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Sprints

Doug Latornell edited this page Nov 19, 2018 · 56 revisions

PyCon Canada 2018 Sprints - 12-13th November

Slack: python-sprints.slack.com

PyCon Canada Development Sprints is a day of intensive learning and development on an open source project of your choice, in a team environment. It's a time to come together with colleagues, old and new, to share what you've learned and apply it to an open source project.

PyCon Canada provides the space and infrastructure (network, power, tables & chairs); you bring your skills, humanity, and brainpower (oh! and don't forget your computer).

This event will take place at The Design Exchange located at 234 Bay Street in Toronto.

Enter your sprint here:

  • include links to your project
  • include project contact information
  • include new contributor tickets and on-boarding info
  • include sprint goals
  • encourage people to add their names to your sprint

Template

## My Awesome Project

* <https://github.com/my/awesome-project>
* Main Contact: [Sprinter Lead](mailto:sprinterlead@mailinator.com)
* Interested in sprinting on This Project? Add your name:
* [Sprinter One](mailto:sprinterone@mailinator.com)
* Sprint tasks / issues list:  https://github.com/my/awesome-project/issues

Projects

Flask & Werkzeug

Pandas Documentation Sprint

Imagination Brainstorming Sprint

PyEnvDiff - Feedback & Iterate Sprint

Validada - Make 3.x Compat Sprint

  • https://github.com/jnmclarty/validada
  • Jeffrey McLarty @ gmail.com (Guy in blue plaid hoodie, @jnmclarty on slack)
  • If anybody wants to help me upgrade to python 3, I could guide somebody to learn the moderately advanced python concepts used to make the API. I'll be straddling this and/or the other project I linked above, depending on interest.

Deep Reinforcement Learning/Machine Learning - beginner/ML-curious friendly

  • Main Contact: Sprinter Lead
  • Interested in sprinting on This Project? Add your name:
  • Tasks (edit your goals in below)
    • Play with various base approaches (DDPG, Deep Q Networks) on Toy AI Gym Tasks
      • Truly toy environments (e.g. Tic Tac Toe) to see if it improves iteration speed
    • Help setup developer environments for ML/Deep Reinforcement Learning
    • Explore tools for (formal or semi-formal) experiment tracking
    • Maybe do some cloud spin-up (Colaboratory, Azure, etc)
    • If we get enough time, explore:
      • Curiosity-Driven Exploration
      • Dropout as Bayesian Approximation

karmapi

setuptools

gunicorn

Interested in sprinting on a Project

Other projects that can have support from organizers if sprinters are interested:

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