Scientific Computing with Python
Austin, Texas • July 6-12, 2015
 

SciPy 2015 Sprints Schedule

Join us for a 2-day open source hackathon! Sit with the authors of open source packages you have been using and contribute a feature you have been needing. Or help push a new and exciting project that will change your life. Don't know how to contribute to project? No problem, we'll teach you at the Sprint tutorial.

We encourage you to fill out the sprints form in order to have your sprint (or sprint idea / request) published on this page! We currently have confirmed sprints for the following packages. See the bottom of the page for details about each of the currently planned sprints:

  • IPython / Jupyter
  • matplotlib
  • NumPy
  • pyugrid
  • scikit-image
  • SymPy/SymEngine/PyDy
  • VisPy and PyQtGraph
  • Conda
  • scikit-learn

Sprints are free for all, but please register to receive a badge and access to the sessions.

Saturday, July 11
8:00 AM - 9:00 AMBreakfast
Served in the Tejas Room on Level 2
9:00 AM - 9:30 AMSprint Kickoff
Room 204
Sprint leaders will speak briefly about their projects and the rooms will be assigned.
9:30 AM - 11:00 PM"How to Sprint" Tutorial
Room 204
A brief tutorial for new sprinters on how to work with open source projects and use git and github to coordinate with other contributors.
11:00 AM - 6:00 PMSprints (Rooms assigned at kickoff)
No location
6:30 PM - 8:30 PMTexas BBQ Dinner
Scholtz's Beer Garten, 1607 San Jacinto Blvd (walking distance from AT&T Center)

Sunday, July 12
8:00 AM - 9:00 AMBreakfast
Served in the Tejas Room on Level 2
9:00 AM - 6:00 PMSprints (Rooms assigned at kickoff)
No location

Sprint Session Details

Name of package or theme Description of the goal(s) of the sprint, tasks planned and why it is important. Minimum level of Python expertise needed
Is familiarity with package required?
VisPy and PyQtGraph This sprint will be a chance for the VisPy/PyQtGraph development communities to mingle with the larger scientific python community. Anyone interested in the future (or present) of high-performance graphics is welcome to join and learn about contributing to these projects or incorporating them into your own projects.

Beginner No
Scikit-image scikit-image is a collection of algorithms for image processing (see http://scikit-image.org)

At this sprint we aim to address open issues [0], review and merge pull requests [1] and expand our user guide [2]. Also, the project website could certainly do with an artistic eye. If you are brave, you can even help us implement a new feature! [4]

[0] https://github.com/scikit-image/scikit-image/issues
[1] https://github.com/scikit-image/scikit-image/pulls
[2] http://scikit-image.org/docs/stable/user_guide.html
[4] https://github.com/scikit-image/scikit-image/wiki/Requested-features

Beginner No
NumPy Let's make NumPy better. All are welcome.

Intermediate Yes
pyugrid Pyugrid (https://github.com/pyugrid/pyugrid) is the package to enable Python IO and manipulation of netCDF files conforming to the UGRID convention (https://github.com/ugrid-conventions/ugrid-conventions).

UGRID conventions apply to data distributed across unstructured grids (i.e. grids which are neither regularly nor rectangularly spaced, such as finite element models). Unstructured grids are employed by many advanced meteorological and oceanographic models. Pyugrid is critical to several analysis applications working with unstructured grid model output. The pyugrid project began at the SciPy 2013 sprints and continued in the SciPy 2014 sprints. A pyugrid poster is to be presented at SciPy 2015.

This sprint will work through a number of open issues, solidify agreement on the future roadmap, and foster pyugrid community.

Intermediate Yes
SymPy SymPy:
- Figure out how to manage all the issues and pull requests we get.
- Review GSoC PRs.

SymEngine
- Build a conda package so that the Python wrappers can be used seamlessly in SymPy.

PyDy
- Build our example gallery and clean up the website.
- Implement some highly desired features.

Beginner No
IPython/Jupyter We will be focused on getting everything in order to finish releasing 4.0 of the IPython and Jupyter packages.
Intermediate Yes
 CondaCome with any questions, discussions, or feature requests about conda or conda packaging. Intermediate
No
 scikit-learnThis sprint will be an opportunity to wet your feet with the project and work on some easy issues to get to know the development process.
Some core developers will be present and guide you in your contribution.
For people that are already quite familiar with the library, we can find more challenging issues to work on.
Beginner
Yes