Science Score: 57.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (16.0%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: pau-ramos1802
- License: other
- Language: Python
- Default Branch: main
- Size: 225 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 4
- Releases: 0
Metadata Files
README.md
NumPy is the fundamental package for scientific computing with Python.
- Website: https://numpy.org
- Documentation: https://numpy.org/doc
- Mailing list: https://mail.python.org/mailman/listinfo/numpy-discussion
- Source code: https://github.com/numpy/numpy
- Contributing: https://numpy.org/devdocs/dev/index.html
- Bug reports: https://github.com/numpy/numpy/issues
- Report a security vulnerability: https://tidelift.com/docs/security
It provides:
- 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
Testing:
NumPy requires pytest and hypothesis. Tests can then be run after installation with:
python -c "import numpy, sys; sys.exit(numpy.test() is False)"
Code of Conduct
NumPy is a community-driven open source project developed by a diverse group of contributors. The NumPy leadership has made a strong commitment to creating an open, inclusive, and positive community. Please read the NumPy Code of Conduct for guidance on how to interact with others in a way that makes our community thrive.
Call for Contributions
The NumPy project welcomes your expertise and enthusiasm!
Small improvements or fixes are always appreciated. If you are considering larger contributions to the source code, please contact us through the mailing list first.
Writing code isn’t the only way to contribute to NumPy. You can also: - review pull requests - help us stay on top of new and old issues - develop tutorials, presentations, and other educational materials - maintain and improve our website - develop graphic design for our brand assets and promotional materials - translate website content - help with outreach and onboard new contributors - write grant proposals and help with other fundraising efforts
For more information about the ways you can contribute to NumPy, visit our website. If you’re unsure where to start or how your skills fit in, reach out! You can ask on the mailing list or here, on GitHub, by opening a new issue or leaving a comment on a relevant issue that is already open.
Our preferred channels of communication are all public, but if you’d like to speak to us in private first, contact our community coordinators at numpy-team@googlegroups.com or on Slack (write numpy-team@googlegroups.com for an invitation).
We also have a biweekly community call, details of which are announced on the mailing list. You are very welcome to join.
If you are new to contributing to open source, this guide helps explain why, what, and how to successfully get involved.
Owner
- Name: Paulina Ramos
- Login: pau-ramos1802
- Kind: user
- Repositories: 1
- Profile: https://github.com/pau-ramos1802
Citation (CITATION.bib)
@ARTICLE{2020NumPy-Array,
author = {Harris, Charles R. and Millman, K. Jarrod and
van der Walt, Stéfan J and Gommers, Ralf and
Virtanen, Pauli and Cournapeau, David and
Wieser, Eric and Taylor, Julian and Berg, Sebastian and
Smith, Nathaniel J. and Kern, Robert and Picus, Matti and
Hoyer, Stephan and van Kerkwijk, Marten H. and
Brett, Matthew and Haldane, Allan and
Fernández del Río, Jaime and Wiebe, Mark and
Peterson, Pearu and Gérard-Marchant, Pierre and
Sheppard, Kevin and Reddy, Tyler and Weckesser, Warren and
Abbasi, Hameer and Gohlke, Christoph and
Oliphant, Travis E.},
title = {Array programming with {NumPy}},
journal = {Nature},
year = {2020},
volume = {585},
pages = {357–362},
doi = {10.1038/s41586-020-2649-2}
}
GitHub Events
Total
- Delete event: 21
- Issue comment event: 52
- Pull request event: 47
- Create event: 36
Last Year
- Delete event: 21
- Issue comment event: 52
- Pull request event: 47
- Create event: 36
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 0
- Total pull requests: 30
- Average time to close issues: N/A
- Average time to close pull requests: 12 days
- Total issue authors: 0
- Total pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 1.53
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 30
Past Year
- Issues: 0
- Pull requests: 30
- Average time to close issues: N/A
- Average time to close pull requests: 12 days
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 1.53
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 30
Top Authors
Issue Authors
Pull Request Authors
- dependabot[bot] (30)
Top Labels
Issue Labels
Pull Request Labels
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