PyDev of the Week: Lorena Mesa

This week we welcome Lorena Mesa (@loooorenanicole) as our PyDev of the Week! Lorena is an organizer for the PyLadies Chicago group and a director at the Python Software Foundation. You can check out some of the things that she is up to on her blog or via her Github page. Let’s spend a few moments getting to know her better!

Can you tell us a little about yourself (hobbies, education, etc):

Hmmm … I have been told that I’m a bit eclectic. So let’s start with the basics, in my day to day gig I am a proud member of GitHub’s software intelligence systems team as a data engineer. In my etc hours I do such things as co-organize PyLadies Chicago and serve as a Director for the Python Software Foundation.

Things I do for fun?

• I’m an avid runner having taken on the Chicago Marathon 13 times now. Why? I encourage you to read Haruki Murakami’s “What I talk about when I talk about running” before you ask me that.
• Jazz, italo disco, and loud 1980s ballads are equal parts guilty pleasure for me. Meaning of course I’ve been learning the sax and getting pretty good at it lately. (Yes, I can play Careless Whispers).
• I’m learning Klingon – https://www.kli.org/.

You can find my random musings when I post on my personal blog at lorenamesa.com on such things as traveling, tech, and other tidbits.

Why did you start using Python?

I began using Python as an Obama for America (OFA) staffer around 2008. At the time I was pursuing my political science degree from Northwestern and working on the Latino Vote team for OFA. Some of the tasks we were looking to accomplish as a part of our outreach included identifying and ultimately predicting patterns of Latino voter behavior. Luckily we had many technologists on hand who helped us think about how we could do this, and given the data set and tech we were using for outreach (yes, this is the early days of social media … Twitter how novel!) programming was an obvious fit. I had the stats background, understood the problem space, and before I knew it was writing my first Python “programs” to help us target and reach our desired voting demographic.  

What other programming languages do you know and which is your favorite?

I am not a classically trained computer scientist, far from it actually. Coming from social science research and applied mathematics when I decided I wanted to pursue a career in engineering I jumped two feet into a coding immersion program. This predated the data science bootcamps and masters we see today, therefore it was a full stack program teaching me JavaScript, SQL (which I already knew), and Ruby. JavaScript became a quick friend. JavaScript was such a different and at times strange entity, but I loved how it invited me to think differently and solve different problems. Namely I was using JavaScript for data viz. I have since fallen in love with functional programming and fully enjoy Scala.

What projects are you working on now?

I always have a personal project in flight and a more professional project in flight.

On the professional front, I’ve been tinkering with deep learning. Since joining GitHub this past October 2018, I’m working closely with the machine learning team on the software intelligence systems team. While I was a previously a member of a data science team in my previous role, that team used a a more traditional Python scientific stack whereas GitHub we’re heavily invested in deep learning. 

Therefore I’ve been self teaching by working through various white papers (I highly recommend the Morning Paper and Papers We Love) focused on deep learning. What specifically does this mean? Well I’m trying my hand at using deep learning to create a recurring neural network to generate a telenovela “script”. If you’re curious about that you can see what I’ve been tinkering with from my NorthBay Python talk.

I’ll be expanding on this talk by comparing and contrasting how to generate a telenovela script in three popular Python frameworks – keras, tensorflow, and PyTorch. 

As a self-dubbed “forever student” or “just in time learner” I am always trying to generate content that would be accessible to my peers or those right behind me in terms of overall experience. Teaching is a means to an end, but also something I am deeply committed to.

Now that I am squarely in the deep learning camp, I am realizing yet again the knowledge silos and lack of accessible resources that exist in this space. Yes, projects like Fast.AI are doing some impressive things with MOOCs but not everyone needs a full on course. I am exploring the idea of an online community that crowdsources resources akin to the style of CodeNewbie –  for learning data science. I’d like to target engineers and those outside academia. This is early days yet but we’ll see where it winds up.

And lastly I continue to channel my activism by continuing to advance and discuss the need for ethics in computer science. I’m judging the Mozilla Foundation Responsible Computer Science Challenge with other leading industry experts – and am continuing to make efforts on that front. 

Which Python libraries are your favorite (core or 3rd party)?

Dataclasses are the best, hands down. As a data engineer they make my life simple and easy, removes boilerplate, and let me get to work quickly. By that same logic I am a big supporter of Cookiecutter, a project maintained by such folks as Daniel Greenfeld and Audrey Roy Greenfeld.

I recently saw a talk at PyCon Sweden by Diego Moreda Rodriguez on an open source Python quantum computing library that my inner physics nerd is deeply intrigued in — qiskit.

How did you get involved with PyLadies?

Chicago, my home base, has a very healthy and active Python User Group (affectionately known as ChiPy for short). Yet when I started down my path into engineering, I found that ChiPy was missing some very important things including: beginner friendly content and really anyone that looked like me in the user group. Add that ChiPy’s monthly meetings began quite late it just wasn’t practical or very accessible to me.

My search for a group that mirrored my core values such as accessibility, diversity, and inclusivity led my to the `pip install pyladies` documentation on PyPi. An email later, I was in touch with PyLadies Esther and Lynn and starting a chapter in Chicago in late 2013!

It was very humbling to start a chapter in Chicago since I was quick to learn how supportive other Python groups were of our work but also how some of the folks active in Chicago simply hadn’t realized some of these inequities. As organizers we’re always learning and listening, take the experience Pyladies Chicago had when invited to offer input and feedback on the new ChiPy Code of Conduct this past year.

Do you have any advice for someone who wants to start a local chapter of PyLadies or DjangoGirls?

Raise your hand and ask a question, any question! Or just ask the question, forget raising your hand!

I have been truly humbled by the willingness of Pythonistas to help me in my journey, be it from starting a new chapter of a group to running to the Python Software Foundation board. The Python community is the most remarkable thing about Python in my opinion, use it!

And to put my money where my mouth is, I am always happy to talk with folks about their work, questions, and more. You can email me at lorena@python.org for any of your Python questions!

Is there anything else you’d like to say?

Since I’m not sure when this will be posted, here’s to wishing you a fruitful 2019 — Pe’vIl mu’qaDmey!

Thanks for doing the interview!