Downloads:
18,185
Downloads of v 1.8.1:
3,389
Last Update:
15 Jul 2014
Package Maintainer(s):
Software Author(s):
- Travis Oliphant
- Software Specific:
- Software Site
- Software License
- Package Specific:
- Package outdated?
- Package broken?
- Contact Maintainers
- Contact Site Admins
- Software Vendor?
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- Download
numpy
This is not the latest version of numpy available.
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1.8.1 | Updated: 15 Jul 2014
- Software Specific:
- Software Site
- Software License
- Package Specific:
- Package outdated?
- Package broken?
- Contact Maintainers
- Contact Site Admins
- Software Vendor?
- Report Abuse
- Download
Downloads:
18,185
Downloads of v 1.8.1:
3,389
Maintainer(s):
Software Author(s):
- Travis Oliphant
numpy 1.8.1
This is not the latest version of numpy available.
- 1
- 2
- 3
This Package Contains an Exempted Check
Not All Tests Have Passed
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
Option 1: Cached Package (Unreliable, Requires Internet - Same As Community)-
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
-
Open Source
-
Download the package:
Download - Follow manual internalization instructions
-
-
Package Internalizer (C4B)
-
Run: (additional options)
choco download numpy --internalize --version=1.8.1 --source=https://community.chocolatey.org/api/v2/
-
For package and dependencies run:
choco push --source="'INTERNAL REPO URL'"
- Automate package internalization
-
Run: (additional options)
3. Copy Your Script
choco upgrade numpy -y --source="'INTERNAL REPO URL'" --version="'1.8.1'" [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'" --version="'1.8.1'"
$exitCode = $LASTEXITCODE
Write-Verbose "Exit code was $exitCode"
$validExitCodes = @(0, 1605, 1614, 1641, 3010)
if ($validExitCodes -contains $exitCode) {
Exit 0
}
Exit $exitCode
- name: Install numpy
win_chocolatey:
name: numpy
version: '1.8.1'
source: INTERNAL REPO URL
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 '1.8.1'
end
See docs at https://docs.chef.io/resource_chocolatey_package.html.
cChocoPackageInstaller numpy
{
Name = "numpy"
Version = "1.8.1"
Source = "INTERNAL REPO URL"
}
Requires cChoco DSC Resource. See docs at https://github.com/chocolatey/cChoco.
package { 'numpy':
ensure => '1.8.1',
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.
This package was approved as a trusted package on 03 Jun 2019.
NumPy is a general-purpose array-processing package designed to
efficiently manipulate large multi-dimensional arrays of arbitrary
records without sacrificing too much speed for small multi-dimensional
arrays. NumPy is built on the Numeric code base and adds features
introduced by numarray as well as an extended C-API and the ability to
create arrays of arbitrary type which also makes NumPy suitable for
interfacing with general-purpose data-base applications.
There are also basic facilities for discrete fourier transform,
basic linear algebra and random number generation.
Log in or click on link to see number of positives.
- numpy.1.8.1.nupkg (3a10c92b78bb) - ## / 56
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 1.26.4 | 281 | Tuesday, February 6, 2024 | Approved | |
NumPy 1.26.3 | 157 | Wednesday, January 3, 2024 | Approved | |
NumPy 1.26.1 | 425 | Sunday, October 15, 2023 | Approved | |
NumPy 1.26.0 | 158 | Sunday, September 17, 2023 | Approved | |
NumPy 1.25.2 | 287 | Monday, July 31, 2023 | Approved | |
NumPy 1.25.1 | 157 | Sunday, July 9, 2023 | Approved | |
NumPy 1.25.0 | 144 | Saturday, June 17, 2023 | Approved | |
NumPy 1.24.3 | 300 | Sunday, April 23, 2023 | Approved | |
NumPy 1.24.2 | 562 | Monday, February 6, 2023 | Approved | |
NumPy 1.24.1 | 218 | Monday, December 26, 2022 | Approved | |
NumPy 1.24.0 | 117 | Monday, December 19, 2022 | Approved | |
NumPy 1.23.5 | 190 | Sunday, November 20, 2022 | Approved | |
NumPy 1.23.4 | 238 | Wednesday, October 12, 2022 | Approved | |
NumPy 1.23.3 | 274 | Saturday, September 10, 2022 | Approved | |
NumPy 1.23.2 | 291 | Monday, August 15, 2022 | Approved | |
NumPy 1.23.1 | 260 | Saturday, July 9, 2022 | Approved | |
NumPy 1.23.0 | 146 | Thursday, June 23, 2022 | Approved | |
NumPy 1.22.4 | 182 | Saturday, May 21, 2022 | Approved | |
NumPy 1.22.3 | 373 | Tuesday, March 8, 2022 | Approved | |
NumPy 1.22.2 | 242 | Friday, February 4, 2022 | Approved | |
NumPy 1.22.1 | 215 | Saturday, January 15, 2022 | Approved | |
NumPy 1.22.0 | 166 | Saturday, January 1, 2022 | Approved | |
NumPy 1.21.5 | 190 | Monday, December 20, 2021 | Approved | |
NumPy 1.21.4 | 322 | Friday, November 5, 2021 | Approved | |
NumPy 1.21.3 | 150 | Thursday, October 21, 2021 | Approved | |
NumPy 1.21.2 | 572 | Monday, August 16, 2021 | Approved | |
NumPy 1.21.1 | 169 | Monday, July 19, 2021 | Approved | |
NumPy 1.21.0 | 195 | Tuesday, June 22, 2021 | Approved | |
NumPy 1.20.3 | 228 | Monday, May 10, 2021 | Approved | |
NumPy 1.20.2 | 237 | Sunday, March 28, 2021 | Approved | |
NumPy 1.20.1 | 282 | Monday, February 8, 2021 | Approved | |
NumPy 1.20.0 | 170 | Sunday, January 31, 2021 | Approved | |
NumPy 1.19.5 | 233 | Wednesday, January 6, 2021 | Approved | |
NumPy 1.19.4 | 482 | Monday, November 2, 2020 | Approved | |
NumPy 1.19.3 | 190 | Thursday, October 29, 2020 | Approved | |
NumPy 1.19.2 | 528 | Friday, September 11, 2020 | Approved | |
NumPy 1.19.1 | 345 | Wednesday, July 22, 2020 | Approved | |
NumPy 1.18.5 | 358 | Friday, June 5, 2020 | Approved | |
NumPy 1.18.4 | 211 | Sunday, May 3, 2020 | Approved | |
NumPy 1.18.3 | 295 | Monday, April 20, 2020 | Approved | |
NumPy 1.18.2 | 336 | Tuesday, March 17, 2020 | Approved | |
NumPy 1.18.1 | 579 | Tuesday, January 7, 2020 | Approved | |
NumPy 1.18.0 | 263 | Monday, December 23, 2019 | Approved | |
NumPy 1.17.4 | 629 | Monday, November 11, 2019 | Approved | |
NumPy 1.17.3 | 434 | Thursday, October 17, 2019 | Approved | |
NumPy 1.17.2 | 361 | Saturday, September 7, 2019 | Approved | |
NumPy 1.17.1 | 411 | Tuesday, August 27, 2019 | Approved | |
NumPy 1.17.0 | 340 | Saturday, July 27, 2019 | Approved | |
NumPy 1.16.4 | 406 | Wednesday, May 29, 2019 | Approved | |
NumPy 1.16.3 | 240 | Tuesday, May 14, 2019 | Approved | |
numpy 1.8.1 | 3389 | Tuesday, July 15, 2014 | Approved |
2013 Numpy developers
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- python2-x86_32 (≥ 2.7.8)
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.
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