PyData Tel Aviv #19 - Open-Source Sprint

In this meetup, we will be having the first PyData Open-Source Sprint!

Whether you are a seasoned open source contributor or you are just interested in starting out, you are welcome to come and contribute for the night. This will be different in format from the typical PyData event, as we will have only two quick talks and for the rest of the time participants will work on their favorite open-source project.

This event is organized by PyData Tel Aviv and Matti Picus of the Berkeley Institute for Data Science.

Thank you to the Israel Tech Challenge (www.itc.tech) for sponsoring and hosting this event!

Schedule
6:00pm-6:30pm: Reception and Shmoozing
6:30pm-6:40pm: Introductory words
6:40pm-7:10pm: Lectures by two open-source contributors (Matti Picus and Shay Palachi)
7:10pm-7:20pm: Break
7:20pm-7:40pm: git/github/OSS tutorial by Uri Goren
7:40pm-9:30pm: Open-Source sprint

Talk Descriptions
First Talk:
Title: Working full-time on Open Source Software
Speaker: Matti Picus

Abstract: "I began a two-year contract to work on NumPy in April. In this talk I will share how it happened, what it is like to work full-time on open-source software, how it differs (or not) from working in a start-up or large firm, and why you should get involved. I will also ramble on a bit about NumPy itself, and PyPy - a python interpreter with a JIT.

Second Talk:
Title: Pied PyPIer: Why packaging is important for both close and open data science projects
Speaker: Shay Palachi

Abstract: When working on data science projects we are often tempted to leave our code to rot in scattered notebooks or Python modules deep in the project’s repository.

However, even when you can’t release parts of your code as open source, breaking some important components into standalone Python packages can help with managing technical debt and code maintenance, facilitate in-house code reuse and repurposing, and make production-ising and deployment of code easier.

In this talk I'll try to demonstrate the ways treating your components and problem solutions as independent packages can benefit both your colleagues and (present and future) you, and review the tools Python provides for building and managing these packages, both in-company and openly.

I will also share from my experience in packaging some of my code, and discuss the extra benefits from open sourcing packages even when they are used mainly internally.