uma coleção padrão de funções que podem ser compartilhadas entre bibliotecas como CuPy e JAX. @@ -133,7 +182,7 @@ Siga o link para começar: https://berkeley.qualtrics.com/jfe/form/SV_aaOONjgcBX ### NumPy versão 1.19.0 -_23 de junho de 2021_ -- O [NumPy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) está disponível. Os destaques desta versão são: +_16 de setembro de 2023_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html) está disponível. Os destaques desta versão são: - a continuação do trabalho com SIMD para suportar mais funções e plataformas, - trabalho inicial na infraestrutura e conversão de novos dtypes, @@ -173,7 +222,7 @@ _14 de setembro de 2020_ -- Python 3.9 será lançado em algumas semanas. Se voc - usar [`--only-binary=numpy`](https://pip.pypa.io/en/stable/reference/pip_install/#cmdoption-only-binary) ou `--only-binary=:all:` para impedir `pip` de tentar compilar a partir do código fonte. -### NumPy versão 1.19.2 +### NumPy versão 1.18.0 _10 de setembro de 2020_ -- O [NumPy 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) está disponível. Essa última versão da série 1.19 corrige vários bugs, inclui preparações para o lançamento [do Cython 3](http://docs.cython.org/en/latest/src/changes.html) e fixa o setuptools para que o distutils continue funcionando enquanto modificações upstream estão sendo feitas. As wheels para aarch64 são compiladas com manylinux2014 mais recente que conserta um problema com distribuições linux diferentes. @@ -203,7 +252,7 @@ _20 de junho de 2020_ -- O NumPy 1.19.0 está disponível. Esta é a primeira ve _11 de maio de 2020_ -- O NumPy foi aceito como uma das organizações mentoras do programa Google Season of Docs. Estamos animados com a oportunidade de trabalhar com um *technical writer* para melhorar a documentação do NumPy mais uma vez! Para mais detalhes, consulte [o site oficial do programa Season of Docs](https://developers.google.com/season-of-docs/) e nossa [página de ideias](https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2020-Project-Ideas). -### NumPy versão 1.18.0 +### NumPy versão 1.19.2 _22 de dezembro de 2019_ -- O NumPy 1.18.0 está disponível. Após as principais mudanças em 1.17.0, esta é uma versão de consolidação. É a última versão menor que suportará Python 3.5. Destaques dessa versão incluem a adição de uma infraestrutura básica para permitir o link com as bibliotecas BLAS e LAPACK em 64 bits durante a compilação, e uma nova C-API para `numpy.random`. @@ -225,6 +274,16 @@ Mais detalhes sobre nossas propostas e resultados esperados podem ser encontrado Aqui está uma lista de versões do NumPy, com links para notas de lançamento. Bugfix lança (apenas o `z` muda no `x.y.` número da versão) não tem novos recursos; versões menores (o `y` aumenta) sim. +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 de outubro de 2024_. +- NumPy 2.1.1 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 de setembro de 2024_. +- NumPy 2.0.2 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 de agosto de 2024_. +- NumPy 2.1.0 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 de agosto de 2024_. +- NumPy 2.0.1 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 de julho de 2024_. +- NumPy 2.0.0 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 de junho de 2024_. +- NumPy 1.26.4 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 de fevereiro de 2024_. +- NumPy 1.26.3 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 de janeiro de 2024_. - NumPy 1.26.2 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 de novembro de 2023_. - NumPy 1.26.1 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 de outubro de 2023_. - NumPy 1.26.0 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 de setembro de 2023_. From f64ad45d9c4800e5d75d551765e5a15d71d4c7fa Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:45 +0100 Subject: [PATCH 10/17] New translations news.md (Persian) --- content/fa/news.md | 322 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 content/fa/news.md diff --git a/content/fa/news.md b/content/fa/news.md new file mode 100644 index 0000000000..7a7aba23fe --- /dev/null +++ b/content/fa/news.md @@ -0,0 +1,322 @@ +--- +title: News +sidebar: false +newsHeader: "NumPy 2.2.0 released!" +date: 2024-12-8 +--- + +### 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: + +* 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 drops support for Python 3.9. In addition to the usual bug fixes and 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. + +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 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: + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) + +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 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:** + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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  + +### 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 + +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](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 (`@=`). + +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](https://contributor-experience.org/docs/posts/dei-report/). + +### 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](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, + +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](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. + +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](http://numfocus.org/) on a [research project](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) funded by the [Gordon & Betty Moore Foundation](https://www.moore.org/) 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](https://numfocus.typeform.com/to/WBWVJSqe) 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](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 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](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 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](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. + +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](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 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](https://chanzuckerberg.com/eoss/), this [Diversity & Inclusion supplemental grant](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 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](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). + +### 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](https://numpy.org/doc/stable/release/1.21.0-notes.html) 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](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. +- 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](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). + +### 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](/diversity_sep2020). + + +### First official NumPy paper published in Nature! + +_Sep 16, 2020_ -- We are pleased to announce the publication of [the first official paper on NumPy](https://www.nature.com/articles/s41586-020-2649-2) 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`](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 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) is now available. This latest release in the 1.19 series fixes several bugs, prepares for the [upcoming Cython 3.x release](http://docs.cython.org/en/latest/src/changes.html) 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](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). + + +### NumPy has a new logo! + +_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](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`. + +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. + +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](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. + + + + +## 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. + +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. +- NumPy 1.26.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 Nov 2023_. +- NumPy 1.26.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 Oct 2023_. +- NumPy 1.26.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 Sep 2023_. +- NumPy 1.25.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 Jul 2023_. +- NumPy 1.25.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 Jul 2023_. +- NumPy 1.24.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 Jun 2023_. +- NumPy 1.25.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 Jun 2023_. +- NumPy 1.24.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 Apr 2023_. +- NumPy 1.24.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 Feb 2023_. +- NumPy 1.24.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 Dec 2022_. +- NumPy 1.24.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 Dec 2022_. +- NumPy 1.23.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _19 Nov 2022_. +- NumPy 1.23.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 Oct 2022_. +- NumPy 1.23.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 Sep 2022_. +- NumPy 1.23.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 Aug 2022_. +- NumPy 1.23.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 Jul 2022_. +- NumPy 1.23.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 Jun 2022_. +- NumPy 1.22.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 May 2022_. +- NumPy 1.21.6 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 Apr 2022_. +- NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. +- NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. +- NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. +- NumPy 1.22.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 Dec 2021_. +- NumPy 1.21.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 Dec 2021_. +- NumPy 1.21.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 Jun 2021_. +- NumPy 1.20.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 May 2021_. +- NumPy 1.20.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 Jan 2021_. +- NumPy 1.19.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 Jan 2021_. +- NumPy 1.19.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 Jun 2020_. +- NumPy 1.18.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 May 2020_. +- NumPy 1.17.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 Jan 2020_. +- NumPy 1.18.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 Dec 2019_. +- NumPy 1.17.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 Jul 2019_. +- NumPy 1.16.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. +- NumPy 1.15.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 Jul 2018_. +- NumPy 1.14.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 Jan 2018_. From ec9f5730972f435fd2898b3d4fb3a703ef74fc6c Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:30:47 +0100 Subject: [PATCH 11/17] New translations news.md (Hindi) --- content/hi/news.md | 322 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 content/hi/news.md diff --git a/content/hi/news.md b/content/hi/news.md new file mode 100644 index 0000000000..7a7aba23fe --- /dev/null +++ b/content/hi/news.md @@ -0,0 +1,322 @@ +--- +title: News +sidebar: false +newsHeader: "NumPy 2.2.0 released!" +date: 2024-12-8 +--- + +### 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: + +* 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 drops support for Python 3.9. In addition to the usual bug fixes and 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. + +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 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: + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) + +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 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:** + +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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  + +### 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 + +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](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 (`@=`). + +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](https://contributor-experience.org/docs/posts/dei-report/). + +### 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](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, + +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](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. + +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](http://numfocus.org/) on a [research project](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) funded by the [Gordon & Betty Moore Foundation](https://www.moore.org/) 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](https://numfocus.typeform.com/to/WBWVJSqe) 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](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 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](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 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](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. + +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](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 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](https://chanzuckerberg.com/eoss/), this [Diversity & Inclusion supplemental grant](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 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](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). + +### 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](https://numpy.org/doc/stable/release/1.21.0-notes.html) 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](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. +- 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](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). + +### 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](/diversity_sep2020). + + +### First official NumPy paper published in Nature! + +_Sep 16, 2020_ -- We are pleased to announce the publication of [the first official paper on NumPy](https://www.nature.com/articles/s41586-020-2649-2) 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`](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 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) is now available. This latest release in the 1.19 series fixes several bugs, prepares for the [upcoming Cython 3.x release](http://docs.cython.org/en/latest/src/changes.html) 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](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). + + +### NumPy has a new logo! + +_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](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`. + +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. + +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](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. + + + + +## 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. + +- NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. +- NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. +- NumPy 1.26.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 Nov 2023_. +- NumPy 1.26.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 Oct 2023_. +- NumPy 1.26.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 Sep 2023_. +- NumPy 1.25.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 Jul 2023_. +- NumPy 1.25.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 Jul 2023_. +- NumPy 1.24.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 Jun 2023_. +- NumPy 1.25.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 Jun 2023_. +- NumPy 1.24.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 Apr 2023_. +- NumPy 1.24.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 Feb 2023_. +- NumPy 1.24.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 Dec 2022_. +- NumPy 1.24.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 Dec 2022_. +- NumPy 1.23.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _19 Nov 2022_. +- NumPy 1.23.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 Oct 2022_. +- NumPy 1.23.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 Sep 2022_. +- NumPy 1.23.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 Aug 2022_. +- NumPy 1.23.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 Jul 2022_. +- NumPy 1.23.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 Jun 2022_. +- NumPy 1.22.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 May 2022_. +- NumPy 1.21.6 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 Apr 2022_. +- NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. +- NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. +- NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. +- NumPy 1.22.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 Dec 2021_. +- NumPy 1.21.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 Dec 2021_. +- NumPy 1.21.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 Jun 2021_. +- NumPy 1.20.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 May 2021_. +- NumPy 1.20.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 Jan 2021_. +- NumPy 1.19.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 Jan 2021_. +- NumPy 1.19.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 Jun 2020_. +- NumPy 1.18.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 May 2020_. +- NumPy 1.17.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 Jan 2020_. +- NumPy 1.18.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 Dec 2019_. +- NumPy 1.17.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 Jul 2019_. +- NumPy 1.16.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. +- NumPy 1.15.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 Jul 2018_. +- NumPy 1.14.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 Jan 2018_. From 43f25c914d01f7ab96d1fff92177915fb36108a0 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:34:50 +0100 Subject: [PATCH 12/17] New translations news.md (Spanish) --- content/es/news.md | 344 ++++++++++++++++++++++----------------------- 1 file changed, 172 insertions(+), 172 deletions(-) diff --git a/content/es/news.md b/content/es/news.md index 209ea5b9da..dc73b05bdb 100644 --- a/content/es/news.md +++ b/content/es/news.md @@ -1,8 +1,8 @@ --- -title: Noticias +title: News sidebar: false -newsHeader: "¡NumPy 2.0 ha sido lanzado!" -date: 2024-06-17 +newsHeader: "NumPy 2.2.0 released!" +date: 2024-12-8 --- ### NumPy 2.2.0 released @@ -18,45 +18,45 @@ _8 Dec, 2024_ -- The NumPy 2.2.0 release is a quick release that brings us back This release supports Python versions 3.10-3.13. -### Lanzamiento de NumPy 2.1.0 +### NumPy 2.1.0 released -_18 de agosto 2024_ -- NumPy 2.1.0 provides support for Python 3.13 and drops support for Python 3.9. Además de las habituales correcciones de errores y soporte actualizado de Python, ayuda a que NumPy vuelva a su ciclo de publicación habitual después del extenso desarrollo de 2.0. Los aspectos más destacados son: +_18 Aug, 2024_ -- NumPy 2.1.0 provides support for Python 3.13 and drops support for Python 3.9. In addition to the usual bug fixes and 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: -- Soporte para Python 3.13. -- Soporte preliminar para Python 3.13 de hilos libres. -- Compatibilidad con la norma array-api 2023.12. +- Support for Python 3.13. +- Preliminary support for free threaded Python 3.13. +- Support for the array-api 2023.12 standard. -Esta versión es compatible con las versiones 3.10-3.13 de Python. +Python versions 3.10-3.13 are supported by this release. -### Lanzamiento de NumPy 2.0.0 +### NumPy 2.0.0 released -_16 de junio de 2024_ -- NumPy 2.0.0 es el primer lanzamiento importante desde 2006. Es el resultado de 11 meses de desarrollo desde el último lanzamiento de características y es el trabajo de 212 colaboradores distribuidos entre 1078 solicitudes de incorporación de cambios. Contiene un gran número de nuevas características interesantes, así como cambios en las APIs de Python y C. Incluye cambios importantes que no podrían producirse en un lanzamiento menor regular, como una ruptura de ABI, cambios en las reglas de promoción de tipos y cambios en la API que podrían no haber estado emitiendo advertencias de obsolescencia en la versión 1.26.x. Los documentos clave relacionados con cómo adaptarse a los cambios en NumPy 2.0 incluyen: +_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 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: -- La [guía de migración a NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- Las [ notas del lanzamiento 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) -- Emisión de anuncios para actualizaciones de estado: [numpy#24300](https://github.com/numpy/numpy/issues/24300) +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) -La publicación ["NumPy 2.0: an evolutionary milestone"](https://blog.scientific-python.org/numpy/numpy2/) cuenta un poco de la historia sobre cómo se llegó a este lanzamiento. +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. -### Fecha de lanzamiento de NumPy 2.0: 16 de junio +### NumPy 2.0 release date: June 16 -_23 de mayo de 2024_ -- Estamos encantados de anunciar que NumPy 2.0 está previsto que sea lanzado el 16 de junio de 2024. Esta publicación lleva más de un año en proceso y es el primer lanzamiento importante desde 2006. Es importante destacar que, además de muchas nuevas características y mejoras en el rendimiento, contiene **cambios disruptivos** frente al ABI, como también a las APIs de Python y C. Es probable que los paquetes dependientes o downstream y código de usuario final necesiten ser adaptados - si puedes, por favor verifica que tu código funciona con NumPy `2.0.0rc2`. **Por favor, revisa lo siguiente para más detalles:** +_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:** -- La [Guía de migración de NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- Las [notas de lanzamiento 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) -- Emisión de anuncios para actualizaciones de estado: [numpy#24300](https://github.com/numpy/numpy/issues/24300) +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) -### Recaudación de fondos de fin de año de NumFOCUS -_19 de diciembre de 2023_ -- NumFOCUS se ha asociado con PyCharm durante su campaña de fin de año para ofrecer un 30% de descuento en licencias de primera vez de PyCharm. Todos los ingresos del primer año de las compras de PyCharm desde ahora hasta el 23 de diciembre de 2023 se destinarán directamente a los programas de NumFOCUS. +### 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. -Utiliza una URL única que te permitirá rastrear las compras https://lp.jetbrains.com/support-data-science/ o un código de cupón ISUPPORTDATASCIENCE  +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 ha sido lanzado +### NumPy 1.26.0 released -_16 de septiembre de 2023_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html) ahora está disponible. Los aspectos más destacados del lanzamiento son: +_Sep 16, 2023_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html) ahora está disponible. The highlights of the release are: * Soporte de Python 3.12.0. * Compatibilidad con Cython 3.0.0. @@ -69,254 +69,254 @@ La versión 1.26.0 de NumPy es la continuación de la serie 1.25.x que marca la Las versiones de Python compatibles con esta versión son 3.9-3.12. -### numpy.org ya está disponible en japonés y portugués +### numpy.org is now available in Japanese and Portuguese -_ 2 de agosto de 2023_ -- numpy.org ya está disponible en 2 idiomas adicionales: japonés y portugués. Esto no sería posible sin nuestros dedicados voluntarios: +_Aug 2, 2023_ -- numpy.org is now available in 2 additional languages: Japanese and Portuguese. This wouldn’t be possible without our dedicated volunteers: -_Portugués:_ -* Melissa Weber Mendonça (melissawm) -* Precios Ricardo (ricardoprins) -* Getúlio Silva (getuliosilva) +_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) -_Japonés:_ +_Japanese:_ * Atsushi Sakai (AtsushiSakai) * KKunai * Tom Kelly (TomKellyGenetics) * Yuji Kanagawa (kngwyu) * Tetsuo Koyama (tkoyama010) -El trabajo sobre la infraestructura de traducción se apoya con fondos de CZI. +The work on the translation infrastructure is supported with funding from CZI. -De cara al futuro, nos encantaría traducir el sitio web a más idiomas. Si quieres ayudar, por favor pone en contacto con el equipo de traducciones de NumPy en Slack: https://join.slack.com/t/numpy-team/shared_invite/zt-1gokbq56s-bvEpo10Ef7aHbVtVFeZv2w. (Busca el canal #translations) También estamos formando un equipo de traducciones que estará trabajando en la localización de la documentación y el contenido educativo a través de todo el ecosistema de Python científico. Si esto ha despertado tu interés, únete a nosotros en el Discord de Python científico: https://discord.gg/khWtqY6RKr. (Busca el canal #translations) +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 ha sido lanzado +### NumPy 1.25.0 released -_17 de junio de 2023_ -- [NumPy 1.25.0](https://numpy.org/doc/stable/release/1.25.0-notes.html) ya está disponible. Los aspectos más destacados del lanzamiento son: +_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: -* Soporte para MUSL, ahora hay ruedas MUSL. -* Soporte para el compilador de Fujitsu C/C++. -* Los arreglos de objetos ahora están soportadas en einsum. -* Soporte para la multiplicación de matrices in situ (`@=`). +* 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 (`@=`). -NumPy 1.25. continúa el trabajo en curso para mejorar el manejo y promoción de dtypes, aumentar la velocidad de ejecución y clarificar la documentación. También se ha realizado trabajo preparatorio para el futuro NumPy 2.0.0, resultando en un gran número de nuevas y eliminadas obsolescencias. +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. -Un total de 148 personas contribuyeron a esta versión y 530 solicitudes de incorporación de cambios fueron aceptadas. +A total of 148 people contributed to this release and 530 pull requests were merged. -Las versiones de Python soportadas por este lanzamiento son 3.9-3.11. +The Python versions supported by this release are 3.9-3.11. -### Fomentar una Cultura Inclusiva: Convocatoria de Participación +### Fostering an Inclusive Culture: Call for Participation -_10 de mayo de 2023_ -- Fomentar una Cultura Inclusiva: Convocatoria de Participación +_May 10, 2023_ -- Fostering an Inclusive Culture: Call for Participation -¿Cómo podemos ser mejores cuando se trata de diversidad e inclusión? Lee el informe y averigua cómo involucrarte [aquí](https://contributor-experience.org/docs/posts/dei-report/). +How can we be better when it comes to diversity and inclusion? Read the report and find out how to get involved [here](https://contributor-experience.org/docs/posts/dei-report/). -### Transición en el liderazgo del equipo de documentación de NumPy +### NumPy documentation team leadership transition -_6 de enero de 2023_ –- Mukulika Pahari y Ross Barnowski son nombrados como los nuevos líderes del equipo de documentación de NumPy, reemplazando a Melissa Mendonça. Damos las gracias a Melissa por todas sus contribuciones a la documentación oficial de NumPy y materiales educativos, y a Mukulika y Ross por asumir este rol. +_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. -### Lanzamiento de NumPy 1.24.0 +### NumPy 1.24.0 released -_18 de diciembre de 2022_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html) ya está disponible. Los aspectos más destacados del lanzamiento son: +_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: -* Nuevas palabras clave "dtype" y "casting" para las funciones de apilamiento. -* Nuevas características y correcciones de F2PY. -* Muchas nuevas obsolescencias, revísalas. -* Muchas obsolescencias caducadas, +* New "dtype" and "casting" keywords for stacking functions. +* New F2PY features and fixes. +* Many new deprecations, check them out. +* Many expired deprecations, -El lanzamiento de NumPy 1.24.0 continúa el trabajo en curso para mejorar el manejo y promoción de dtypes, aumentar la velocidad de ejecución y clarificar la documentación. Hay un gran número de obsolescencias nuevas y caducadas debido a los cambios en la limpieza y promoción de tipo dtype. Es el trabajo de 177 colaboradores distribuidos sobre 444 solicitudes de incorporación de cambios. Las versiones Python soportadas son 3.8-3.11. +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 ha sido lanzado +### Numpy 1.23.0 released -_22 de junio de 2022_ -- [NumPy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html) ya está disponible. Los aspectos más destacados del lanzamiento son: +_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: -* Implementación de `loadtxt` en C, mejorando enormemente su rendimiento. -* Exposición de DLPack a nivel Python para facilitar el intercambio de datos. -* Cambios a la promoción y comparación de dtypes estructurados. -* Mejoras a 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. -El lanzamiento de NumPy 1.23.0 continúa el trabajo en curso para mejorar el manejo y promoción de dtypes, aumentar la velocidad de ejecución y clarificar la documentación, caducar viejas obsolescencias. Es el trabajo de 151 colaboradores distribuidos sobre 494 solicitudes de incorporación de cambios. Las versiones de Python soportadas por este lanzamiento son 3.8-3.10. Python 3.11 será soportado cuando alcance la etapa rc. +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. -### Estudio de investigación NumFOCUS DEI: llamado a participar +### NumFOCUS DEI research study: call for participation -_13 de abril de 2022_ -- NumPy está trabajando con [NumFOCUS](http://numfocus.org/) en un [proyecto de investigación](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) financiado por la [Fundación Gordon & Betty Moore](https://www.moore.org/) para entender las barreras de participación que enfrentan los colaboradores, especialmente aquellos de grupos históricamente subrepresentados, en la comunidad de software de código abierto. El equipo de investigación quisiera hablar con nuevos colaboradores, desarrolladores y mantenedores del proyecto, y con aquellos que han contribuido en el pasado acerca de sus experiencias uniéndose y contribuyendo a NumPy. +_Apr 13, 2022_ -- NumPy is working with [NumFOCUS](http://numfocus.org/) on a [research project](https://numfocus.org/diversity-inclusion-disc/a-pivotal-time-in-numfocuss-project-aimed-dei-efforts?eType=EmailBlastContent&eId=f41a86c3-60d4-4cf9-86cf-58eb49dc968c) funded by the [Gordon & Betty Moore Foundation](https://www.moore.org/) 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. -**¿Estás interesado en compartir tus experiencias?** +**Interested in sharing your experiences?** -Por favor, completa este breve [formulario de "Interés del Participante"](https://numfocus.typeform.com/to/WBWVJSqe), que contiene información adicional sobre los objetivos de la investigación, la privacidad y las consideraciones de confidencialidad. Tu participación será valiosa para el crecimiento y la sostenibilidad de comunidades de software de código abierto diversas e inclusivas. Los participantes aceptados participarán en una entrevista de 30 minutos con un miembro del equipo de investigación. +Please complete this brief [“Participant Interest” form](https://numfocus.typeform.com/to/WBWVJSqe) 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. -### Lanzamiento de NumPy 1.22.0 +### Numpy 1.22.0 release -_31 de diciembre de 2021_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) ya está disponible. Los aspectos más destacados del lanzamiento son: +_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: -* Las anotaciones de tipo del espacio de nombres principal están esencialmente completas. El repositorio principal (upstream) es un objetivo en movimiento, así que probablemente habrán más mejoras, pero el mayor trabajo ya está hecho. Esta es probablemente la mejora más visible para el usuario en esta versión. -* Una versión preliminar del propuesto [Estándar API de Arreglos](https://data-apis.org/array-api/latest/) es suministrada (véase [NEP 47](https://numpy.org/neps/nep-0047-array-api-standard.html)). Este es un paso en la creación de una colección estándar de funciones que pueden ser usadas a través de librerías como CuPy y JAX. -* NumPy ahora tiene un backend de DLPack. DLPack proporciona un formato de intercambio común para datos de arreglos (tensor). -* Nuevos métodos para `cuantil`, `percentil` y funciones relacionadas. Los nuevos métodos proporcionan un conjunto completo de los métodos comúnmente encontrados en la literatura. -* Las funciones universales se han refactorizado para implementar la mayor parte de [NEP 43](https://numpy.org/neps/nep-0043-extensible-ufuncs.html). Esto también desbloquea la capacidad de experimentar con la futura API DType. -* Un nuevo asignador de memoria configurable para el uso de proyectos dependientes o downstream. +* 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](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 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](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. -NumPy 1.22.0 es un gran lanzamiento que contó con el trabajo de 153 colaboradores distribuidos sobre 609 solicitudes de incorporación de cambios. Las versiones de Python soportadas por este lanzamiento son 3.8-3.10. +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. -### Promoviendo una cultura inclusiva en el ecosistema científico de Python +### Advancing an inclusive culture in the scientific Python ecosystem -_31 de agosto de 2021_ -- Nos complace anunciar que la Iniciativa Chan Zuckerberg ha [otorgado una subvención](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) para apoyar la incorporación, inclusión, y retención de personas de grupos históricamente marginados en proyectos científicos de Python y para mejorar estructuralmente la dinámica de la comunidad para NumPy, SciPy, Matplotlib y Pandas. +_August 31, 2021_ -- We are happy to announce the Chan Zuckerberg Initiative has [awarded a grant](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 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. -Como parte del [Programa de Software Esencial de Código Abierto para la Ciencia de CZI](https://chanzuckerberg.com/eoss/), esta subvención suplementaria de [Diversidad &e Inclusión](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) apoyará la creación de posiciones dedicadas de Líder de Experiencia del Colaborador para identificar, documentar e implementar prácticas para fomentar comunidades inclusivas de código abierto. Este proyecto será liderado por Melissa Mendonça (NumPy), con mentoría y orientación adicionales por parte de Ralf Gommers (NumPy, SciPy), Hannah Aizenman y Thomas Caswell (Matplotlib), Matt Haberland (SciPy), y Joris Van den Bossche (Pandas). +As a part of [CZI's Essential Open Source Software for Science program](https://chanzuckerberg.com/eoss/), this [Diversity & Inclusion supplemental grant](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 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). -Este es un proyecto ambicioso destinado a descubrir e implementar actividades que deberían mejorar estructuralmente la dinámica comunitaria de nuestros proyectos. Al establecer estos nuevos roles entre proyectos, esperamos introducir un nuevo modelo de colaboración para las comunidades de Python Científico, permitiendo que el trabajo de construcción de comunidades dentro del ecosistema se realice de manera más eficiente y con mejores resultados. También esperamos desarrollar una idea más clara tanto de lo que funciona y lo que no en nuestros proyectos, para atraer y retener nuevos colaboradores, especialmente de grupos históricamente subrepresentados. Finalmente, planeamos producir informes detallados sobre las acciones ejecutadas, explicando cómo éstas han impactado nuestros proyectos en términos de representación e interacción con nuestras comunidades. +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. -Se espera que este proyecto, de dos años de duración, comience en noviembre de 2021, y estamos emocionados por ver los resultados de este trabajo! [Puedes leer la propuesta completa aquí](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). +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](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). -### Encuesta de NumPy de 2021 +### 2021 NumPy survey -_12 de julio de 2021_ -- En NumPy creemos en el poder de nuestra comunidad. 1,236 usuarios de NumPy de 75 países participaron en nuestra encuesta inaugural el año pasado. Los resultados de la encuesta nos dieron una muy buena comprensión acerca de lo que debería ser nuestro enfoque durante los próximos 12 meses. +_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. -Es hora de otra encuesta, y contamos contigo una vez más. Te tomará alrededor de 15 minutos de tu tiempo. Además de inglés, el cuestionario de la encuesta está disponible en 8 idiomas adicionales: Bangla, Francés, Hindi, Japonés, Mandarín, Portugués, Ruso y Español. +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. -Sigue el enlace para comenzar: https://berkeley.qualtrics.com/jfe/form/SV_aaOONjgcBXDSl4q. +Follow the link to get started: https://berkeley.qualtrics.com/jfe/form/SV_aaOONjgcBXDSl4q. -### Lanzamiento de NumPy 1.21.0 +### Numpy 1.21.0 release -_23 de junio de 2021_ -- [NumPy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) ya está disponible. Los aspectos más destacados de esta versión son: +_Jun 23, 2021_ -- [NumPy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) is now available. Los aspectos más destacados de esta versión son: -- trabajo SIMD continuo que cubre más funciones y plataformas, -- trabajo inicial sobre la nueva infraestructura dtype y conversiones de tipo, -- universal2 wheels para Python 3.8 y Python 3.9 en Mac, -- documentación mejorada, -- anotaciones mejoradas, -- nuevo `PCG64DXSM` generador de bits para números aleatorios. +- 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. -Esta versión de NumPy es el resultado de 581 solicitudes de incorporación de cambios contribuidas por 175 personas. Las versiones de Python soportadas por este lanzamiento son las 3.7-3.9, se añadirá soporte para Python 3.10 después del lanzamiento de Python 3.10. +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. -### Resultados de la encuesta de NumPy de 2020 +### 2020 NumPy survey results -_22 de junio de 2021_ -- En 2020, el equipo de encuestas de NumPy, en asociación con los estudiantes y profesores de la Universidad de Michigan y la Universidad de Maryland, realizó la primera encuesta oficial de la comunidad NumPy. Encuentra los resultados de la encuesta aquí: https://numpy.org/user-survey-2020/. +_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/. -### Lanzamiento de NumPy 1.20.0 +### Numpy 1.20.0 release -_30 de enero de 2021_ -- [NumPy 1.20.0](https://numpy.org/doc/stable/release/1.20.0-notes.html) ya está disponible. Este es el lanzamiento de NumPy más grande hasta la fecha, gracias a los más de 180 colaboradores. Las dos nuevas características más importantes son: -- Anotaciones de tipo para grandes partes de NumPy, y un nuevo submódulo `numpy.typing` que contiene los alias `ArralyLike` y `DtypeLike` que los usuarios y las librerías dependientes o downstream pueden usar al agregar anotaciones de tipo en su propio código. -- Optimizaciones de compilador SIMD multiplataforma, con soporte para instrucciones x86 (SSE, AVX), ARM64 (Neon) y PowerPC (VSX). Esto produjo mejoras significativas de rendimiento para muchas funciones (ejemplos: [sin/cos](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). +_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. +- 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](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). -### Diversidad en el proyecto NumPy +### Diversity in the NumPy project -_20 de septiembre de 2020_ -- Escribimos una [declaración sobre el estado de, y discusión en redes sociales, alrededor de la diversidad e inclusión en el proyecto NumPy](/diversity_sep2020). +_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). -### Primer artículo oficial de NumPy publicado en Nature! +### First official NumPy paper published in Nature! -_16 de septiembre de 2020_ -- Nos complace anunciar la publicación del [primer artículo oficial sobre NumPy](https://www.nature.com/articles/s41586-020-2649-2) como artículo de revisión en Nature. Esto llega 14 años después de la publicación de NumPy 1.0. El documento cubre aplicaciones y conceptos fundamentales de programación de arreglos, el rico ecosistema científico de Python construido sobre NumPy, y los recientemente añadidos protocolos de arreglos que facilitan la interoperabilidad con librerías de arreglos y tensores externas, tales como CuPy, Dask y JAX. +_Sep 16, 2020_ -- We are pleased to announce the publication of [the first official paper on NumPy](https://www.nature.com/articles/s41586-020-2649-2) 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 está por llegar, ¿cuándo lanzará NumPy ruedas binarias? +### Python 3.9 is coming, when will NumPy release binary wheels? -_14 de septiembre de 2020_ -- Python 3.9 será lanzado dentro de unas pocas semanas. Si eres uno de los primeros en adoptar las más recientes versiones de Python, es posible que te sientas decepcionado al descubrir que NumPy (y otros paquetes binarios como SciPy) no tendrán ruedas binarias listas para el día del lanzamiento. Es un esfuerzo importante el adaptar la infraestructura de compilación a una versión nueva de Python y normalmente tarda unas cuantas semanas para que los paquetes aparezcan en PyPI y conda-forge. En preparación para este evento, por favor asegúrese de -- actualizar su versión de `pip` al menos a la 20.1 para soportar `manylinux2010` y `manylinux2014` -- utiliza [`--only-binary=numpy`](https://pip.pypa.io/en/stable/reference/pip_install/#cmdoption-only-binary) o `--only-binary=:all:` para evitar que `pip` intente compilar desde la fuente. +_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`](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. -### Lanzamiento de NumPy 1.19.2 +### Numpy 1.19.2 release -_10 de septiembre de 2020_ -- [NumPy 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) ya está disponible. Este último lanzamiento de la serie 1.19 corrige varios errores, se prepara para el [lanzamiento próximo de Cython 3.x](http://docs.cython.org/en/latest/src/changes.html) y fija las versiones de setuptools para mantener distutils funcionando mientras las modificaciones hacia el repositorio principal continúan. Las wheels para aarch64 están construidas con la última versión de manylinux2014 que corrige el problema de diferentes tamaños de página utilizados por diferentes distribuciones de linux. +_Sep 10, 2020_ -- [NumPy 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) is now available. This latest release in the 1.19 series fixes several bugs, prepares for the [upcoming Cython 3.x release](http://docs.cython.org/en/latest/src/changes.html) 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. -### La encuesta inaugural de NumPy ya está disponible! +### The inaugural NumPy survey is live! -_2 de julio de 2020_ -- Esta encuesta está destinada a guiar y establecer prioridades para la toma de decisiones sobre el desarrollo de NumPy como software y como comunidad. La encuesta está disponible en 8 idiomas adicionales además del Inglés: Bangla, Hindi, Japonés, Mandarín, Portugués, Ruso, Español y Francés. +_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. -Por favor ayúdanos a mejorar NumPy diligenciando la encuesta: [aquí](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). +Please help us make NumPy better and take the survey [here](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). -### ¡NumPy tiene un nuevo logo! +### NumPy has a new logo! -_24 de junio de 2020_ -- NumPy tiene ahora un nuevo logo: +_Jun 24, 2020_ -- NumPy now has a new logo: -Logo de NumPy +NumPy logo -El logo es una versión moderna del anterior, con un diseño más limpio. Gracias a Isabela Presedo-Floyd por diseñar el nuevo logo, así como a Travis Vaught por el viejo logo que nos sirvió tanto durante más de 15 años. +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. -### Lanzamiento de NumPy 1.19.0 +### NumPy 1.19.0 release -_20 de junio de 2020_ -- NumPy 1.19.0 ya está disponible. Esta es el primer lanzamiento sin soporte para Python 2, por lo que fue una "versión de limpieza". La versión mínima soportada de Python es ahora Python 3.6. Una nueva característica importante es que la infraestructura de generación de números aleatorios que fue introducida en NumPy 1.17.0 es ahora accesible desde Cython. +_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. -### Aceptación a Season of Docs +### Season of Docs acceptance -_11 de mayo de 2020_ -- NumPy ha sido aceptado como una de las organizaciones mentoras para el programa Google Season of Docs. ¡Estamos entusiasmados de tener la oportunidad de trabajar con un redactor técnico para mejorar la documentación de NumPy una vez más! Para más detalles, por favor consulte [el sitio oficial de Season of Docs](https://developers.google.com/season-of-docs/) y nuestra [página de ideas](https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2020-Project-Ideas). +_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](https://developers.google.com/season-of-docs/) and our [ideas page](https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2020-Project-Ideas). -### Lanzamiento de NumPy 1.18.0 +### NumPy 1.18.0 release -_22 de diciembre de 2019_ -- NumPy 1.18.0 ya está disponible. Después de los grandes cambios en 1.17.0, este es un lanzamiento de consolidación. Es el último lanzamiento menor que soportará Python 3.5. Los aspectos más destacados de la publicación incluyen la adición de la infraestructura básica para enlazar con las librerías BLAS de 64 bits y LAPACK, y un nuevo C-API para `numpy.random`. +_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`. -Por favor revise las [notas del lanzamiento](https://github.com/npm/npm/releases/tag/v2.11.0) para conocer más detalles. +Please see the [release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0) for more details. -### NumPy recibe una subvención de la Iniciativa Chan Zuckerberg +### NumPy receives a grant from the Chan Zuckerberg Initiative -_15 de noviembre de 2019_ -- Nos complace anunciar que NumPy y OpenBLAS, una de las dependencias clave de NumPy, han recibido una subvención conjunta por $195,000 de la Iniciativa Chan Zuckerberg a través de su [programa Esencial de Software Abierto para la Ciencia](https://chanzuckerberg.com/eoss/) que apoya el mantenimiento de software, crecimiento, desarrollo y compromiso comunitario para herramientas de código abierto críticas para la ciencia. +_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. -Esta subvención se utilizará para acelerar los esfuerzos en la mejora de la documentación de NumPy, rediseño del sitio web y desarrollo de la comunidad para servir mejor a nuestra amplia y creciente base de usuarios, y asegurar la sostenibilidad a largo plazo del proyecto. Mientras que el equipo de OpenBLAS se enfocará en abordar conjuntos de problemas técnicos clave, en particular la seguridad de los hilos, AVX-512, y problemas de almacenamiento local de hilos (TLS), así como mejoras algorítmicas en ReLAPACK (Recursive LAPACK) de las que depende OpenBLAS. +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. -Puede encontrar más detalles sobre nuestras iniciativas y entregables propuestos en la [propuesta completa de subvención](https://figshare.com/articles/Proposal_NumPy_OpenBLAS_for_Chan_Zuckerberg_Initiative_EOSS_2019_round_1/10302167). Está previsto que el trabajo comience el 1 de diciembre de 2019 y continúe durante los siguientes 12 meses. +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. -## Lanzamientos +## Releases -Esta es una lista de lanzamientos NumPy, con enlaces a notas de lanzamiento. Los lanzamientos de corrección de errores (solo cambia la `z` en el número de versión `x.y.z`) no tienen nuevas características; las versiones menores (aumenta la `y`) sí las tienen. +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. - NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. - NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. - NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. -- NumPy 2.1.1 ([notas de lanzamiento](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 de septiembre 2024_. -- NumPy 2.0.2 ([notas de lanzamiento](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 de agosto 2024_. -- NumPy 2.1.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 de agosto de 2024_. -- NumPy 2.0.1 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 de julio de 2024_. -- NumPy 2.0.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 de junio de 2024_. -- NumPy 1.26.4 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 de febrero de 2024_. -- NumPy 1.26.3 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 de enero de 2024_. -- NumPy 1.26.2 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _12 de noviembre de 2023_. -- NumPy 1.26.1 ([notas de publicación](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 de octubre de 2023_. -- NumPy 1.26.0 ([notas de publicación](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 de septiembre de 2023_. -- NumPy 1.25.2 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 de julio de 2023_. -- NumPy 1.25.1 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 de julio de 2023_. -- NumPy 1.24.4 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 de junio de 2023_. -- NumPy 1.25.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 de junio de 2023_. -- NumPy 1.24.3 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 de abril de 2023_. -- NumPy 1.24.2 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 de febrero de 2023_. -- NumPy 1.24.1 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 de diciembre de 2022_. -- NumPy 1.24.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 de diciembre de 2022_. -- NumPy 1.23.5 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _19 de noviembre de 2022_. -- NumPy 1.23.4 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 de octubre de 2022_. -- NumPy 1.23.3 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 de septiembre de 2022_. -- NumPy 1.23.2 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 de agosto de 2022_. -- NumPy 1.23.1 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 de julio de 2022_. -- NumPy 1.23.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 de junio de 2022_. -- NumPy 1.22.4 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 de mayo de 2022_. -- NumPy 1.21.6 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 de abril de 2022_. -- NumPy 1.22.3 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 de marzo de 2022_. -- NumPy 1.22.2 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 de febrero de 2022_. -- NumPy 1.22.1 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 de enero de 2022_. -- NumPy 1.22.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 de diciembre de 2021_. -- NumPy 1.21.5 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 de diciembre de 2021_. -- NumPy 1.21.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 de junio de 2021_. -- NumPy 1.20.3 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 de mayo de 2021_. -- NumPy 1.20.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 de enero de 2021_. -- NumPy 1.19.5 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 de enero de 2021_. -- NumPy 1.19.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 de junio de 2020_. -- NumPy 1.18.4 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 de mayo de 2020_. -- NumPy 1.17.5 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 de enero de 2020_. -- NumPy 1.18.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 de diciembre de 2019_. -- NumPy 1.17.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 de julio de 2019_. -- NumPy 1.16.0 ([notas de lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. -- NumPy 1.15.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 de julio de 2018_. -- NumPy 1.14.0 ([notas del lanzamiento](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 de enero de 2018_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. +- NumPy 1.26.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 Nov 2023_. +- NumPy 1.26.1 ([notas de publicación](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 Oct 2023_. +- NumPy 1.26.0 ([notas de publicación](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 Sep 2023_. +- NumPy 1.25.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.2)) -- _31 Jul 2023_. +- NumPy 1.25.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.1)) -- _8 Jul 2023_. +- NumPy 1.24.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.4)) -- _26 Jun 2023_. +- NumPy 1.25.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.25.0)) -- _17 Jun 2023_. +- NumPy 1.24.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.3)) -- _22 Apr 2023_. +- NumPy 1.24.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.2)) -- _5 Feb 2023_. +- NumPy 1.24.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.1)) -- _26 Dec 2022_. +- NumPy 1.24.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.24.0)) -- _18 Dec 2022_. +- NumPy 1.23.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.5)) -- _19 Nov 2022_. +- NumPy 1.23.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.4)) -- _12 Oct 2022_. +- NumPy 1.23.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.3)) -- _9 Sep 2022_. +- NumPy 1.23.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.2)) -- _14 Aug 2022_. +- NumPy 1.23.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.1)) -- _8 Jul 2022_. +- NumPy 1.23.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.23.0)) -- _22 Jun 2022_. +- NumPy 1.22.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _20 May 2022_. +- NumPy 1.21.6 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.6)) -- _12 Apr 2022_. +- NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. +- NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. +- NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. +- NumPy 1.22.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 Dec 2021_. +- NumPy 1.21.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 Dec 2021_. +- NumPy 1.21.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 Jun 2021_. +- NumPy 1.20.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 May 2021_. +- NumPy 1.20.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 Jan 2021_. +- NumPy 1.19.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 Jan 2021_. +- NumPy 1.19.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 Jun 2020_. +- NumPy 1.18.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 May 2020_. +- NumPy 1.17.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 Jan 2020_. +- NumPy 1.18.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 Dec 2019_. +- NumPy 1.17.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 Jul 2019_. +- NumPy 1.16.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. +- NumPy 1.15.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 Jul 2018_. +- NumPy 1.14.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 Jan 2018_. From 645139f378e6bf0106b2bbbf394128fe1dabce9a Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:34:51 +0100 Subject: [PATCH 13/17] New translations news.md (Arabic) --- content/ar/news.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/content/ar/news.md b/content/ar/news.md index 08bd83d7f0..7a7aba23fe 100644 --- a/content/ar/news.md +++ b/content/ar/news.md @@ -1,5 +1,5 @@ --- -title: الأخبار +title: News sidebar: false newsHeader: "NumPy 2.2.0 released!" date: 2024-12-8 @@ -270,7 +270,7 @@ More details on our proposed initiatives and deliverables can be found in the [f -## الإصدارات +## 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. From 06b683d66de11bfbf5a4c5c0c13493a8df007d9f Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:34:53 +0100 Subject: [PATCH 14/17] New translations news.md (Japanese) --- content/ja/news.md | 40 ++++++++++++++++++++-------------------- 1 file changed, 20 insertions(+), 20 deletions(-) diff --git a/content/ja/news.md b/content/ja/news.md index acd02d628f..673f5021fa 100644 --- a/content/ja/news.md +++ b/content/ja/news.md @@ -20,24 +20,24 @@ This release supports Python versions 3.10-3.13. ### NumPy 1.26.0 がリリースされました。 -_2024 Aug, 2024_ -- Numpy 2.1.0 は Python 3.13 をサポートし、Python 3.9をサポート外としました。 今回のリリースは通常のバグ修正やPythonサポートの更新に加えて、NumPyが2.0の長期開発を経て、通常のリリースサイクルに戻るためのリリースでもあります。 今回のリリースのハイライトは下記の通りです。 +_18 Aug, 2024_ -- NumPy 2.1.0 provides support for Python 3.13 and drops support for Python 3.9. In addition to the usual bug fixes and 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: - Python 3.12.0 のサポート - 多くの期限切れの非推奨(Deprecation)の削除 -- Array-api 2023.12 標準のサポート +- Support for the array-api 2023.12 standard. -Python バージョン 3.10-3.13 か、このリリースでサポートされています。 +Python versions 3.10-3.13 are supported by this release. ### 多くの新しい非推奨(Deprecation)の追加 -_2024年6月16日_ -- Numpy 2.0.0 は2006年以来のメジャーリリースです。 これは、前回の機能リリースから11か月間の開発の成果であり、1078件のプルリクエストにわたる212人の貢献者の成果となります。 このリリースには、大きく、エキサイティングな新機能と、PythonとCの両方のAPIへの変更が含まれています。 今回のリリースが、通常のマイナーリリースでは実施できなかった互換性を破壊する変更を含んでいます。これには、ABIの破壊、型昇格ルールの変更、および1.26.xでは非推奨警告が出されていなかった可能性のあるAPIの変更が含まれています。 NumPy 2.0の変更に対応する方法に関する主要なドキュメントは次のとおりです。 +_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 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: -- [NumPy 2.0移行ガイド](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- [2.0.0 リリースノート](https://numpy.org/devdocs/release/2.0.0-notes.html) -- ステータス更新のお知らせイシューチケット: [numpy#24300](https://github.com/numpy/numpy/issues/24300) +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) -ブログ記事 ["NumPy 2.0: 進化のマイルストーン"](https://blog.scientific-python.org/numpy/numpy2/) は、今回のメジャーバージョンリリースがどのようにして決定されたかについてのストーリーを少し伝えています。 +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 1.25.0 リリース @@ -56,7 +56,7 @@ _2023年12月19日_ -- NumFOCUSは、年末キャンペーンでPyCharmチーム ### NumPy 1.20.0 リリース -_2022年12月18日_ -- [Numpy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html) がリリースされました。 今回のリリースのハイライトは次のとおりです。 +_2023年1月17日_ -- [Numpy 1.25.0](https://numpy.org/doc/stable/release/1.25.0-notes.html) がリリースされました。 今回のリリースの目玉機能は次のとおりです。 * Python 3.12.0 のサポート * Cython 3.0.0 との互換性 @@ -95,7 +95,7 @@ _日本語：_ ### Numpy 1.23.0 リリース -_2022年1月22日_ -- [Numpy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html) がリリースされました。 今回のリリースのハイライトは次のとおりです。 +_2022年12月18日_ -- [Numpy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html) がリリースされました。 今回のリリースのハイライトは次のとおりです。 * MUSLのサポート。 MUSLのWheelが準備されました。 * 富士通のC/C++コンパイラサポート @@ -120,7 +120,7 @@ _2023年1月6日_ –- Mukulika PahariとRoss Barnowskiは、Melissa MendoncAudi ### NumPy 1.24.0 リリース -_2021年1月23日_ -- [Numpy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) がリリースされました。 今回のリリースのハイライトは下記の通りです。 +_2022年1月22日_ -- [Numpy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html) がリリースされました。 今回のリリースのハイライトは次のとおりです。 * スタッキング関数のための新しい"dtype"と"casting"キーワードの追加 * F2PYの新機能追加とバグ修正 @@ -131,7 +131,7 @@ Numpy 1.25. リリースは引き続きdtypeの取り扱いと dtypeのプロモ ### Numpy 1.26.0 は 1.25 からの互換性を保持しています。 -_2021年12月31日_ -- [Numpy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) がリリースされました。 今回のリリースの目玉機能は次のとおりです。 +_2021年1月23日_ -- [Numpy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) がリリースされました。 今回のリリースのハイライトは下記の通りです。 * `loadtxt` がCで実装されたことによる、大幅なパフォーマンス向上 * より簡単なデータ交換のためのPythonレベルでのDLPackの公開 @@ -150,7 +150,7 @@ _2022年4月13日_ -- NumPyは、[NumFOCUS](http://numfocus.org/)と協力して ### NumPy 1.19.2 リリース -_2023年9月16日_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html)がリリースされました。 今回のリリースの目玉機能は次のとおりです。 +_2021年12月31日_ -- [Numpy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) がリリースされました。 今回のリリースの目玉機能は次のとおりです。 * メインの名前空間の型アノテーションは基本的に完了しました。 上流のコードは常に変化するものなので、さらなる改良が必要でしょうが、大きな作業は終わったと考えています。 これはおそらく、今回のリリースで最も目に見える改良でしょう。 * 以前から提案されていた [array API 標準](https://data-apis.org/array-api/latest/) のベータ版が提供されています ( [NEP 47](https://numpy.org/neps/nep-0047-array-api-standard.html) を参照) 。 これは、CuPy や JAX などのライブラリで使用できる 関数の標準的なコレクションを作成するために必要なステップです。 @@ -182,7 +182,7 @@ _2021年7月12日_ -- NumPy ではコミュニティの力を信じています ### Numpy 1.18.0 リリース -_2023年1月17日_ -- [Numpy 1.25.0](https://numpy.org/doc/stable/release/1.25.0-notes.html) がリリースされました。 今回のリリースの目玉機能は次のとおりです。 +_2023年9月16日_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html)がリリースされました。 今回のリリースの目玉機能は次のとおりです。 - より多くの機能やプラットフォームをカバーするためのSIMD関連の改善が実施されました。 - dtypeのための新しいインフラとキャストの準備 @@ -276,14 +276,14 @@ _2019年11月15日_ -- NumPyと、NumPyの重要な依存ライブラリの1つ - NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. - NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. -- NumPy 2.1.2 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _2024年10月5日_. -- NumPy 2.1.1 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _2024年9月3日_. -- NumPy 2.0.2 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _2024年8月26日_. -- NumPy 2.1.0 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _2024年8月18日_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. - NumPy 1.22.4 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v1.22.4)) -- _2022年5月20日_. -- NumPy 2.0.0 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _2024年6月16日_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. - NumPy 1.26.3 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _ 2024年1月2日_. -- NumPy 1.26.3 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _ 2024年1月2日_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. - NumPy 1.26.2 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _2023年11月12日_. - NumPy 1.26.1 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _2023年10月14日_. - NumPy 1.26.0 ([リリースノート](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _2023年9月16日_. From 28379a9d888fbb71aaca918294f8fa500d3f9a9b Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:34:54 +0100 Subject: [PATCH 15/17] New translations news.md (Korean) --- content/ko/news.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/content/ko/news.md b/content/ko/news.md index 4fb6664900..0808edd6ca 100644 --- a/content/ko/news.md +++ b/content/ko/news.md @@ -33,9 +33,9 @@ Python versions 3.10-3.13 are supported by this release. _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 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: -- [NumPy 2.0 이주 가이드](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- [2.0.0 릴리즈 노트](https://numpy.org/devdocs/release/2.0.0-notes.html) -- 상태 업데이트 공지용 이슈: [numpy#24300](https://github.com/numpy/numpy/issues/24300) +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) 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. From 065094504da17eaa92b62daa6a99d693fcffe924 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:34:57 +0100 Subject: [PATCH 16/17] New translations news.md (Chinese Simplified) --- content/zh/news.md | 164 ++++++++++++++++++++++----------------------- 1 file changed, 82 insertions(+), 82 deletions(-) diff --git a/content/zh/news.md b/content/zh/news.md index 8f47d8b76c..7a7aba23fe 100644 --- a/content/zh/news.md +++ b/content/zh/news.md @@ -1,5 +1,5 @@ --- -title: 社区快讯 +title: News sidebar: false newsHeader: "NumPy 2.2.0 released!" date: 2024-12-8 @@ -56,7 +56,7 @@ Use unique URL that will allow to track purchases https://lp.jetbrains.com/suppo ### 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. 此次发布的重点是： +_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. @@ -95,7 +95,7 @@ Looking ahead, we’d love to translate the website into more languages. If you ### 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. 此次发布的重点是： +_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. @@ -120,7 +120,7 @@ _Jan 6, 2023_ –- Mukulika Pahari and Ross Barnowski are appointed as the new N ### NumPy 1.24.0 released -_Dec 18, 2022_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html) is now available. 此次发布的重点是： +_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. @@ -131,7 +131,7 @@ The NumPy 1.24.0 release continues the ongoing work to improve the handling and ### Numpy 1.23.0 released -_Jun 22, 2022_ -- [NumPy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html) is now available. 此次发布的重点是： +_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. @@ -148,131 +148,131 @@ _Apr 13, 2022_ -- NumPy is working with [NumFOCUS](http://numfocus.org/) on a [r Please complete this brief [“Participant Interest” form](https://numfocus.typeform.com/to/WBWVJSqe) 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 发布 +### Numpy 1.22.0 release -_2021年6月31日_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) 正式发布。 此次发布的重点是： +_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: -* 主命名空间的注释类型基本上已完成。 上游是个移动目标，所以很可能会有进一步的改进，但是主要的 项工作已经完成。 这可能是本次发布中用户最可见的增强功能。 -* 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)). 这是创建一个可以在 CuPy 和 JAX 等库中使用的函数的标准收藏的一个步骤。 -* NumPy 现在有一个 DLPack 后端。 DLPack提供了一个数组 (tensor) 数据的通用交换格式。 -* `量化`, `百分比`以及相关函数的新方法。 新的 方法提供了一整套常见于 文献中的方法。 -* 通用函数已被重新考虑，以实现大多数的 [NEP 43](https://numpy.org/neps/nep-0043-extensible-ufuncs.html) 这也会解锁实验未来DType API的能力。 -* 一个新的可配置内存分配器，供下游项目使用。 +* 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](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 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](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. -NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. 此版本支持的 Python 版本是 3.8-3.10。 +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. -### 促进Python科学生态系统中的包容性文化 +### Advancing an inclusive culture in the scientific Python ecosystem -_8月31日， 2021_ — 我们很高兴宣布Chan Zuckerberg倡议 [授予赠款](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 以支持历史上被边缘化群体的人在科学Python项目中的融入、包容和留存，并为NumPy、SciPy、Matplotlib和Pandas的社区动态进行结构性改善。 +_August 31, 2021_ -- We are happy to announce the Chan Zuckerberg Initiative has [awarded a grant](https://chanzuckerberg.com/newsroom/czi-awards-16-million-for-foundational-open-source-software-tools-essential-to-biomedicine/) 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. -作为 [CZI 基本开放源码科学程序](https://chanzuckerberg.com/eoss/)的一部分， 这 个[多样性 & 包容性补充赠款](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 将支持创建专门的负责人职位，以确定、记录和实施促进包容性开源社区的实践。 这个项目将由Melissa Mendoncstima (NumPy) 领导，由Ralf Gommers (NumPy, SciPy) Hannah Aizenman and Thomas Caswell (Matplotlib), Matt Haberland (SciPy), and Joris Van den Bossche (Pandas)， 提供 额外的辅导和指导 +As a part of [CZI's Essential Open Source Software for Science program](https://chanzuckerberg.com/eoss/), this [Diversity & Inclusion supplemental grant](https://cziscience.medium.com/advancing-diversity-and-inclusion-in-scientific-open-source-eaabe6a5488b) 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). -这是一个雄心勃勃的项目，旨在发现和执行 应该从结构上改善我们项目的社区动态的活动。 通过 建立这些新的跨项目角色，我们希望在Scientific Python社区引进一个新的 协作模型。 使生态系统中的 社区建设工作能够更有效地开展， 取得更大的成果。 我们还希望在项目中了解什么有效，什么无效，以吸引和留住来自历史上未被代表的群体的新贡献者，建立更清晰的认知。 最后，我们计划制作详细的报告，说明我们采取的措施如何在代表性和与社区互动方面对我们的项目产生影响。 +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. -这个为期两年的项目预计将于2021年11月开始，我们很期待看到这项工作的成果! [您可以在这里阅读完整的提案](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063)。 +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](https://figshare.com/articles/online_resource/Advancing_an_inclusive_culture_in_the_scientific_Python_ecosystem/16548063). -### 2021 Numpy调查 +### 2021 NumPy survey -_2021年7月12日_ -- 我们相信NumPy社区的力量。 来自75个国家的1236 名用户参加了我们去年的首次调查。 调查结果使我们对今后12个月应该集中注意的问题有了很好的了解。 +_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. -现在是时候进行另一次调查了，我们将再度尋求您的合作。 这份调查将耗费您大约15分钟的时间。 除英文外，调查问卷还提供另外8种语文：孟加拉语、法语、印地语、日语、普通话、葡萄牙语、俄语和西班牙语。 +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. -点击链接开始：https://berkeley.qualtrics.com/jfe/form/SV_aOONjgcBXDSl4q。 +Follow the link to get started: https://berkeley.qualtrics.com/jfe/form/SV_aaOONjgcBXDSl4q. -### NumPy 1.21.0 发布 +### Numpy 1.21.0 release -_2021年6月23日_ -- [NumPy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) 正式发布。 此次发布的重点是： +_Jun 23, 2021_ -- [NumPy 1.21.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) is now available. The highlights of the release are: -- 继续开展SIMD工作，涵盖更多的功能和平台 -- 新dtype的基础和型态转换初步工作 -- 适用于Mac平台的Python 3.8和Python 3.9的universal2 wheels -- 改进文档 -- 改进注释 -- 新的 `PCG64DXSM` 位元生成器，用于生成随机数字 +- 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. -这个NumPy版本包含175人所贡献的581个合并请求。 此发布版本支持Python 3.7-3.9，将在Python 3.10发布后添加Python 3.10支持。 +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调研结果结果 +### 2020 NumPy survey results -_2021年6月22日_ -- 在2020年, NumPy调研小组与密歇根大学和马里兰大学的学生和教职员工合作，进行了第一次官方NumPy社区调查。 在这里可以查看调研结果：https://numpy.org/user-survey-2020/。 +_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 发布 +### Numpy 1.20.0 release -_2021年1月30日_ -- [NumPy 1.20.0](https://numpy.org/doc/stable/release/1.21.0-notes.html) 正式发布。 这是 NumPy到目前为止最大的一次版本更新，感谢180+位贡献者。 最令人振奋的两个特点是： -- 为大部分Numpy代码做了类型注解，並添加了一个全新的`numpy.typing` 子模块，其中包含 `ArrayLike` 和 `DtypeLike`别名 ，使得用户和下游依赖库可以为自己的代码添加类型注解。 -- 为多个架构进行SIMD编译优化，其支持X86(SSE、AVX)、ARM64(Neon) 和PowerPC(VSX) 指令集。 大幅提高许多函数的性能(例如： [sin/cos](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194))。 +_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. +- 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](https://github.com/numpy/numpy/pull/17587), [einsum](https://github.com/numpy/numpy/pull/18194)). -### NumPy项目的多样性 +### Diversity in the NumPy project -_2020年9月20日_ -- 我们就NumPy项目的社交媒体、多样性和包容性的现状以及相关的讨论撰写了一份[声明](/diversity_sep2020)。 +_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). -### NumPy官方第一次在Nature发表论文！ +### First official NumPy paper published in Nature! -_2020年9月16日_ - 我们高兴地宣布 [Numpy的第一篇官方论文](https://www.nature.com/articles/s41586-020-2649-2)刊登在Nature的评论文章。 这离NumPy 1.0发布已经过去了整整14年。 这篇论文涵盖了数组编程的应用和基本概念，基于NumPy构建的丰富科学Python生态系统，以及最近添加的数组协议，以促进与外部数组和张量库（如CuPy、Dask和JAX）的互操作性。 +_Sep 16, 2020_ -- We are pleased to announce the publication of [the first official paper on NumPy](https://www.nature.com/articles/s41586-020-2649-2) 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 即将来临，新版本的NumPy 将在何时发布？ +### Python 3.9 is coming, when will NumPy release binary wheels? -_2020年9月14日_ -- Python 3.9 将在几周后发布。 如果您是这个Python版本的早期采用者， 您可能会失望的发现NumPy(以及其他二进制软件包，如SciPy) 在Python新版发布当天还不会发布相应的版本。 构建兼容新的 Python 版本的基础设施需要付出重大努力，通常需要几周时间才能让新版本出现在 PyPI 和 conda-forge 上。 为了这次版本升级得以顺利进行，请确保： -- 将您的 `pip` 升级到 20.1 版本，至少要支持`manylinux2010` 和 `manylinux2014` -- 使用 [`--only-binary=numpy`](https://pip.pypa.io/en/stable/reference/pip_install/#cmdoption-only-binary) 或 `--only-binary=:all:` 选项来防止 `pip` 尝试从源码构建。 +_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`](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 发布 +### Numpy 1.19.2 release -_2020年9月10日_ -- [NumPy 19.2.0](https://numpy.org/devdocs/release/1.19.2-notes.html) 正式发布。 这个最新版本修复了1.19 系列中的几个漏洞，为 [即将发布的Cython3.x](http://docs.cython.org/en/latest/src/changes.html) 做准备，並固定设置工具以在上游修改正在进行时保持 distutils 工作。 Aarch64架构的安装包是用最新的 manylinux2014 版本构建的，它修复了 linux 发行版之间使用不同大小内存页的问题。 +_Sep 10, 2020_ -- [NumPy 1.19.2](https://numpy.org/devdocs/release/1.19.2-notes.html) is now available. This latest release in the 1.19 series fixes several bugs, prepares for the [upcoming Cython 3.x release](http://docs.cython.org/en/latest/src/changes.html) 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. -### 首次NumPy调研即将开始！ +### The inaugural NumPy survey is live! -_Jul 2, 2020_ - 本次调查旨在指导并确定 关于开发NumPy 作为软件和社区的决策重点。 除英文外，调查还提供了另外8种语言的版本：孟加拉语、印地语、日语、普通话、葡萄牙语、俄语、西班牙语和法语。 +_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. -请帮助我们让 NumPy 变得更好，在[这里](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl)参与调查。 +Please help us make NumPy better and take the survey [here](https://umdsurvey.umd.edu/jfe/form/SV_8bJrXjbhXf7saAl). -### NumPy 有新标志了! +### NumPy has a new logo! -_2020年7月24日_ -- NumPy 现在有一个新的标志： +_Jun 24, 2020_ -- NumPy now has a new logo: -NumPy 标志 +NumPy logo -这个标志是对旧标志的现代化演绎，采用更加简洁的设计。 感谢Isabela Presedo-Floryd的设计方案， 同时感谢Travis Vaugh设计的旧图标为我们服务了15年以上。 +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 发布 +### NumPy 1.19.0 release -_2020年6月20日_ -- NumPy 1.19.0 正式发布。 这是第一个不支持Python 2的版本，因此它是一个“清理版本”。 目前支持的最低Python 版本是 Python 3.6。 本版本拥有一个重要的新特性，NumPy 1.17.0引进的随机数字生成基础模块现在可以通过Cython访问。 +_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. -### 文档整改时段 +### Season of Docs acceptance -_2020年5月11日_ -- NumPy 已成为Google Season 文档项目之一。 我们很高兴看到有机会和技术写作者一起再次改进NumPy的技术文档！ 更多详情，请参考 [文档整改时段官方网站](https://developers.google.com/season-of-docs/) 和我们的 [意见页面](https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2020-Project-Ideas)。 +_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](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 发布 +### NumPy 1.18.0 release -_2019年12月22日_ -- NumPy 1.18.0 正式发布。 在1.17.0发生重大变化后，这是一个合并版本。 这是最后一个支持 Python 3.5的小版本。 该版本的重要更新包括两个，添加了与64位 BLAS 和 LAPACK 库有关的底层更新， 添加 一个用于`numpy.random`的新C-API更新。 +_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`. -详情请看 [版本说明](https://github.com/numpy/numpy/releases/tag/v1.18.0)。 +Please see the [release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0) for more details. -### NumPy 从Chan Zuckerberg Initiative获得了一笔捐款 +### NumPy receives a grant from the Chan Zuckerberg Initiative -_2019年11月15日_ -- 我们高兴地宣布NumPy和 OpenBLAS (Numpy的一个核心依赖库)已经收到一笔19,5000美元的联合赠款。 捐款来自于Chan Zuckerberg Initiative通过的[基础开源科学计算软件项目](https://chanzuckerberg.com/eoss/)，用来支持对科学发展起到关键作用的开源软件的维护、增长、开发和社区参与。 +_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. -这笔赠款将用来加速改进NumPy文档、网站重构和社区开发，进而更好地为我们庞大和迅速增长的用户基础服务，并确保项目的长期可持续性。 OpenBLAS 团队将侧重于处理几个关键技术问题，特别是线程安全问题、AVX-512和 thread-local 存储(TLS) 问题，以及OpenBLAS 依赖的 ReLAPACK (递归的LAPACK) 算法改进。 +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. -若想查看更多关于捐款的倡议和交付件的详情，可在 [全额赠款提案](https://figshare.com/articles/Proposal_NumPy_OpenBLAS_for_Chan_Zuckerberg_Initiative_EOSS_2019_round_1/10302167) 中找到。 项目开始于2019年12月1日，今后12个月将持续运作下去。 +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. -## 版本发布 +## Releases -这是NumPy 版本列表，包含了对应版本发布说明的链接。 所有的 bug修复版本(即在 `x.y.z`格式版本号中只有 `z`改变)没有新功能；小版本更新(`y` 改变)有新功能。 +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. - NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. - NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. @@ -306,17 +306,17 @@ _2019年11月15日_ -- 我们高兴地宣布NumPy和 OpenBLAS (Numpy的一个核 - NumPy 1.22.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.3)) -- _7 Mar 2022_. - NumPy 1.22.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.2)) -- _3 Feb 2022_. - NumPy 1.22.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.1)) -- _14 Jan 2022_. -- NumPy1.22.0 (发行说明) -- _2021年12月31日_. -- NumPy1.21.5 (发行说明) -- _2021年12月19日_. -- NumPy1.21.0 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _2021年6月22日_. -- NumPy1.23.0 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _2021年5月10日_. -- NumPy1.20.0 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _2021年1月30日_. -- NumPy1.19.5 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _2021年1月5日_. -- NumPy1.19.0 ([发行说明](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _2020年6月20日_. -- NumPy1.18.4 (发行说明) -- _2020年5月3日_. -- NumPy1.17.5 (发行说明) -- _2020年1月1日_. -- NumPy1.18.0 (发行说明) -- _2019年12月22日_. -- NumPy1.17.0 (发行说明) -- _2019年7月26日_. -- NumPy1.16.0 (发行说明) -- _2019年1月14日_. -- NumPy1.15.0 (发行说明) -- _2018年7月23日_. -- NumPy1.14.0 (发行说明) -- _2018年1月7日_. +- NumPy 1.22.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.22.0)) -- _31 Dec 2021_. +- NumPy 1.21.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.5)) -- _19 Dec 2021_. +- NumPy 1.21.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.21.0)) -- _22 Jun 2021_. +- NumPy 1.20.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.3)) -- _10 May 2021_. +- NumPy 1.20.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.20.0)) -- _30 Jan 2021_. +- NumPy 1.19.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.5)) -- _5 Jan 2021_. +- NumPy 1.19.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.19.0)) -- _20 Jun 2020_. +- NumPy 1.18.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.4)) -- _3 May 2020_. +- NumPy 1.17.5 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.5)) -- _1 Jan 2020_. +- NumPy 1.18.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.18.0)) -- _22 Dec 2019_. +- NumPy 1.17.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.17.0)) -- _26 Jul 2019_. +- NumPy 1.16.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.16.0)) -- _14 Jan 2019_. +- NumPy 1.15.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.15.0)) -- _23 Jul 2018_. +- NumPy 1.14.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.14.0)) -- _7 Jan 2018_. From e4acc20092f2d6350dedcb461bcb29bb1ce9d3c6 Mon Sep 17 00:00:00 2001 From: Ralf Gommers Date: Sun, 8 Dec 2024 20:34:58 +0100 Subject: [PATCH 17/17] New translations news.md (Portuguese, Brazilian) --- content/pt/news.md | 56 +++++++++++++++++++++++----------------------- 1 file changed, 28 insertions(+), 28 deletions(-) diff --git a/content/pt/news.md b/content/pt/news.md index cfb217bcc7..3195ef5e47 100644 --- a/content/pt/news.md +++ b/content/pt/news.md @@ -20,33 +20,33 @@ This release supports Python versions 3.10-3.13. ### Lançado o NumPy versão 1.26.0 -_18 de agosto, 2024_ -- NumPy 2.1.0 fornece suporte para Python 3.13 e remove suporte para Python 3.9. Além das habituais correções de erros e suporte a Python atualizado, esta versão ajuda a trazer o NumPy de volta ao ciclo habitual de lançamento após o longo desenvolvimento da versão 2.0. Os destaques desta versão são: +_18 Aug, 2024_ -- NumPy 2.1.0 provides support for Python 3.13 and drops support for Python 3.9. In addition to the usual bug fixes and updated Python support, it helps get NumPy back to its usual release cycle after the extended development of 2.0. Os destaques desta versão são: - Suporte ao Python 3.12.0. -- Suporte preliminar para Python 3.13 free threaded. -- Suporte para array-api 2023.12 standard. +- Preliminary support for free threaded Python 3.13. +- Support for the array-api 2023.12 standard. -As versões 3.10-3.13 do Python são suportadas por esta versão. +Python versions 3.10-3.13 are supported by this release. -### NumPy 2.0.0 lançada +### NumPy 2.0.0 released -_16 de junho, 2024_ -- NumPy 2.0.0 é a primeira grande versão desde 2006. É o resultado de 11 meses de desenvolvimento desde a última feature release e é o trabalho de 212 contribuidores espalhado por 1078 pull requests. Esta versão contém um grande número de novas funcionalidades interessantes, bem como mudanças nas APIs Python e C. As mudanças incluem quebras de compatibilidade que não puderam acontecer em uma versão regular menor - incluindo uma quebra na ABI, mudanças nas regras de promoção de tipo e mudanças na API que poderiam não estar emitindo alertas de fim de suporte nas versões 1.26.x. Documentos-chave, relacionados a como se adaptar às mudanças em NumPy 2.0, incluem: +_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 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: -- O [guia de migração NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- As [notas de lançamento da versão 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) -- Issue de anúncio para atualizações de estado: [numpy#24300](https://github.com/numpy/numpy/issues/24300) +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) -A postagem de blog ["NumPy 2.0: an evolutionary milestone"](https://blog.scientific-python.org/numpy/numpy2/) conta um pouco da história sobre como esta versão foi construída. +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. -### Data de lançamento da NumPy 2.0: 16 de junho +### NumPy 2.0 release date: June 16 -_23 de maio, 2024_ -- Estamos animados em anunciar que planejamos lançar a NumPy 2.0 em 16 de junho de 2024. Este lançamento está em desenvolvimento há mais de um ano, e é o primeiro grande lançamento desde 2006. Importante, além de muitas funcionalidades novas e melhoria de desempenho, esta versão contém **quebras de compatibilidade** com a ABI e com as APIs Python e C. É provável que os pacotes downstream e o código de usuário final precisem ser adaptados - se você puder, por favor, verifique se o seu código funciona com NumPy `2.0.0rc2`. **Por favor, veja o seguinte para mais detalhes:** +_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:** -- O [guia de migração NumPy 2.0](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) -- As [notas de lançamento da versão 2.0.0](https://numpy.org/devdocs/release/2.0.0-notes.html) -- Issue de anúncio para atualizações de estado: [numpy#24300](https://github.com/numpy/numpy/issues/24300) +- The [NumPy 2.0 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) +- 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) ### Lançado o NumPy versão 1.26.0 @@ -56,7 +56,7 @@ Use a URL única que permitirá rastrear as compras https://lp.jetbrains.com/sup ### NumPy versão 1.24.0 -_17 de junho, 2023_ -- [NumPy 1.25.0](https://numpy.org/doc/stable/release/1.25.0-notes.html) está disponível agora. Os destaques desta versão são: +_16 de setembro de 2023_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html) está disponível. Os destaques desta versão são: * Suport ao Python 3.12.0. * Compatibilidade com Cython 3.0.0. @@ -95,7 +95,7 @@ No futuro, adoraríamos traduzir o site para mais línguas. Se você quiser ajud ### NumPy versão 1.22.0 -_18 de dezembro de 2022_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html) está agora disponível. Os destaques desta versão são: +_17 de junho, 2023_ -- [NumPy 1.25.0](https://numpy.org/doc/stable/release/1.25.0-notes.html) está disponível agora. Os destaques desta versão são: * Suporte para MUSL, agora existem rodas MUSL. * Suporte para o compilador Fujitsu C/C++. @@ -120,7 +120,7 @@ _6 de janeiro de 2023_ –- Mukulika Pahari e Ross Barnowski são nomeados como ### NumPy versão 1.23.0 -_31 de dezembro de 2021_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) está agora disponível. Os destaques desta versão são: +_18 de dezembro de 2022_ -- [NumPy 1.24.0](https://numpy.org/doc/stable/release/1.24.0-notes.html) está agora disponível. Os destaques desta versão são: * Novas palavras-chave "dtype" e "casting" para funções que atuam com stacking. * Novas funcionalidades e correções do F2PY. @@ -131,7 +131,7 @@ A versão 1.24.0 do NumPy continua o trabalho de melhorias no suporte e promoç ### NumPy versão 1.19.0 -_22 de junho de 2022_ -- O [NumPy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html) está disponível. Os destaques desta versão são: +_31 de dezembro de 2021_ -- [NumPy 1.22.0](https://numpy.org/doc/stable/release/1.22.0-notes.html) está agora disponível. Os destaques desta versão são: * Implementação de `loadtxt` em C, melhorando muito seu desempenho. * Exposição do DLPack ao nível de Python para facilitar a troca de dados. @@ -182,7 +182,7 @@ Siga o link para começar: https://berkeley.qualtrics.com/jfe/form/SV_aaOONjgcBX ### NumPy versão 1.19.0 -_16 de setembro de 2023_ -- [NumPy 1.26.0](https://numpy.org/doc/stable/release/1.26.0-notes.html) está disponível. Os destaques desta versão são: +_22 de junho de 2022_ -- O [NumPy 1.23.0](https://numpy.org/doc/stable/release/1.23.0-notes.html) está disponível. Os destaques desta versão são: - a continuação do trabalho com SIMD para suportar mais funções e plataformas, - trabalho inicial na infraestrutura e conversão de novos dtypes, @@ -276,14 +276,14 @@ Aqui está uma lista de versões do NumPy, com links para notas de lançamento. - NumPy 2.2.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.2.0)) -- _8 Dec 2024_. - NumPy 2.1.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.3)) -- _2 Nov 2024_. -- NumPy 2.1.2 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 de outubro de 2024_. -- NumPy 2.1.1 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 de setembro de 2024_. -- NumPy 2.0.2 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 de agosto de 2024_. -- NumPy 2.1.0 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 de agosto de 2024_. -- NumPy 2.0.1 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 de julho de 2024_. -- NumPy 2.0.0 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 de junho de 2024_. -- NumPy 1.26.4 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 de fevereiro de 2024_. -- NumPy 1.26.3 ([notas de lançamento](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 de janeiro de 2024_. +- NumPy 2.1.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.2)) -- _5 Oct 2024_. +- NumPy 2.1.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.1)) -- _3 Sep 2024_. +- NumPy 2.0.2 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.2)) -- _26 Aug 2024_. +- NumPy 2.1.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.1.0)) -- _18 Aug 2024_. +- NumPy 2.0.1 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.1)) -- _21 Jul 2024_. +- NumPy 2.0.0 ([release notes](https://github.com/numpy/numpy/releases/tag/v2.0.0)) -- _16 Jun 2024_. +- NumPy 1.26.4 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.4)) -- _5 Feb 2024_. +- NumPy 1.26.3 ([release notes](https://github.com/numpy/numpy/releases/tag/v1.26.3)) -- _2 Jan 2024_. - NumPy 1.26.2 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v1.26.2)) -- _12 de novembro de 2023_. - NumPy 1.26.1 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v1.26.1)) -- _14 de outubro de 2023_. - NumPy 1.26.0 ([notas de versão](https://github.com/numpy/numpy/releases/tag/v1.26.0)) -- _16 de setembro de 2023_.