numpy | fundamental package for scientific computing

by rmjarvis Python Version: Current License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | numpy Summary

numpy is a Python library. numpy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

NumPy is the fundamental package needed for scientific computing with Python.

Support

Quality

Security

License

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Support

numpy has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

numpy has no issues reported. There are 10 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of numpy is current.

Quality

numpy has no bugs reported.

Security

numpy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

numpy is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

numpy releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

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numpy Key Features

No Key Features are available at this moment for numpy.

numpy Examples and Code Snippets

No Code Snippets are available at this moment for numpy.

Community Discussions

No Community Discussions are available at this moment for numpy.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install numpy

You can download it from GitHub.
You can use numpy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

The NumPy project welcomes your expertise and enthusiasm!. Small improvements or fixes are always appreciated; issues labeled as "good first issue" may be a good starting point. If you are considering larger contributions to the source code, please contact us through the mailing list first.

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