NumPy is a community-driven open source project developed by a very 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 the community thrive.
We offer several communication channels to learn, share your knowledge and connect with others within the NumPy community.
The following are ways to engage directly with the NumPy project and community. Please note that we encourage users and community members to support each other for usage questions - see Get Help.
This list is the main forum for longer-form discussions, like adding new features to NumPy, making changes to the NumPy Roadmap, and all kinds of project-wide decision making. Announcements about NumPy, such as for releases, developer meetings, sprints or conference talks are also made on this list.
On this list please use bottom posting, reply to the list (rather than to another sender), and don’t reply to digests. A searchable archive of this list is available here.
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Please note that GitHub is not the right place to report a security vulnerability. If you think you have found a security vulnerability in NumPy, please report it here.
A real-time chat room to ask questions about contributing to NumPy. This is a private space, specifically meant for people who are hesitant to bring up their questions or ideas on a large public mailing list or GitHub. Please see here for more details and how to get an invite.
If you would like to find a local meetup or study group to learn more about NumPy and the wider ecosystem of Python packages for data science and scientific computing, we recommend exploring the PyData meetups (150+ meetups, 100,000+ members).
NumPy also organizes in-person sprints for its team and interested contributors occasionally. These are typically planned several months in advance and will be announced on the mailing list and Twitter.
The NumPy project doesn’t organize its own conferences. The conferences that have traditionally been most popular with NumPy maintainers, contributors and users are the SciPy and PyData conference series:
Many of these conferences include tutorial days that cover NumPy and/or sprints where you can learn how to contribute to NumPy or related open source projects.
To thrive, the NumPy project needs your expertise and enthusiasm. Not a coder? Not a problem! There are many ways to contribute to NumPy.
If you are interested in becoming a NumPy contributor (yay!) we recommend checking out our Contribute page.