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Downloads of v 1.26.4:


Last Update:

06 Feb 2024

Package Maintainer(s):

Software Author(s):

  • NumPy developers


numpy python scientific computing


  • 1
  • 2
  • 3

1.26.4 | Updated: 06 Feb 2024



Downloads of v 1.26.4:


Software Author(s):

  • NumPy developers

NumPy 1.26.4

  • 1
  • 2
  • 3

This Package Contains an Exempted Check

Not All Tests Have Passed

Validation Testing Passed

Verification Testing Exemption:

Dependency on kb2919355 which requires a reboot.


Scan Testing Successful:

No detections found in any package files

Learn More

Deployment Method: Individual Install, Upgrade, & Uninstall

To install NumPy, run the following command from the command line or from PowerShell:


To upgrade NumPy, run the following command from the command line or from PowerShell:


To uninstall NumPy, run the following command from the command line or from PowerShell:


Deployment Method:


This applies to both open source and commercial editions of Chocolatey.

1. Enter Your Internal Repository Url

(this should look similar to https://community.chocolatey.org/api/v2/)

2. Setup Your Environment

1. Ensure you are set for organizational deployment

Please see the organizational deployment guide

2. Get the package into your environment

  • Open Source or Commercial:
    • Proxy Repository - Create a proxy nuget repository on Nexus, Artifactory Pro, or a proxy Chocolatey repository on ProGet. Point your upstream to https://community.chocolatey.org/api/v2/. Packages cache on first access automatically. Make sure your choco clients are using your proxy repository as a source and NOT the default community repository. See source command for more information.
    • You can also just download the package and push it to a repository Download

3. Copy Your Script

choco upgrade numpy -y --source="'INTERNAL REPO URL'" [other options]

See options you can pass to upgrade.

See best practices for scripting.

Add this to a PowerShell script or use a Batch script with tools and in places where you are calling directly to Chocolatey. If you are integrating, keep in mind enhanced exit codes.

If you do use a PowerShell script, use the following to ensure bad exit codes are shown as failures:

choco upgrade numpy -y --source="'INTERNAL REPO URL'" 

Write-Verbose "Exit code was $exitCode"
$validExitCodes = @(0, 1605, 1614, 1641, 3010)
if ($validExitCodes -contains $exitCode) {
  Exit 0

Exit $exitCode

- name: Install numpy
    name: numpy
    version: '1.26.4'
    state: present

See docs at https://docs.ansible.com/ansible/latest/modules/win_chocolatey_module.html.

chocolatey_package 'numpy' do
  action    :install
  source   'INTERNAL REPO URL'
  version  '1.26.4'

See docs at https://docs.chef.io/resource_chocolatey_package.html.

cChocoPackageInstaller numpy
    Name     = "numpy"
    Version  = "1.26.4"
    Source   = "INTERNAL REPO URL"

Requires cChoco DSC Resource. See docs at https://github.com/chocolatey/cChoco.

package { 'numpy':
  ensure   => '1.26.4',
  provider => 'chocolatey',
  source   => 'INTERNAL REPO URL',

Requires Puppet Chocolatey Provider module. See docs at https://forge.puppet.com/puppetlabs/chocolatey.

4. If applicable - Chocolatey configuration/installation

See infrastructure management matrix for Chocolatey configuration elements and examples.

Package Approved

This package was approved as a trusted package on 06 Feb 2024.


NumPy is the fundamental package for scientific computing with Python. It contains among other things:

  • a powerful N-dimensional array object
  • sophisticated (broadcasting) functions
  • tools for integrating C/C++ and Fortran code
  • useful linear algebra, Fourier transform, and random number capabilities
    Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

NumPy is licensed under the BSD license, enabling reuse with few restrictions.

Getting Started

To install NumPy, we strongly recommend using a scientific Python distribution. See Installing the SciPy Stack for details.

Many high quality online tutorials, courses, and books are available to get started with NumPy. For a quick introduction to NumPy we provide the NumPy Tutorial. We also recommend the SciPy Lecture Notes for a broader introduction to the scientific Python ecosystem.

For more information on the SciPy Stack (for which NumPy provides the fundamental array data structure), see scipy.org.


The most up-to-date NumPy documentation can be found at Latest (development) version. It includes a user guide, full reference documentation, a developer guide, meta information, and “NumPy Enhancement Proposals” (which include the NumPy Roadmap and detailed plans for major new features).

A complete archive of documentation for all NumPy releases (minor versions; bug fix releases don’t contain significant documentation changes) since 2009 can be found at https://docs.scipy.org.

$version = '1.26.4'
$proxy = Get-EffectiveProxy
if ($proxy) {
  Write-Host "Setting CLI proxy: $proxy"
  $env:http_proxy = $env:https_proxy = $proxy
python -m pip install numpy==$version
python -m pip uninstall numpy -y

Log in or click on link to see number of positives.

In cases where actual malware is found, the packages are subject to removal. Software sometimes has false positives. Moderators do not necessarily validate the safety of the underlying software, only that a package retrieves software from the official distribution point and/or validate embedded software against official distribution point (where distribution rights allow redistribution).

Chocolatey Pro provides runtime protection from possible malware.

Add to Builder Version Downloads Last Updated Status
NumPy 1.26.3 153 Wednesday, January 3, 2024 Approved
NumPy 1.26.1 422 Sunday, October 15, 2023 Approved
NumPy 1.26.0 155 Sunday, September 17, 2023 Approved
NumPy 1.25.2 284 Monday, July 31, 2023 Approved
NumPy 1.25.1 154 Sunday, July 9, 2023 Approved
NumPy 1.25.0 140 Saturday, June 17, 2023 Approved
NumPy 1.24.3 295 Sunday, April 23, 2023 Approved
NumPy 1.24.2 558 Monday, February 6, 2023 Approved
NumPy 1.24.1 214 Monday, December 26, 2022 Approved
NumPy 1.24.0 114 Monday, December 19, 2022 Approved
NumPy 1.23.5 188 Sunday, November 20, 2022 Approved
NumPy 1.23.4 235 Wednesday, October 12, 2022 Approved
NumPy 1.23.3 272 Saturday, September 10, 2022 Approved
NumPy 1.23.2 289 Monday, August 15, 2022 Approved
NumPy 1.23.1 258 Saturday, July 9, 2022 Approved
NumPy 1.23.0 143 Thursday, June 23, 2022 Approved
NumPy 1.22.4 180 Saturday, May 21, 2022 Approved
NumPy 1.22.3 371 Tuesday, March 8, 2022 Approved
NumPy 1.22.2 240 Friday, February 4, 2022 Approved
NumPy 1.22.1 211 Saturday, January 15, 2022 Approved
NumPy 1.22.0 163 Saturday, January 1, 2022 Approved
NumPy 1.21.5 185 Monday, December 20, 2021 Approved
NumPy 1.21.4 318 Friday, November 5, 2021 Approved
NumPy 1.21.3 148 Thursday, October 21, 2021 Approved
NumPy 1.21.2 569 Monday, August 16, 2021 Approved
NumPy 1.21.1 166 Monday, July 19, 2021 Approved
NumPy 1.21.0 193 Tuesday, June 22, 2021 Approved
NumPy 1.20.3 226 Monday, May 10, 2021 Approved
NumPy 1.20.2 235 Sunday, March 28, 2021 Approved
NumPy 1.20.1 278 Monday, February 8, 2021 Approved
NumPy 1.20.0 168 Sunday, January 31, 2021 Approved
NumPy 1.19.5 231 Wednesday, January 6, 2021 Approved
NumPy 1.19.4 479 Monday, November 2, 2020 Approved
NumPy 1.19.3 188 Thursday, October 29, 2020 Approved
NumPy 1.19.2 525 Friday, September 11, 2020 Approved
NumPy 1.19.1 340 Wednesday, July 22, 2020 Approved
NumPy 1.18.5 354 Friday, June 5, 2020 Approved
NumPy 1.18.4 207 Sunday, May 3, 2020 Approved
NumPy 1.18.3 291 Monday, April 20, 2020 Approved
NumPy 1.18.2 332 Tuesday, March 17, 2020 Approved
NumPy 1.18.1 575 Tuesday, January 7, 2020 Approved
NumPy 1.18.0 257 Monday, December 23, 2019 Approved
NumPy 1.17.4 625 Monday, November 11, 2019 Approved
NumPy 1.17.3 429 Thursday, October 17, 2019 Approved
NumPy 1.17.2 356 Saturday, September 7, 2019 Approved
NumPy 1.17.1 407 Tuesday, August 27, 2019 Approved
NumPy 1.17.0 335 Saturday, July 27, 2019 Approved
NumPy 1.16.4 402 Wednesday, May 29, 2019 Approved
NumPy 1.16.3 234 Tuesday, May 14, 2019 Approved
numpy 1.8.1 3385 Tuesday, July 15, 2014 Approved

Discussion for the NumPy Package

Ground Rules:

  • This discussion is only about NumPy and the NumPy package. If you have feedback for Chocolatey, please contact the Google Group.
  • This discussion will carry over multiple versions. If you have a comment about a particular version, please note that in your comments.
  • The maintainers of this Chocolatey Package will be notified about new comments that are posted to this Disqus thread, however, it is NOT a guarantee that you will get a response. If you do not hear back from the maintainers after posting a message below, please follow up by using the link on the left side of this page or follow this link to contact maintainers. If you still hear nothing back, please follow the package triage process.
  • Tell us what you love about the package or NumPy, or tell us what needs improvement.
  • Share your experiences with the package, or extra configuration or gotchas that you've found.
  • If you use a url, the comment will be flagged for moderation until you've been whitelisted. Disqus moderated comments are approved on a weekly schedule if not sooner. It could take between 1-5 days for your comment to show up.
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