Scipy and the first few GSoC weeks

Hi all,

We're about three (and a half) weeks into the GSoC and it's been one crazy ride so far. Being my first experience working in OpenSource projects and not being much of an expert in statistics was challenging at first, but I think I might be getting the hang of it now.

First off, for those of you still wondering what I'm actually doing, here is an abridged version of the abstract from my proposal to the GSoC (or you can click here for the full proposal):

"scipy.stats is one of the largest and most heavily used modules in Scipy. [...] it must be ensured that the quality of this module is up to par and [..] there are still some milestones to be reached. [...] Milestones include a number of enhancements and [...] maintenance issues; most of the scope is already outlined and described by the community in the form of open issues or proposed enhancements."

So basically, the bulk of my project consists on getting to work on open issues for the StatisticsCleanup milestone within the statistics module of SciPy (a Python-based OpenSource library for scientific computing). I suppose this is an unusual approach for a GSoC project since it focuses on maintaining and streamlining an already stable module (in preparation for the release of SciPy 1.0), rather than adding a new module or a specific function within.

The unusual approach allows me to make several small contributions and it gives me a wide (although not as deep) scope, rather than a narrow one. This is precisely the reason why I chose it. I feel like I can benefit (and contribute) a lot more this way, while I get acquainted with the OpenSource way and it also helps me to find new personal interests (win-win).

However, there are also some nuances that may be uncommon. During the first few weeks I have discovered that my proposal did not account for the normal life-cycle of issues and PRs in scipy; my estimations we're too hopeful.

One of OpenSource's greatest strengths is the community getting involved in peer reviews; this allows a developer to "in the face of ambiguity, refuse the temptation to guess". If you didn't get that [spoiler alert] it was a reference to the zen of python (and if you're still reading this and your name is Hélène, I love you).

The problem with this is that even the smooth PRs can take much longer than one week to be merged because of the back and forth with feedback from the community and code update (if it's a controversial topic, discussions can take months). Originally, I had planned to work on four or five open issues a week, have the PRs merged and then continue with the next four or five issues for the next week but this was too naive so I have had to make some changes.

I spent the last week compiling a list of next steps for pretty much all of the open issues and I am now trying to work on as many as I can at a time, thus minimising the impact of waiting periods between feedback cycles for each PR. I can already feel the snowball effect it is having on the project and on my motivation. I am learning a lot more (and in less time) than before which was the whole idea behind doing the Summer of Code.

I will get back in touch soon. I feel like I have rambled on for too long, so I will stop and let you continue to be awesome and get on with your day.

Cheers,
Abraham.

My motivation and how I got started

Hello all,

It's been a busy couple of weeks. The GSoC has officially begun and I've been coding away but before I go heavy into details, I think I should give a brief introduction on how I found SciPy and my motivations as well as the reasons why I think I got selected.

The first thing to know is that this is my first time contributing to OpenSource. I had been wanting to get into it for quite a while but I just didn't know where to start. I thought the GSoC was the perfect opportunity. I would have a list of interesting organisations with many sorts of projects and an outline of the requirements to be selected which I could use as a roadmap for my integration with the OpenSource community. Being selected provided an extra motivation and having deadlines was perfect to make sure I stuck to it.

I started searching for a project that was novice friendly, preferably in python because I'm good at it and I enjoy using it but of course, the project had to be interesting. Long story short, I found in SciPy a healthy and welcoming community so I decided this might be the perfect fit for me.

The first thing I did was try find an easy-fix issue to get the ball rolling by making my first contribution and allowing one thing to lead to another, which is exactly what happened; before I knew it I was getting familiarised with the code, getting involved in discussions and exchanging ideas with some of the most active members of the SciPy community.

In short, what I'm trying to say is: find your motivation, then find something that suits that motivation and get involved, do your homework and start contributing. Become active in the community and things will follow. Even if you don't make it into the GSoC, joining a community is a great learning opportunity.

Cheers,
Abraham.