PyData NYC Sprint Night: python-dateutil

Apr 12, 2018 · New York, United States of America

Join us for our first PyData NYC Sprint night. At each Sprint Night, we'll pick one or more open source projects and attendees will all work to improve the software infrastructure in the Python data stack!

For our first meeting, we'll have Paul Ganssle, maintainer of the python-dateutil project, who will be leading a sprint on dateutil, which is a core dependency of matplotlib, pandas and many other libraries and applications: https://github.com/dateutil/dateutil

Food and drinks will be available, sponsored by Bloomberg (https://www.bloomberg.com/company/).

Wiki page with useful information for the sprint: https://github.com/dateutil/dateutil/wiki/PyData-NYC-Sprint---2018-April-11

What to expect
---------------------
Welcome people of all skill levels - whether you're an open source beginner or a github guru, you'll definitely be able to contribute. We can work individually or in groups, however you feel comfortable.

In addition to the maintainer, others familiar with the github workflow will be available to help guide you in making a contribution to the library.

What to bring
-------------------
- A laptop
- A government-issued identification card

To be extra-prepared:
- Make sure you have `git` installed
- Fork and clone (https://blog.scottlowe.org/2015/01/27/using-fork-branch-git-workflow/) the dateutil repository (https://github.com/dateutil/dateutil).
- Check out the dateutil issue tracker to get an idea of what you might want to work on. Specifically take a look at issues labeled "help wanted": https://github.com/dateutil/dateutil/issues?q=is%3Aopen+is%3Aissue+label%3A%22help+wanted%22

Event organizers
  • PyData NYC

    PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to)

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