Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

feat: to_iceberg support for filling missing columns in the DataFrame with None #2616

Merged
merged 12 commits into from
Jan 18, 2024

Conversation

LeonLuttenberger
Copy link
Contributor

@LeonLuttenberger LeonLuttenberger commented Jan 16, 2024

Feature or Bugfix

  • Feature

Detail

  • If to_iceberg is invoked with fill_missing_columns_in_df=True, missing columns in the DataFrame will be filled in with None

Relates

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

@LeonLuttenberger LeonLuttenberger marked this pull request as ready for review January 16, 2024 19:55
@malachi-constant

This comment was marked as outdated.

@malachi-constant

This comment was marked as outdated.

@malachi-constant

This comment was marked as outdated.

@malachi-constant

This comment was marked as outdated.

Copy link
Contributor

@kukushking kukushking left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Approved as discussed internally.

@malachi-constant

This comment was marked as outdated.

@malachi-constant

This comment was marked as outdated.

@malachi-constant
Copy link
Contributor

AWS CodeBuild CI Report

  • CodeBuild project: GitHubCodeBuild8756EF16-4rfo0GHQ0u9a
  • Commit ID: 71b778c
  • Result: SUCCEEDED
  • Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

@LeonLuttenberger LeonLuttenberger merged commit 498b586 into main Jan 18, 2024
18 of 19 checks passed
@LeonLuttenberger LeonLuttenberger deleted the feat/iceberg-drop-columns branch January 18, 2024 18:50
@malachi-constant
Copy link
Contributor

AWS CodeBuild CI Report

  • CodeBuild project: GitHubDistributedCodeBuild6-jWcl5DLmvupS
  • Commit ID: 71b778c
  • Result: SUCCEEDED
  • Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository

sawyerh referenced this pull request in sawyerh/highlights Mar 1, 2024
[![Mend
Renovate](https://app.renovatebot.com/images/banner.svg)](https://renovatebot.com)

This PR contains the following updates:

| Package | Change | Age | Adoption | Passing | Confidence |
|---|---|---|---|---|---|
|
[aws-lambda-powertools](https://togithub.com/aws-powertools/powertools-lambda-python)
([changelog](https://togithub.com/aws-powertools/powertools-lambda-python/releases))
| `2.26.0` -> `2.34.2` |
[![age](https://developer.mend.io/api/mc/badges/age/pypi/aws-lambda-powertools/2.34.2?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![adoption](https://developer.mend.io/api/mc/badges/adoption/pypi/aws-lambda-powertools/2.34.2?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![passing](https://developer.mend.io/api/mc/badges/compatibility/pypi/aws-lambda-powertools/2.26.0/2.34.2?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![confidence](https://developer.mend.io/api/mc/badges/confidence/pypi/aws-lambda-powertools/2.26.0/2.34.2?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
| [awswrangler](https://aws-sdk-pandas.readthedocs.io/)
([source](https://togithub.com/aws/aws-sdk-pandas)) | `3.4.1` -> `3.6.0`
|
[![age](https://developer.mend.io/api/mc/badges/age/pypi/awswrangler/3.6.0?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![adoption](https://developer.mend.io/api/mc/badges/adoption/pypi/awswrangler/3.6.0?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![passing](https://developer.mend.io/api/mc/badges/compatibility/pypi/awswrangler/3.4.1/3.6.0?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![confidence](https://developer.mend.io/api/mc/badges/confidence/pypi/awswrangler/3.4.1/3.6.0?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
| [numpy](https://numpy.org)
([source](https://togithub.com/numpy/numpy),
[changelog](https://numpy.org/doc/stable/release)) | `1.25.2` ->
`1.26.4` |
[![age](https://developer.mend.io/api/mc/badges/age/pypi/numpy/1.26.4?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![adoption](https://developer.mend.io/api/mc/badges/adoption/pypi/numpy/1.26.4?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![passing](https://developer.mend.io/api/mc/badges/compatibility/pypi/numpy/1.25.2/1.26.4?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![confidence](https://developer.mend.io/api/mc/badges/confidence/pypi/numpy/1.25.2/1.26.4?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
| [pandas](https://pandas.pydata.org)
([source](https://togithub.com/pandas-dev/pandas)) | `2.1.2` -> `2.2.1`
|
[![age](https://developer.mend.io/api/mc/badges/age/pypi/pandas/2.2.1?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![adoption](https://developer.mend.io/api/mc/badges/adoption/pypi/pandas/2.2.1?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![passing](https://developer.mend.io/api/mc/badges/compatibility/pypi/pandas/2.1.2/2.2.1?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![confidence](https://developer.mend.io/api/mc/badges/confidence/pypi/pandas/2.1.2/2.2.1?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
| [pytest](https://docs.pytest.org/en/latest/)
([source](https://togithub.com/pytest-dev/pytest),
[changelog](https://docs.pytest.org/en/stable/changelog.html)) | `7.4.3`
-> `7.4.4` |
[![age](https://developer.mend.io/api/mc/badges/age/pypi/pytest/7.4.4?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![adoption](https://developer.mend.io/api/mc/badges/adoption/pypi/pytest/7.4.4?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![passing](https://developer.mend.io/api/mc/badges/compatibility/pypi/pytest/7.4.3/7.4.4?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|
[![confidence](https://developer.mend.io/api/mc/badges/confidence/pypi/pytest/7.4.3/7.4.4?slim=true)](https://docs.renovatebot.com/merge-confidence/)
|

---

### Release Notes

<details>
<summary>aws-powertools/powertools-lambda-python
(aws-lambda-powertools)</summary>

###
[`v2.34.2`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2342---2024-02-26)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.34.1...v2.34.2)

#### \[v2.34.2] - 2024-02-26

###
[`v2.34.1`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2341---2024-02-21)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.34.0...v2.34.1)

#### \[v2.34.1] - 2024-02-21

###
[`v2.34.0`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2340---2024-02-21)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.33.1...v2.34.0)

#### \[v2.34.0] - 2024-02-21

###
[`v2.33.1`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2331---2024-02-09)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.33.0...v2.33.1)

#### \[v2.33.1] - 2024-02-09

###
[`v2.33.0`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2330---2024-02-02)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.32.0...v2.33.0)

#### \[v2.33.0] - 2024-02-02

###
[`v2.32.0`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2320---2024-01-19)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.31.0...v2.32.0)

#### \[v2.32.0] - 2024-01-19

###
[`v2.31.0`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2310---2024-01-05)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.30.2...v2.31.0)

#### \[v2.31.0] - 2024-01-05

###
[`v2.30.2`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2302---2023-12-18)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.30.1...v2.30.2)

#### \[v2.30.2] - 2023-12-18

###
[`v2.30.1`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2301---2023-12-15)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.30.0...v2.30.1)

#### \[v2.30.1] - 2023-12-15

###
[`v2.30.0`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2300---2023-12-14)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.29.1...v2.30.0)

#### \[v2.30.0] - 2023-12-14

###
[`v2.29.1`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2291---2023-12-11)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.29.0...v2.29.1)

#### \[v2.29.1] - 2023-12-11

###
[`v2.29.0`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2290---2023-12-06)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.28.1...v2.29.0)

#### \[v2.29.0] - 2023-12-06

###
[`v2.28.1`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2281---2023-11-28)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.28.0...v2.28.1)

#### \[v2.28.1] - 2023-11-28

###
[`v2.28.0`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2280---2023-11-23)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.27.1...v2.28.0)

#### \[v2.28.0] - 2023-11-23

###
[`v2.27.1`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2271---2023-11-21)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.27.0...v2.27.1)

#### \[v2.27.1] - 2023-11-21

###
[`v2.27.0`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2270---2023-11-16)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.26.1...v2.27.0)

#### \[v2.27.0] - 2023-11-16

###
[`v2.26.1`](https://togithub.com/aws-powertools/powertools-lambda-python/blob/HEAD/CHANGELOG.md#v2261---2023-11-10)

[Compare
Source](https://togithub.com/aws-powertools/powertools-lambda-python/compare/v2.26.0...v2.26.1)

#### \[v2.26.1] - 2023-11-10

</details>

<details>
<summary>aws/aws-sdk-pandas (awswrangler)</summary>

###
[`v3.6.0`](https://togithub.com/aws/aws-sdk-pandas/releases/tag/3.6.0):
AWS SDK for pandas 3.6.0

[Compare
Source](https://togithub.com/aws/aws-sdk-pandas/compare/3.5.2...3.6.0)

#### Features/Enhancements 🚀

- Enable Iceberg row deletion & add `mode` parameter to `to_iceberg` by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[#&#8203;2632](https://togithub.com/aws/aws-sdk-pandas/issues/2632)
- Add support for pyarrow type `large_string` by
[@&#8203;joakibo](https://togithub.com/joakibo) in
[#&#8203;2663](https://togithub.com/aws/aws-sdk-pandas/issues/2663)
- Add `max_results` to `athena.list_query_executions` by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[#&#8203;2665](https://togithub.com/aws/aws-sdk-pandas/issues/2665)

#### Bug fixes 🐛

- Pyarrow 15 imports & remove unused code by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[#&#8203;2649](https://togithub.com/aws/aws-sdk-pandas/issues/2649)

#### New Contributors

- [@&#8203;joakibo](https://togithub.com/joakibo) made their first
contribution in
[https://github.com/aws/aws-sdk-pandas/pull/2663](https://togithub.com/aws/aws-sdk-pandas/pull/2663)

**Full Changelog**:
https://github.com/aws/aws-sdk-pandas/compare/3.5.2...3.6.0

###
[`v3.5.2`](https://togithub.com/aws/aws-sdk-pandas/releases/tag/3.5.2):
AWS SDK for pandas 3.5.2

[Compare
Source](https://togithub.com/aws/aws-sdk-pandas/compare/3.5.1...3.5.2)

#### Bug fixes 🐛

- DynamoDB key & filter expressions attribute overwrite by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[https://github.com/aws/aws-sdk-pandas/pull/2615](https://togithub.com/aws/aws-sdk-pandas/pull/2615)
- Allow PostgreSQL reserved keywords as column names by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2619](https://togithub.com/aws/aws-sdk-pandas/pull/2619)
- Add `to_iceberg` support for filling missing columns in the DataFrame
with None by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2616](https://togithub.com/aws/aws-sdk-pandas/pull/2616)
- Forward `ignore_nulls` for container types by
[@&#8203;raaidarshad](https://togithub.com/raaidarshad) in
[#&#8203;2636](https://togithub.com/aws/aws-sdk-pandas/issues/2636)

#### Documentation 📚

- Add `s3_additional_kwargs` to docstrings by
[@&#8203;malachi-constant](https://togithub.com/malachi-constant) in
[https://github.com/aws/aws-sdk-pandas/pull/2627](https://togithub.com/aws/aws-sdk-pandas/pull/2627)
- Fix outdated hyperlinks in documentation by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2634](https://togithub.com/aws/aws-sdk-pandas/pull/2634)

#### Other 🤖

- Enable dependabot to upgrade GitHub actions by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2618](https://togithub.com/aws/aws-sdk-pandas/pull/2618)
- Update badges in README by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2628](https://togithub.com/aws/aws-sdk-pandas/pull/2628)
- Add vulnerability label to dependabot PRs with alert state by
[@&#8203;jaidisido](https://togithub.com/jaidisido) in
[https://github.com/aws/aws-sdk-pandas/pull/2629](https://togithub.com/aws/aws-sdk-pandas/pull/2629)

#### New Contributors

- [@&#8203;raaidarshad](https://togithub.com/raaidarshad) made their
first contribution in
[#&#8203;2636](https://togithub.com/aws/aws-sdk-pandas/issues/2636)

**Full Changelog**:
https://github.com/aws/aws-sdk-pandas/compare/3.5.1...3.5.2

###
[`v3.5.1`](https://togithub.com/aws/aws-sdk-pandas/releases/tag/3.5.1):
AWS SDK for pandas 3.5.1

[Compare
Source](https://togithub.com/aws/aws-sdk-pandas/compare/3.5.0...3.5.1)

#### Bug fixes 🐛

- Deserialization error when reading from DynamoDB using
`KeyConditionExpression` by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[#&#8203;2607](https://togithub.com/aws/aws-sdk-pandas/issues/2607)
- Reading of chunked parquet when columns parameter is specified by
[@&#8203;rchromik](https://togithub.com/rchromik) in
[#&#8203;2599](https://togithub.com/aws/aws-sdk-pandas/issues/2599)

#### Documentation 📚

- Add `show_create_table` to Athena API page by
[@&#8203;MikeSchriefer](https://togithub.com/MikeSchriefer) in
[#&#8203;2610](https://togithub.com/aws/aws-sdk-pandas/issues/2610)

#### Other 🤖

- chore: Replace `bump2version` with `bump-my-version` by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[#&#8203;2608](https://togithub.com/aws/aws-sdk-pandas/issues/2608)
- chore(deps-dev): bump jinja2 from 3.1.2 to 3.1.3 by
[@&#8203;dependabot](https://togithub.com/dependabot) in
[#&#8203;2609](https://togithub.com/aws/aws-sdk-pandas/issues/2609)
- chore(deps): bump grpcio from 1.51.3 to 1.53.0 by
[@&#8203;dependabot](https://togithub.com/dependabot) in
[#&#8203;2612](https://togithub.com/aws/aws-sdk-pandas/issues/2612)

#### New Contributors

- [@&#8203;MikeSchriefer](https://togithub.com/MikeSchriefer) made their
first contribution in
[#&#8203;2610](https://togithub.com/aws/aws-sdk-pandas/issues/2610)
- [@&#8203;rchromik](https://togithub.com/rchromik) made their first
contribution in
[#&#8203;2599](https://togithub.com/aws/aws-sdk-pandas/issues/2599)

**Full Changelog**:
https://github.com/aws/aws-sdk-pandas/compare/3.5.0...3.5.1

###
[`v3.5.0`](https://togithub.com/aws/aws-sdk-pandas/releases/tag/3.5.0):
AWS SDK for pandas 3.5.0

[Compare
Source](https://togithub.com/aws/aws-sdk-pandas/compare/3.4.2...3.5.0)

#### Breaking changes 💥

Due to
[CVEs](https://www.anyscale.com/blog/update-on-ray-cves-cve-2023-6019-cve-2023-6020-cve-2023-6021-cve-2023-48022-cve-2023-48023),
Ray is capped to patched version 2.9.x. As a result, the latest version
of the library cannot be used on the Glue for Ray runtime. We have
raised the CVEs issue to the Glue team

#### Features/Enhancements 🚀

- Add `spark_properties` to athena spark by
[@&#8203;rajagurunath](https://togithub.com/rajagurunath) in
[https://github.com/aws/aws-sdk-pandas/pull/2508](https://togithub.com/aws/aws-sdk-pandas/pull/2508)
- Add `MERGE INTO` support for Iceberg by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2527](https://togithub.com/aws/aws-sdk-pandas/pull/2527)
- Support partitioning by index cols by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[https://github.com/aws/aws-sdk-pandas/pull/2528](https://togithub.com/aws/aws-sdk-pandas/pull/2528)
- Add `analysis_template_arn` to `cleanrooms.read_sql_query` by
[@&#8203;jaidisido](https://togithub.com/jaidisido) in
[https://github.com/aws/aws-sdk-pandas/pull/2584](https://togithub.com/aws/aws-sdk-pandas/pull/2584)
- Python 3.12 support by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2559](https://togithub.com/aws/aws-sdk-pandas/pull/2559)
- Note: Ray currently does not support Python 3.12. As such, distributed
operations on data frames will not work yet.
- [Relevant Ray
issue](https://togithub.com/ray-project/ray/issues/40211)
- Upgrade to Ray 2.9.0+ and refactor Ray datasources to the new API by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[https://github.com/aws/aws-sdk-pandas/pull/2570](https://togithub.com/aws/aws-sdk-pandas/pull/2570)

#### Bug fixes 🐛

- Athena/Neptune minor fixes by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[https://github.com/aws/aws-sdk-pandas/pull/2526](https://togithub.com/aws/aws-sdk-pandas/pull/2526)
- Reset index and handle last index by
[@&#8203;Antropath](https://togithub.com/Antropath) in
[https://github.com/aws/aws-sdk-pandas/pull/2531](https://togithub.com/aws/aws-sdk-pandas/pull/2531)
- Oracle failed import message by
[@&#8203;matthewdeanmartin](https://togithub.com/matthewdeanmartin) in
[https://github.com/aws/aws-sdk-pandas/pull/2537](https://togithub.com/aws/aws-sdk-pandas/pull/2537)
- Add parameterized queries where possible to address the risk of SQL
injection by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2540](https://togithub.com/aws/aws-sdk-pandas/pull/2540)
- SQL identifiers by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[https://github.com/aws/aws-sdk-pandas/pull/2543](https://togithub.com/aws/aws-sdk-pandas/pull/2543)
- coerce_timestamps - allow None by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[https://github.com/aws/aws-sdk-pandas/pull/2556](https://togithub.com/aws/aws-sdk-pandas/pull/2556)
- Add validation for `table` and `schema` params for Redshift by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2551](https://togithub.com/aws/aws-sdk-pandas/pull/2551)
- Redshift VARBYTE support by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[https://github.com/aws/aws-sdk-pandas/pull/2573](https://togithub.com/aws/aws-sdk-pandas/pull/2573)

#### Documentation 📚

- Add SSM Public Param usage to docs by
[@&#8203;malachi-constant](https://togithub.com/malachi-constant) in
[https://github.com/aws/aws-sdk-pandas/pull/2521](https://togithub.com/aws/aws-sdk-pandas/pull/2521)

#### Other 🤖

- refactor: Remove usage of boto3 resources by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2525](https://togithub.com/aws/aws-sdk-pandas/pull/2525)
- chore(deps): bump aiohttp from 3.8.5 to 3.8.6 by
[@&#8203;dependabot](https://togithub.com/dependabot) in
[https://github.com/aws/aws-sdk-pandas/pull/2519](https://togithub.com/aws/aws-sdk-pandas/pull/2519)
- chore(deps): bump aiohttp from 3.8.6 to 3.9.0 by
[@&#8203;dependabot](https://togithub.com/dependabot) in
[https://github.com/aws/aws-sdk-pandas/pull/2535](https://togithub.com/aws/aws-sdk-pandas/pull/2535)
- chore(deps): bump cryptography from 41.0.4 to 41.0.6 by
[@&#8203;dependabot](https://togithub.com/dependabot) in
[https://github.com/aws/aws-sdk-pandas/pull/2538](https://togithub.com/aws/aws-sdk-pandas/pull/2538)
- chore(deps-dev): bump jupyter-server from 2.7.2 to 2.11.2 by
[@&#8203;dependabot](https://togithub.com/dependabot) in
[https://github.com/aws/aws-sdk-pandas/pull/2545](https://togithub.com/aws/aws-sdk-pandas/pull/2545)
- chore: Upgrade test infrastructure dependencies by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2562](https://togithub.com/aws/aws-sdk-pandas/pull/2562)
- chore: Prepare 3.5.0 release by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2560](https://togithub.com/aws/aws-sdk-pandas/pull/2560)
- chore: Upgrade deltalake dependency by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2563](https://togithub.com/aws/aws-sdk-pandas/pull/2563)
- chore: Replace black formatter with ruff format by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2568](https://togithub.com/aws/aws-sdk-pandas/pull/2568)
- chore: ruff improvements by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2571](https://togithub.com/aws/aws-sdk-pandas/pull/2571)
- chore: upgrade `oracledb` to 2.0 by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2574](https://togithub.com/aws/aws-sdk-pandas/pull/2574)
- chore(deps-dev): bump the development-dependencies group with 8
updates by [@&#8203;dependabot](https://togithub.com/dependabot) in
[https://github.com/aws/aws-sdk-pandas/pull/2577](https://togithub.com/aws/aws-sdk-pandas/pull/2577)
- chore(deps-dev): bump the development-dependencies group with 5
updates by [@&#8203;dependabot](https://togithub.com/dependabot) in
[https://github.com/aws/aws-sdk-pandas/pull/2583](https://togithub.com/aws/aws-sdk-pandas/pull/2583)
- chore(deps-dev): bump the development-dependencies group with 3
updates by [@&#8203;dependabot](https://togithub.com/dependabot) in
[https://github.com/aws/aws-sdk-pandas/pull/2590](https://togithub.com/aws/aws-sdk-pandas/pull/2590)
- chore(deps): bump the production-dependencies group with 5 updates by
[@&#8203;dependabot](https://togithub.com/dependabot) in
[https://github.com/aws/aws-sdk-pandas/pull/2591](https://togithub.com/aws/aws-sdk-pandas/pull/2591)
- chore: type annotations by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2585](https://togithub.com/aws/aws-sdk-pandas/pull/2585)
- chore: Replace PyLint with Ruff by
[@&#8203;LeonLuttenberger](https://togithub.com/LeonLuttenberger) in
[https://github.com/aws/aws-sdk-pandas/pull/2588](https://togithub.com/aws/aws-sdk-pandas/pull/2588)
- chore: Update gremlinpython & add aiohttp by
[@&#8203;kukushking](https://togithub.com/kukushking) in
[https://github.com/aws/aws-sdk-pandas/pull/2595](https://togithub.com/aws/aws-sdk-pandas/pull/2595)

#### New Contributors

- [@&#8203;rajagurunath](https://togithub.com/rajagurunath) made their
first contribution in
[https://github.com/aws/aws-sdk-pandas/pull/2508](https://togithub.com/aws/aws-sdk-pandas/pull/2508)
- [@&#8203;Antropath](https://togithub.com/Antropath) made their first
contribution in
[https://github.com/aws/aws-sdk-pandas/pull/2531](https://togithub.com/aws/aws-sdk-pandas/pull/2531)
- [@&#8203;matthewdeanmartin](https://togithub.com/matthewdeanmartin)
made their first contribution in
[https://github.com/aws/aws-sdk-pandas/pull/2537](https://togithub.com/aws/aws-sdk-pandas/pull/2537)

**Full Changelog**:
https://github.com/aws/aws-sdk-pandas/compare/3.4.2...3.5.0

###
[`v3.4.2`](https://togithub.com/aws/aws-sdk-pandas/releases/tag/3.4.2):
AWS SDK for pandas 3.4.2

[Compare
Source](https://togithub.com/aws/aws-sdk-pandas/compare/3.4.1...3.4.2)

#### Features/Enhancements 🚀

- Update pyarrow to 14.0.1 to fix [arbitrary code execution security
vulnerability](https://togithub.com/aws/aws-sdk-pandas/security/dependabot/35)

**Full Changelog**:
https://github.com/aws/aws-sdk-pandas/compare/3.4.1...3.4.2

</details>

<details>
<summary>numpy/numpy (numpy)</summary>

### [`v1.26.4`](https://togithub.com/numpy/numpy/releases/tag/v1.26.4)

[Compare
Source](https://togithub.com/numpy/numpy/compare/v1.26.3...v1.26.4)

### NumPy 1.26.4 Release Notes

NumPy 1.26.4 is a maintenance release that fixes bugs and regressions
discovered after the 1.26.3 release. The Python versions supported by
this release are 3.9-3.12. This is the last planned release in the
1.26.x series.

#### Contributors

A total of 13 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

-   Charles Harris
-   Elliott Sales de Andrade
-   Lucas Colley +
-   Mark Ryan +
-   Matti Picus
-   Nathan Goldbaum
-   Ola x Nilsson +
-   Pieter Eendebak
-   Ralf Gommers
-   Sayed Adel
-   Sebastian Berg
-   Stefan van der Walt
-   Stefano Rivera

#### Pull requests merged

A total of 19 pull requests were merged for this release.

- [#&#8203;25323](https://togithub.com/numpy/numpy/pull/25323): BUG:
Restore missing asstr import
- [#&#8203;25523](https://togithub.com/numpy/numpy/pull/25523): MAINT:
prepare 1.26.x for further development
- [#&#8203;25539](https://togithub.com/numpy/numpy/pull/25539): BUG:
`numpy.array_api`: fix `linalg.cholesky` upper decomp...
- [#&#8203;25584](https://togithub.com/numpy/numpy/pull/25584): CI: Bump
azure pipeline timeout to 120 minutes
- [#&#8203;25585](https://togithub.com/numpy/numpy/pull/25585): MAINT,
BLD: Fix unused inline functions warnings on clang
- [#&#8203;25599](https://togithub.com/numpy/numpy/pull/25599): BLD:
include fix for MinGW platform detection
- [#&#8203;25618](https://togithub.com/numpy/numpy/pull/25618): TST: Fix
test_numeric on riscv64
- [#&#8203;25619](https://togithub.com/numpy/numpy/pull/25619): BLD: fix
building for windows ARM64
- [#&#8203;25620](https://togithub.com/numpy/numpy/pull/25620): MAINT:
add `newaxis` to `__all__` in `numpy.array_api`
- [#&#8203;25630](https://togithub.com/numpy/numpy/pull/25630): BUG: Use
large file fallocate on 32 bit linux platforms
- [#&#8203;25643](https://togithub.com/numpy/numpy/pull/25643): TST: Fix
test_warning_calls on Python 3.12
- [#&#8203;25645](https://togithub.com/numpy/numpy/pull/25645): TST:
Bump pytz to 2023.3.post1
- [#&#8203;25658](https://togithub.com/numpy/numpy/pull/25658): BUG: Fix
AVX512 build flags on Intel Classic Compiler
- [#&#8203;25670](https://togithub.com/numpy/numpy/pull/25670): BLD: fix
potential issue with escape sequences in `__config__.py`
- [#&#8203;25718](https://togithub.com/numpy/numpy/pull/25718): CI: pin
cygwin python to 3.9.16-1 and fix typing tests \[skip...
- [#&#8203;25720](https://togithub.com/numpy/numpy/pull/25720): MAINT:
Bump cibuildwheel to v2.16.4
- [#&#8203;25748](https://togithub.com/numpy/numpy/pull/25748): BLD:
unvendor meson-python on 1.26.x and upgrade to meson-python...
- [#&#8203;25755](https://togithub.com/numpy/numpy/pull/25755): MAINT:
Include header defining backtrace
- [#&#8203;25756](https://togithub.com/numpy/numpy/pull/25756): BUG: Fix
np.quantile(\[Fraction(2,1)], 0.5)
([#&#8203;24711](https://togithub.com/numpy/numpy/issues/24711))

#### Checksums

##### MD5

90f33cdd8934cd07192d6ede114d8d4d
numpy-1.26.4-cp310-cp310-macosx_10_9_x86_64.whl
63ac60767f6724490e587f6010bd6839
numpy-1.26.4-cp310-cp310-macosx_11_0_arm64.whl
ad4e82b225aaaf5898ea9798b50978d8
numpy-1.26.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
d428e3da2df4fa359313348302cf003a
numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
89937c3bb596193f8ca9eae2ff84181e
numpy-1.26.4-cp310-cp310-musllinux_1_1_aarch64.whl
de4f9da0a4e6dfd4cec39c7ad5139803
numpy-1.26.4-cp310-cp310-musllinux_1_1_x86_64.whl
    2c1f73fd9b3acf4b9b0c23e985cdd38f  numpy-1.26.4-cp310-cp310-win32.whl
920ad1f50e478b1a877fe7b7a46cc520 numpy-1.26.4-cp310-cp310-win_amd64.whl
719d1ff12db38903dcfd6749078fb11d
numpy-1.26.4-cp311-cp311-macosx_10_9_x86_64.whl
eb601e80194d2e1c00d8daedd8dc68c4
numpy-1.26.4-cp311-cp311-macosx_11_0_arm64.whl
71a7ab11996fa370dc28e28731bd5c32
numpy-1.26.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
eb0cdd03e1ee2eb45c57c7340c98cf48
numpy-1.26.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
9d4ae1b0b27a625400f81ed1846a5667
numpy-1.26.4-cp311-cp311-musllinux_1_1_aarch64.whl
1b6771350d2f496157430437a895ba4b
numpy-1.26.4-cp311-cp311-musllinux_1_1_x86_64.whl
    1e4a18612ee4d0e54e0833574ebc6d25  numpy-1.26.4-cp311-cp311-win32.whl
5fd325dd8704023c1110835d7a1b095a numpy-1.26.4-cp311-cp311-win_amd64.whl
d95ce582923d24dbddbc108aa5fd2128
numpy-1.26.4-cp312-cp312-macosx_10_9_x86_64.whl
6f16f3d70e0d95ce2b032167c546cc95
numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl
5369536d4c45fbe384147ff23185b48a
numpy-1.26.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
1ceb224096686831ad731e472b65e96a
numpy-1.26.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
cd8d3c00bbc89f9bc07e2df762f9e2ae
numpy-1.26.4-cp312-cp312-musllinux_1_1_aarch64.whl
5bd81ce840bb2e42befe01efb0402b79
numpy-1.26.4-cp312-cp312-musllinux_1_1_x86_64.whl
    2cc3b0757228078395da3efa3dc99f23  numpy-1.26.4-cp312-cp312-win32.whl
305155bd5ae879344c58968879584ed1 numpy-1.26.4-cp312-cp312-win_amd64.whl
ec2310f67215743e9c5d16b6c9fb87b6
numpy-1.26.4-cp39-cp39-macosx_10_9_x86_64.whl
406aea6081c1affbebdb6ad56b5deaf4
numpy-1.26.4-cp39-cp39-macosx_11_0_arm64.whl
fee12f0a3cbac7bbf1a1c2d82d3b02a9
numpy-1.26.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
baf4b7143c7b9ce170e62b33380fb573
numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
376ff29f90b7840ae19ecd59ad1ddf53
numpy-1.26.4-cp39-cp39-musllinux_1_1_aarch64.whl
86785b3a7cd156c08c2ebc26f7816fb3
numpy-1.26.4-cp39-cp39-musllinux_1_1_x86_64.whl
    ab8a9ab69f16b7005f238cda76bc0bac  numpy-1.26.4-cp39-cp39-win32.whl
fafa4453e820c7ff40907e5dc79d8199 numpy-1.26.4-cp39-cp39-win_amd64.whl
7f13e2f07bd3e4a439ade0e4d27905c6
numpy-1.26.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
928954b41c1cd0e856f1a31d41722661
numpy-1.26.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
57bbd5c0b3848d804c416cbcab4a0ae8
numpy-1.26.4-pp39-pypy39_pp73-win_amd64.whl
    19550cbe7bedd96a928da9d4ad69509d  numpy-1.26.4.tar.gz

##### SHA256

9ff0f4f29c51e2803569d7a51c2304de5554655a60c5d776e35b4a41413830d0
numpy-1.26.4-cp310-cp310-macosx_10_9_x86_64.whl
2e4ee3380d6de9c9ec04745830fd9e2eccb3e6cf790d39d7b98ffd19b0dd754a
numpy-1.26.4-cp310-cp310-macosx_11_0_arm64.whl
d209d8969599b27ad20994c8e41936ee0964e6da07478d6c35016bc386b66ad4
numpy-1.26.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
ffa75af20b44f8dba823498024771d5ac50620e6915abac414251bd971b4529f
numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
62b8e4b1e28009ef2846b4c7852046736bab361f7aeadeb6a5b89ebec3c7055a
numpy-1.26.4-cp310-cp310-musllinux_1_1_aarch64.whl
a4abb4f9001ad2858e7ac189089c42178fcce737e4169dc61321660f1a96c7d2
numpy-1.26.4-cp310-cp310-musllinux_1_1_x86_64.whl
bfe25acf8b437eb2a8b2d49d443800a5f18508cd811fea3181723922a8a82b07
numpy-1.26.4-cp310-cp310-win32.whl
b97fe8060236edf3662adfc2c633f56a08ae30560c56310562cb4f95500022d5
numpy-1.26.4-cp310-cp310-win_amd64.whl
4c66707fabe114439db9068ee468c26bbdf909cac0fb58686a42a24de1760c71
numpy-1.26.4-cp311-cp311-macosx_10_9_x86_64.whl
edd8b5fe47dab091176d21bb6de568acdd906d1887a4584a15a9a96a1dca06ef
numpy-1.26.4-cp311-cp311-macosx_11_0_arm64.whl
7ab55401287bfec946ced39700c053796e7cc0e3acbef09993a9ad2adba6ca6e
numpy-1.26.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
666dbfb6ec68962c033a450943ded891bed2d54e6755e35e5835d63f4f6931d5
numpy-1.26.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
96ff0b2ad353d8f990b63294c8986f1ec3cb19d749234014f4e7eb0112ceba5a
numpy-1.26.4-cp311-cp311-musllinux_1_1_aarch64.whl
60dedbb91afcbfdc9bc0b1f3f402804070deed7392c23eb7a7f07fa857868e8a
numpy-1.26.4-cp311-cp311-musllinux_1_1_x86_64.whl
1af303d6b2210eb850fcf03064d364652b7120803a0b872f5211f5234b399f20
numpy-1.26.4-cp311-cp311-win32.whl
cd25bcecc4974d09257ffcd1f098ee778f7834c3ad767fe5db785be9a4aa9cb2
numpy-1.26.4-cp311-cp311-win_amd64.whl
b3ce300f3644fb06443ee2222c2201dd3a89ea6040541412b8fa189341847218
numpy-1.26.4-cp312-cp312-macosx_10_9_x86_64.whl
03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b
numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl
9fad7dcb1aac3c7f0584a5a8133e3a43eeb2fe127f47e3632d43d677c66c102b
numpy-1.26.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
675d61ffbfa78604709862923189bad94014bef562cc35cf61d3a07bba02a7ed
numpy-1.26.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
ab47dbe5cc8210f55aa58e4805fe224dac469cde56b9f731a4c098b91917159a
numpy-1.26.4-cp312-cp312-musllinux_1_1_aarch64.whl
1dda2e7b4ec9dd512f84935c5f126c8bd8b9f2fc001e9f54af255e8c5f16b0e0
numpy-1.26.4-cp312-cp312-musllinux_1_1_x86_64.whl
50193e430acfc1346175fcbdaa28ffec49947a06918b7b92130744e81e640110
numpy-1.26.4-cp312-cp312-win32.whl
08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818
numpy-1.26.4-cp312-cp312-win_amd64.whl
7349ab0fa0c429c82442a27a9673fc802ffdb7c7775fad780226cb234965e53c
numpy-1.26.4-cp39-cp39-macosx_10_9_x86_64.whl
52b8b60467cd7dd1e9ed082188b4e6bb35aa5cdd01777621a1658910745b90be
numpy-1.26.4-cp39-cp39-macosx_11_0_arm64.whl
d5241e0a80d808d70546c697135da2c613f30e28251ff8307eb72ba696945764
numpy-1.26.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
f870204a840a60da0b12273ef34f7051e98c3b5961b61b0c2c1be6dfd64fbcd3
numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
679b0076f67ecc0138fd2ede3a8fd196dddc2ad3254069bcb9faf9a79b1cebcd
numpy-1.26.4-cp39-cp39-musllinux_1_1_aarch64.whl
47711010ad8555514b434df65f7d7b076bb8261df1ca9bb78f53d3b2db02e95c
numpy-1.26.4-cp39-cp39-musllinux_1_1_x86_64.whl
a354325ee03388678242a4d7ebcd08b5c727033fcff3b2f536aea978e15ee9e6
numpy-1.26.4-cp39-cp39-win32.whl
3373d5d70a5fe74a2c1bb6d2cfd9609ecf686d47a2d7b1d37a8f3b6bf6003aea
numpy-1.26.4-cp39-cp39-win_amd64.whl
afedb719a9dcfc7eaf2287b839d8198e06dcd4cb5d276a3df279231138e83d30
numpy-1.26.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
95a7476c59002f2f6c590b9b7b998306fba6a5aa646b1e22ddfeaf8f78c3a29c
numpy-1.26.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
7e50d0a0cc3189f9cb0aeb3a6a6af18c16f59f004b866cd2be1c14b36134a4a0
numpy-1.26.4-pp39-pypy39_pp73-win_amd64.whl
2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010
numpy-1.26.4.tar.gz

###
[`v1.26.3`](https://togithub.com/numpy/numpy/compare/v1.26.2...v1.26.3)

[Compare
Source](https://togithub.com/numpy/numpy/compare/v1.26.2...v1.26.3)

### [`v1.26.2`](https://togithub.com/numpy/numpy/releases/tag/v1.26.2):
1.26.2 release

[Compare
Source](https://togithub.com/numpy/numpy/compare/v1.26.1...v1.26.2)

### NumPy 1.26.2 Release Notes

NumPy 1.26.2 is a maintenance release that fixes bugs and regressions
discovered after the 1.26.1 release. The 1.26.release series is the last
planned minor release series before NumPy 2.0. The Python versions
supported by this release are 3.9-3.12.

#### Contributors

A total of 13 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

-   [@&#8203;stefan6419846](https://togithub.com/stefan6419846)
-   [@&#8203;thalassemia](https://togithub.com/thalassemia) +
-   Andrew Nelson
-   Charles Bousseau +
-   Charles Harris
-   Marcel Bargull +
-   Mark Mentovai +
-   Matti Picus
-   Nathan Goldbaum
-   Ralf Gommers
-   Sayed Adel
-   Sebastian Berg
-   William Ayd +

#### Pull requests merged

A total of 25 pull requests were merged for this release.

- [#&#8203;24814](https://togithub.com/numpy/numpy/pull/24814): MAINT:
align test_dispatcher s390x targets with \_umath_tests_mtargets
- [#&#8203;24929](https://togithub.com/numpy/numpy/pull/24929): MAINT:
prepare 1.26.x for further development
- [#&#8203;24955](https://togithub.com/numpy/numpy/pull/24955): ENH: Add
Cython enumeration for NPY_FR_GENERIC
- [#&#8203;24962](https://togithub.com/numpy/numpy/pull/24962): REL:
Remove Python upper version from the release branch
- [#&#8203;24971](https://togithub.com/numpy/numpy/pull/24971): BLD: Use
the correct Python interpreter when running tempita.py
- [#&#8203;24972](https://togithub.com/numpy/numpy/pull/24972): MAINT:
Remove unhelpful error replacements from `import_array()`
- [#&#8203;24977](https://togithub.com/numpy/numpy/pull/24977): BLD: use
classic linker on macOS, the new one in XCode 15 has...
- [#&#8203;25003](https://togithub.com/numpy/numpy/pull/25003): BLD:
musllinux_aarch64 \[wheel build]
- [#&#8203;25043](https://togithub.com/numpy/numpy/pull/25043): MAINT:
Update mailmap
- [#&#8203;25049](https://togithub.com/numpy/numpy/pull/25049): MAINT:
Update meson build infrastructure.
- [#&#8203;25071](https://togithub.com/numpy/numpy/pull/25071): MAINT:
Split up .github/workflows to match main
- [#&#8203;25083](https://togithub.com/numpy/numpy/pull/25083): BUG:
Backport fix build on ppc64 when the baseline set to Power9...
- [#&#8203;25093](https://togithub.com/numpy/numpy/pull/25093): BLD: Fix
features.h detection for Meson builds \[1.26.x Backport]
- [#&#8203;25095](https://togithub.com/numpy/numpy/pull/25095): BUG:
Avoid intp conversion regression in Cython 3 (backport)
- [#&#8203;25107](https://togithub.com/numpy/numpy/pull/25107): CI:
remove obsolete jobs, and move macOS and conda Azure jobs...
- [#&#8203;25108](https://togithub.com/numpy/numpy/pull/25108): CI: Add
linux_qemu action and remove travis testing.
- [#&#8203;25112](https://togithub.com/numpy/numpy/pull/25112): MAINT:
Update .spin/cmds.py from main.
- [#&#8203;25113](https://togithub.com/numpy/numpy/pull/25113): DOC:
Visually divide main license and bundled licenses in wheels
- [#&#8203;25115](https://togithub.com/numpy/numpy/pull/25115): MAINT:
Add missing `noexcept` to shuffle helpers
- [#&#8203;25116](https://togithub.com/numpy/numpy/pull/25116): DOC: Fix
license identifier for OpenBLAS
- [#&#8203;25117](https://togithub.com/numpy/numpy/pull/25117): BLD:
improve detection of Netlib libblas/libcblas/liblapack
- [#&#8203;25118](https://togithub.com/numpy/numpy/pull/25118): MAINT:
Make bitfield integers unsigned
- [#&#8203;25119](https://togithub.com/numpy/numpy/pull/25119): BUG:
Make n a long int for np.random.multinomial
- [#&#8203;25120](https://togithub.com/numpy/numpy/pull/25120): BLD:
change default of the `allow-noblas` option to true.
- [#&#8203;25121](https://togithub.com/numpy/numpy/pull/25121): BUG:
ensure passing `np.dtype` to itself doesn't crash

#### Checksums

##### MD5

1a5dc6b5b3bf11ad40a59eedb3b69fa1
numpy-1.26.2-cp310-cp310-macosx_10_9_x86_64.whl
4b741c6dfe4e6e22e34e9c5c788d4f04
numpy-1.26.2-cp310-cp310-macosx_11_0_arm64.whl
2953687fb26e1dd8a2d1bb7109551fcd
numpy-1.26.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
ea9127a3a03f27fd101c62425c661d8d
numpy-1.26.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
7a6be7c6c1cc3e1ff73f64052fe30677
numpy-1.26.2-cp310-cp310-musllinux_1_1_aarch64.whl
4f45d3f69f54fd1638609fde34c33a5c
numpy-1.26.2-cp310-cp310-musllinux_1_1_x86_64.whl
    f22f5ea26c86eb126ff502fff75d6c21  numpy-1.26.2-cp310-cp310-win32.whl
49871452488e1a55d15ab54c6f3e546e numpy-1.26.2-cp310-cp310-win_amd64.whl
676740bf60fb1c8f5a6b31e00b9a4e9b
numpy-1.26.2-cp311-cp311-macosx_10_9_x86_64.whl
7170545dcc2a38a1c2386a6081043b64
numpy-1.26.2-cp311-cp311-macosx_11_0_arm64.whl
feae1190c73d811e2e7ebcad4baf6edf
numpy-1.26.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
03131896abade61b77e0f6e53abb988a
numpy-1.26.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
f160632f128a3fd46787aa02d8731fbb
numpy-1.26.2-cp311-cp311-musllinux_1_1_aarch64.whl
014250db593d589b5533ef7127839c46
numpy-1.26.2-cp311-cp311-musllinux_1_1_x86_64.whl
    fb437346dac24d0cb23f5314db043c8b  numpy-1.26.2-cp311-cp311-win32.whl
7359adc233874898ea768cd4aec28bb3 numpy-1.26.2-cp311-cp311-win_amd64.whl
207a678bea75227428e7fb84d4dc457a
numpy-1.26.2-cp312-cp312-macosx_10_9_x86_64.whl
302ff6cc047a408cdf21981bd7b26056
numpy-1.26.2-cp312-cp312-macosx_11_0_arm64.whl
7526faaea58c76aed395c7128dd6e14d
numpy-1.26.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
28d3b1943d3a8ad4bbb2ae9da0a77cb9
numpy-1.26.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
d91f5b2bb2c931e41ae7c80ec7509a31
numpy-1.26.2-cp312-cp312-musllinux_1_1_aarch64.whl
b2504d4239419f012c08fa1eab12f940
numpy-1.26.2-cp312-cp312-musllinux_1_1_x86_64.whl
    57944ba30adc07f33e83a9b45f5c625a  numpy-1.26.2-cp312-cp312-win32.whl
fe38cd95bbee405ce0cf51c8753a2676 numpy-1.26.2-cp312-cp312-win_amd64.whl
28e1bc3efaf89cf6f0a2b616c0e16401
numpy-1.26.2-cp39-cp39-macosx_10_9_x86_64.whl
9932ccff54855f12ee24f60528279bf1
numpy-1.26.2-cp39-cp39-macosx_11_0_arm64.whl
b52c1e987074dad100ad234122a397b9
numpy-1.26.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
1d1bd7e0d2a89ce795a9566a38ed9bb5
numpy-1.26.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
01d2abfe8e9b35415efb791ac6c5865e
numpy-1.26.2-cp39-cp39-musllinux_1_1_aarch64.whl
5a6d6ac287ebd93a221e59590329e202
numpy-1.26.2-cp39-cp39-musllinux_1_1_x86_64.whl
    4e4e4d8cf661a8d2838ee700fabae87e  numpy-1.26.2-cp39-cp39-win32.whl
b8e52ecac110471502686abbdf774b78 numpy-1.26.2-cp39-cp39-win_amd64.whl
aed2d2914be293f60fedda360b64abf8
numpy-1.26.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
6bd88e0f33933445d0e18c1a850f60e0
numpy-1.26.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
010aeb2a50af0af1f7ef56f76f8cf463
numpy-1.26.2-pp39-pypy39_pp73-win_amd64.whl
    8f6446a32e47953a03f8fe8533e21e98  numpy-1.26.2.tar.gz

##### SHA256

3703fc9258a4a122d17043e57b35e5ef1c5a5837c3db8be396c82e04c1cf9b0f
numpy-1.26.2-cp310-cp310-macosx_10_9_x86_64.whl
cc392fdcbd21d4be6ae1bb4475a03ce3b025cd49a9be5345d76d7585aea69440
numpy-1.26.2-cp310-cp310-macosx_11_0_arm64.whl
36340109af8da8805d8851ef1d74761b3b88e81a9bd80b290bbfed61bd2b4f75
numpy-1.26.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
bcc008217145b3d77abd3e4d5ef586e3bdfba8fe17940769f8aa09b99e856c00
numpy-1.26.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
3ced40d4e9e18242f70dd02d739e44698df3dcb010d31f495ff00a31ef6014fe
numpy-1.26.2-cp310-cp310-musllinux_1_1_aarch64.whl
b272d4cecc32c9e19911891446b72e986157e6a1809b7b56518b4f3755267523
numpy-1.26.2-cp310-cp310-musllinux_1_1_x86_64.whl
22f8fc02fdbc829e7a8c578dd8d2e15a9074b630d4da29cda483337e300e3ee9
numpy-1.26.2-cp310-cp310-win32.whl
26c9d33f8e8b846d5a65dd068c14e04018d05533b348d9eaeef6c1bd787f9919
numpy-1.26.2-cp310-cp310-win_amd64.whl
b96e7b9c624ef3ae2ae0e04fa9b460f6b9f17ad8b4bec6d7756510f1f6c0c841
numpy-1.26.2-cp311-cp311-macosx_10_9_x86_64.whl
aa18428111fb9a591d7a9cc1b48150097ba6a7e8299fb56bdf574df650e7d1f1
numpy-1.26.2-cp311-cp311-macosx_11_0_arm64.whl
06fa1ed84aa60ea6ef9f91ba57b5ed963c3729534e6e54055fc151fad0423f0a
numpy-1.26.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
96ca5482c3dbdd051bcd1fce8034603d6ebfc125a7bd59f55b40d8f5d246832b
numpy-1.26.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
854ab91a2906ef29dc3925a064fcd365c7b4da743f84b123002f6139bcb3f8a7
numpy-1.26.2-cp311-cp311-musllinux_1_1_aarch64.whl
f43740ab089277d403aa07567be138fc2a89d4d9892d113b76153e0e412409f8
numpy-1.26.2-cp311-cp311-musllinux_1_1_x86_64.whl
a2bbc29fcb1771cd7b7425f98b05307776a6baf43035d3b80c4b0f29e9545186
numpy-1.26.2-cp311-cp311-win32.whl
2b3fca8a5b00184828d12b073af4d0fc5fdd94b1632c2477526f6bd7842d700d
numpy-1.26.2-cp311-cp311-win_amd64.whl
a4cd6ed4a339c21f1d1b0fdf13426cb3b284555c27ac2f156dfdaaa7e16bfab0
numpy-1.26.2-cp312-cp312-macosx_10_9_x86_64.whl
5d5244aabd6ed7f312268b9247be47343a654ebea52a60f002dc70c769048e75
numpy-1.26.2-cp312-cp312-macosx_11_0_arm64.whl
6a3cdb4d9c70e6b8c0814239ead47da00934666f668426fc6e94cce869e13fd7
numpy-1.26.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
aa317b2325f7aa0a9471663e6093c210cb2ae9c0ad824732b307d2c51983d5b6
numpy-1.26.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
174a8880739c16c925799c018f3f55b8130c1f7c8e75ab0a6fa9d41cab092fd6
numpy-1.26.2-cp312-cp312-musllinux_1_1_aarch64.whl
f79b231bf5c16b1f39c7f4875e1ded36abee1591e98742b05d8a0fb55d8a3eec
numpy-1.26.2-cp312-cp312-musllinux_1_1_x86_64.whl
4a06263321dfd3598cacb252f51e521a8cb4b6df471bb12a7ee5cbab20ea9167
numpy-1.26.2-cp312-cp312-win32.whl
b04f5dc6b3efdaab541f7857351aac359e6ae3c126e2edb376929bd3b7f92d7e
numpy-1.26.2-cp312-cp312-win_amd64.whl
4eb8df4bf8d3d90d091e0146f6c28492b0be84da3e409ebef54349f71ed271ef
numpy-1.26.2-cp39-cp39-macosx_10_9_x86_64.whl
1a13860fdcd95de7cf58bd6f8bc5a5ef81c0b0625eb2c9a783948847abbef2c2
numpy-1.26.2-cp39-cp39-macosx_11_0_arm64.whl
64308ebc366a8ed63fd0bf426b6a9468060962f1a4339ab1074c228fa6ade8e3
numpy-1.26.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
baf8aab04a2c0e859da118f0b38617e5ee65d75b83795055fb66c0d5e9e9b818
numpy-1.26.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
d73a3abcac238250091b11caef9ad12413dab01669511779bc9b29261dd50210
numpy-1.26.2-cp39-cp39-musllinux_1_1_aarch64.whl
b361d369fc7e5e1714cf827b731ca32bff8d411212fccd29ad98ad622449cc36
numpy-1.26.2-cp39-cp39-musllinux_1_1_x86_64.whl
bd3f0091e845164a20bd5a326860c840fe2af79fa12e0469a12768a3ec578d80
numpy-1.26.2-cp39-cp39-win32.whl
2beef57fb031dcc0dc8fa4fe297a742027b954949cabb52a2a376c144e5e6060
numpy-1.26.2-cp39-cp39-win_amd64.whl
1cc3d5029a30fb5f06704ad6b23b35e11309491c999838c31f124fee32107c79
numpy-1.26.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
94cc3c222bb9fb5a12e334d0479b97bb2df446fbe622b470928f5284ffca3f8d
numpy-1.26.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
fe6b44fb8fcdf7eda4ef4461b97b3f63c466b27ab151bec2366db8b197387841
numpy-1.26.2-pp39-pypy39_pp73-win_amd64.whl
f65738447676ab5777f11e6bbbdb8ce11b785e105f690bc45966574816b6d3ea
numpy-1.26.2.tar.gz

### [`v1.26.1`](https://togithub.com/numpy/numpy/releases/tag/v1.26.1)

[Compare
Source](https://togithub.com/numpy/numpy/compare/v1.26.0...v1.26.1)

##### NumPy 1.26.1 Release Notes

NumPy 1.26.1 is a maintenance release that fixes bugs and regressions
discovered after the 1.26.0 release. In addition, it adds new
functionality for detecting BLAS and LAPACK when building from source.
Highlights are:

-   Improved detection of BLAS and LAPACK libraries for meson builds
-   Pickle compatibility with the upcoming NumPy 2.0.

The 1.26.release series is the last planned minor release series before
NumPy 2.0. The Python versions supported by this release are 3.9-3.12.

##### Build system changes

##### Improved BLAS/LAPACK detection and control

Auto-detection for a number of BLAS and LAPACK is now implemented for
Meson. By default, the build system will try to detect MKL, Accelerate
(on macOS >=13.3), OpenBLAS, FlexiBLAS, BLIS and reference BLAS/LAPACK.
Support for MKL was significantly improved, and support for FlexiBLAS
was added.

New command-line flags are available to further control the selection of
the BLAS and LAPACK libraries to build against.

To select a specific library, use the config-settings interface via
`pip` or `pypa/build`. E.g., to select `libblas`/`liblapack`, use:

$ pip install numpy -Csetup-args=-Dblas=blas
-Csetup-args=-Dlapack=lapack
    $ # OR
$ python -m build . -Csetup-args=-Dblas=blas
-Csetup-args=-Dlapack=lapack

This works not only for the libraries named above, but for any library
that Meson is able to detect with the given name through `pkg-config` or
CMake.

Besides `-Dblas` and `-Dlapack`, a number of other new flags are
available to control BLAS/LAPACK selection and behavior:

-   `-Dblas-order` and `-Dlapack-order`: a list of library names to
    search for in order, overriding the default search order.
-   `-Duse-ilp64`: if set to `true`, use ILP64 (64-bit integer) BLAS and
    LAPACK. Note that with this release, ILP64 support has been extended
    to include MKL and FlexiBLAS. OpenBLAS and Accelerate were supported
    in previous releases.
-   `-Dallow-noblas`: if set to `true`, allow NumPy to build with its
    internal (very slow) fallback routines instead of linking against an
    external BLAS/LAPACK library. *The default for this flag may be
    changed to \`\`true\`\` in a future 1.26.x release, however for
    1.26.1 we'd prefer to keep it as \`\`false\`\` because if failures
    to detect an installed library are happening, we'd like a bug
    report for that, so we can quickly assess whether the new
    auto-detection machinery needs further improvements.*
-   `-Dmkl-threading`: to select the threading layer for MKL. There are
    four options: `seq`, `iomp`, `gomp` and `tbb`. The default is
    `auto`, which selects from those four as appropriate given the
    version of MKL selected.
-   `-Dblas-symbol-suffix`: manually select the symbol suffix to use for
    the library - should only be needed for linking against libraries
    built in a non-standard way.

##### New features

##### `numpy._core` submodule stubs

`numpy._core` submodule stubs were added to provide compatibility with
pickled arrays created using NumPy 2.0 when running Numpy 1.26.

##### Contributors

A total of 13 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

-   Andrew Nelson
-   Anton Prosekin +
-   Charles Harris
-   Chongyun Lee +
-   Ivan A. Melnikov +
-   Jake Lishman +
-   Mahder Gebremedhin +
-   Mateusz Sokół
-   Matti Picus
-   Munira Alduraibi +
-   Ralf Gommers
-   Rohit Goswami
-   Sayed Adel

##### Pull requests merged

A total of 20 pull requests were merged for this release.

- [#&#8203;24742](https://togithub.com/numpy/numpy/pull/24742): MAINT:
Update cibuildwheel version
- [#&#8203;24748](https://togithub.com/numpy/numpy/pull/24748): MAINT:
fix version string in wheels built with setup.py
- [#&#8203;24771](https://togithub.com/numpy/numpy/pull/24771): BLD,
BUG: Fix build failure for host flags e.g. `-march=native`...
- [#&#8203;24773](https://togithub.com/numpy/numpy/pull/24773): DOC:
Updated the f2py docs to remove a note on -fimplicit-none
- [#&#8203;24776](https://togithub.com/numpy/numpy/pull/24776): BUG: Fix
SIMD f32 trunc test on s390x when baseline is none
- [#&#8203;24785](https://togithub.com/numpy/numpy/pull/24785): BLD: add
libquadmath to licences and other tweaks
([#&#8203;24753](https://togithub.com/numpy/numpy/issues/24753))
- [#&#8203;24786](https://togithub.com/numpy/numpy/pull/24786): MAINT:
Activate `use-compute-credits` for Cirrus.
- [#&#8203;24803](https://togithub.com/numpy/numpy/pull/24803): BLD:
updated vendored-meson/meson for mips64 fix
- [#&#8203;24804](https://togithub.com/numpy/numpy/pull/24804): MAINT:
fix licence path win
- [#&#8203;24813](https://togithub.com/numpy/numpy/pull/24813): BUG: Fix
order of Windows OS detection macros.
- [#&#8203;24831](https://togithub.com/numpy/numpy/pull/24831): BUG,
SIMD: use scalar cmul on bad Apple clang x86\_64
([#&#8203;24828](https://togithub.com/numpy/numpy/issues/24828))
- [#&#8203;24840](https://togithub.com/numpy/numpy/pull/24840): BUG: Fix
DATA statements for f2py
- [#&#8203;24870](https://togithub.com/numpy/numpy/pull/24870): API: Add
`NumpyUnpickler` for backporting
- [#&#8203;24872](https://togithub.com/numpy/numpy/pull/24872): MAINT:
Xfail test failing on PyPy.
- [#&#8203;24879](https://togithub.com/numpy/numpy/pull/24879): BLD: fix
math func feature checks, fix FreeBSD build, add CI...
- [#&#8203;24899](https://togithub.com/numpy/numpy/pull/24899): ENH:
meson: implement BLAS/LAPACK auto-detection and many CI...
- [#&#8203;24902](https://togithub.com/numpy/numpy/pull/24902): DOC: add
a 1.26.1 release notes section for BLAS/LAPACK build...
- [#&#8203;24906](https://togithub.com/numpy/numpy/pull/24906): MAINT:
Backport `numpy._core` stubs. Remove `NumpyUnpickler`
- [#&#8203;24911](https://togithub.com/numpy/numpy/pull/24911): MAINT:
Bump pypa/cibuildwheel from 2.16.1 to 2.16.2
- [#&#8203;24912](https://togithub.com/numpy/numpy/pull/24912): BUG:
loongarch doesn't use REAL(10)

##### Checksums

##### MD5

bda38de1a047dd9fdddae16c0d9fb358
numpy-1.26.1-cp310-cp310-macosx_10_9_x86_64.whl
196d2e39047da64ab28e177760c95461
numpy-1.26.1-cp310-cp310-macosx_11_0_arm64.whl
9d25010a7bf50e624d2fed742790afbd
numpy-1.26.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
9b22fa3d030807f0708007d9c0659f65
numpy-1.26.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
eea626b8b930acb4b32302a9e95714f5
numpy-1.26.1-cp310-cp310-musllinux_1_1_x86_64.whl
    3c40ef068f50d2ac2913c5b9fa1233fa  numpy-1.26.1-cp310-cp310-win32.whl
315c251d2f284af25761a37ce6dd4d10 numpy-1.26.1-cp310-cp310-win_amd64.whl
ebdd5046937df50e9f54a6d38c5775dd
numpy-1.26.1-cp311-cp311-macosx_10_9_x86_64.whl
682f9beebe8547f205d6cdc8ff96a984
numpy-1.26.1-cp311-cp311-macosx_11_0_arm64.whl
e86da9b6040ea88b3835c4d8f8578658
numpy-1.26.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
ebcb6cf7f64454215e29d8a89829c8e1
numpy-1.26.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
a8c89e13dc9a63712104e2fb06fb63a6
numpy-1.26.1-cp311-cp311-musllinux_1_1_x86_64.whl
    339795930404988dbc664ff4cc72b399  numpy-1.26.1-cp311-cp311-win32.whl
4ef5e1bdd7726c19615843f5ac72e618 numpy-1.26.1-cp311-cp311-win_amd64.whl
3aad6bc72db50e9cc88aa5813e8f35bd
numpy-1.26.1-cp312-cp312-macosx_10_9_x86_64.whl
fd62f65ae7798dbda9a3f7af7aa5c8db
numpy-1.26.1-cp312-cp312-macosx_11_0_arm64.whl
104d939e080f1baf0a56aed1de0e79e3
numpy-1.26.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
c44b56c96097f910bbec1420abcf3db5
numpy-1.26.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
1dce230368ae5fc47dd0fe8de8ff771d
numpy-1.26.1-cp312-cp312-musllinux_1_1_x86_64.whl
    d93338e7d60e1d294ca326450e99806b  numpy-1.26.1-cp312-cp312-win32.whl
a1832f46521335c1ee4c56dbf12e600b numpy-1.26.1-cp312-cp312-win_amd64.whl
946fbb0b6caca9258985495532d3f9ab
numpy-1.26.1-cp39-cp39-macosx_10_9_x86_64.whl
78c2ab13d395d67d90bcd6583a6f61a8
numpy-1.26.1-cp39-cp39-macosx_11_0_arm64.whl
0a9d80d8b646abf4ffe51fff3e075d10
numpy-1.26.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
0229ba8145d4f58500873b540a55d60e
numpy-1.26.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
9179fc57c03260374c86e18867c24463
numpy-1.26.1-cp39-cp39-musllinux_1_1_x86_64.whl
    246a3103fdbe5d891d7a8aee28875a26  numpy-1.26.1-cp39-cp39-win32.whl
4589dcb7f754fade6ea3946416bee638 numpy-1.26.1-cp39-cp39-win_amd64.whl
3af340d5487a6c045f00fe5eb889957c
numpy-1.26.1-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
28aece4f1ceb92ec463aa353d4a91c8b
numpy-1.26.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
bbd0461a1e31017b05509e9971b3478e
numpy-1.26.1-pp39-pypy39_pp73-win_amd64.whl
    2d770f4c281d405b690c4bcb3dbe99e2  numpy-1.26.1.tar.gz

##### SHA256

82e871307a6331b5f09efda3c22e03c095d957f04bf6bc1804f30048d0e5e7af
numpy-1.26.1-cp310-cp310-macosx_10_9_x86_64.whl
cdd9ec98f0063d93baeb01aad472a1a0840dee302842a2746a7a8e92968f9575
numpy-1.26.1-cp310-cp310-macosx_11_0_arm64.whl
d78f269e0c4fd365fc2992c00353e4530d274ba68f15e968d8bc3c69ce5f5244
numpy-1.26.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
8ab9163ca8aeb7fd32fe93866490654d2f7dda4e61bc6297bf72ce07fdc02f67
numpy-1.26.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
78ca54b2f9daffa5f323f34cdf21e1d9779a54073f0018a3094ab907938331a2
numpy-1.26.1-cp310-cp310-musllinux_1_1_x86_64.whl
d1cfc92db6af1fd37a7bb58e55c8383b4aa1ba23d012bdbba26b4bcca45ac297
numpy-1.26.1-cp310-cp310-win32.whl
d2984cb6caaf05294b8466966627e80bf6c7afd273279077679cb010acb0e5ab
numpy-1.26.1-cp310-cp310-win_amd64.whl
cd7837b2b734ca72959a1caf3309457a318c934abef7a43a14bb984e574bbb9a
numpy-1.26.1-cp311-cp311-macosx_10_9_x86_64.whl
1c59c046c31a43310ad0199d6299e59f57a289e22f0f36951ced1c9eac3665b9
numpy-1.26.1-cp311-cp311-macosx_11_0_arm64.whl
d58e8c51a7cf43090d124d5073bc29ab2755822181fcad978b12e144e5e5a4b3
numpy-1.26.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
6081aed64714a18c72b168a9276095ef9155dd7888b9e74b5987808f0dd0a974
numpy-1.26.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
97e5d6a9f0702c2863aaabf19f0d1b6c2628fbe476438ce0b5ce06e83085064c
numpy-1.26.1-cp311-cp311-musllinux_1_1_x86_64.whl
b9d45d1dbb9de84894cc50efece5b09939752a2d75aab3a8b0cef6f3a35ecd6b
numpy-1.26.1-cp311-cp311-win32.whl
3649d566e2fc067597125428db15d60eb42a4e0897fc48d28cb75dc2e0454e53
numpy-1.26.1-cp311-cp311-win_amd64.whl
1d1bd82d539607951cac963388534da3b7ea0e18b149a53cf883d8f699178c0f
numpy-1.26.1-cp312-cp312-macosx_10_9_x86_64.whl
afd5ced4e5a96dac6725daeb5242a35494243f2239244fad10a90ce58b071d24
numpy-1.26.1-cp312-cp312-macosx_11_0_arm64.whl
a03fb25610ef560a6201ff06df4f8105292ba56e7cdd196ea350d123fc32e24e
numpy-1.26.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
dcfaf015b79d1f9f9c9fd0731a907407dc3e45769262d657d754c3a028586124
numpy-1.26.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
e509cbc488c735b43b5ffea175235cec24bbc57b227ef1acc691725beb230d1c
numpy-1.26.1-cp312-cp312-musllinux_1_1_x86_64.whl
af22f3d8e228d84d1c0c44c1fbdeb80f97a15a0abe4f080960393a00db733b66
numpy-1.26.1-cp312-cp312-win32.whl
9f42284ebf91bdf32fafac29d29d4c07e5e9d1af862ea73686581773ef9e73a7
numpy-1.26.1-cp312-cp312-win_amd64.whl
bb894accfd16b867d8643fc2ba6c8617c78ba2828051e9a69511644ce86ce83e
numpy-1.26.1-cp39-cp39-macosx_10_9_x86_64.whl
e44ccb93f30c75dfc0c3aa3ce38f33486a75ec9abadabd4e59f114994a9c4617
numpy-1.26.1-cp39-cp39-macosx_11_0_arm64.whl
9696aa2e35cc41e398a6d42d147cf326f8f9d81befcb399bc1ed7ffea339b64e
numpy-1.26.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
a5b411040beead47a228bde3b2241100454a6abde9df139ed087bd73fc0a4908
numpy-1.26.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
1e11668d6f756ca5ef534b5be8653d16c5352cbb210a5c2a79ff288e937010d5
numpy-1.26.1-cp39-cp39-musllinux_1_1_x86_64.whl
d1d2c6b7dd618c41e202c59c1413ef9b2c8e8a15f5039e344af64195459e3104
numpy-1.26.1-cp39-cp39-win32.whl
59227c981d43425ca5e5c01094d59eb14e8772ce6975d4b2fc1e106a833d5ae2
numpy-1.26.1-cp39-cp39-win_amd64.whl
06934e1a22c54636a059215d6da99e23286424f316fddd979f5071093b648668
numpy-1.26.1-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
76ff661a867d9272cd2a99eed002470f46dbe0943a5ffd140f49be84f68ffc42
numpy-1.26.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
6965888d65d2848e8768824ca8288db0a81263c1efccec881cb35a0d805fcd2f
numpy-1.26.1-pp39-pypy39_pp73-win_amd64.whl
c8c6c72d4a9f831f328efb1312642a1cafafaa88981d9ab76368d50d07d93cbe
numpy-1.26.1.tar.gz

### [`v1.26.0`](https://togithub.com/numpy/numpy/releases/tag/v1.26.0)

[Compare
Source](https://togithub.com/numpy/numpy/compare/v1.25.2...v1.26.0)

### NumPy 1.26.0 Release Notes

The NumPy 1.26.0 release is a continuation of the 1.25.x release cycle
with the addition of Python 3.12.0 support. Python 3.12 dropped
distutils, consequently supporting it required finding a replacement for
the setup.py/distu

</details>

---

### Configuration

📅 **Schedule**: Branch creation - "before 4am on the first day of the
month" (UTC), Automerge - At any time (no schedule defined).

🚦 **Automerge**: Disabled by config. Please merge this manually once you
are satisfied.

♻ **Rebasing**: Whenever PR becomes conflicted, or you tick the
rebase/retry checkbox.

👻 **Immortal**: This PR will be recreated if closed unmerged. Get
[config help](https://togithub.com/renovatebot/renovate/discussions) if
that's undesired.

---

- [ ] <!-- rebase-check -->If you want to rebase/retry this PR, check
this box

---

This PR has been generated by [Mend
Renovate](https://www.mend.io/free-developer-tools/renovate/). View
repository job log
[here](https://developer.mend.io/github/sawyerh/highlights).

<!--renovate-debug:eyJjcmVhdGVkSW5WZXIiOiIzNy4yMjAuMiIsInVwZGF0ZWRJblZlciI6IjM3LjIyMC4yIiwidGFyZ2V0QnJhbmNoIjoibWFpbiJ9-->

Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Projects
None yet
Development

Successfully merging this pull request may close these issues.

4 participants