Tonight I’m giving a lightning talk at PyLadiesATL called “Five Things I Learned at PyOhio”, and I wanted to share it here in case you weren’t able to make the meeting, or are curious about what I covered!
PyOhio is an amazing FREE conference that was held this year in Columbus, Ohio at the Ohio Union. The dates were Saturday August 1 and Sunday August 2, with sprints on Friday July 31 and Monday August 3. Thanks to the organizers and sponsors for making this unforgettable experience possible, and to each of the speakers for taking the time to prepare and deliver such thoughtful, helpful talks. Below, I highlight a few of them.
1) Diversity? You Gotta Want It
Stephanie Hippo’s talk “You Gotta Want It: Building Up Women in Computer Science” was possibly the most honest, critical, and at times damning talk I’ve ever heard about a group’s journey towards becoming more inclusive, welcoming, and ultimately, diverse. What I loved about Stephanie’s delivery was how very much she owned the fact that her group hadn’t been welcoming. It reminded me that the first step in recovery is admitting you have a problem. But to even be able to admit that problem, Stephanie had to critically look at the way her group was doing things – starting with the data – and have hard conversations with her colleagues about why things should change.
It’s not enough to simply say that you want things to be different. Like Stephanie’s family’s motto: you gotta want it. When you realise that you don’t like the diversity distribution of a given team/organization/project, admitting you have a problem is only the first step. It must be swiftly followed by a commitment to examining critically how things got the way they did, and a resolution and plan to address the issues structurally. And hey, if you can find time to tell the rest of us how you did it, all the better! Thanks, Stephanie, for your amazing talk and actionable suggestions.
2) The Pomodoro Technique
I thoroughly enjoyed Ann Schoenenberger’s talk “Learning to Learn Python”. Ann covered the challenges and opportunities confronting the autonomous learner from a personal perspective and from many conversations with other women coming to STEM from non-traditional backgrounds. One of the most helpful takeaways I got from her presentation was the description of the Pomodoro Technique. Now, if you’re a Pomodoro devotee and I’m totally butchering it, I apologize in advance. But the gist of the technique, as I understood it, is to work without distraction for 25 minutes, and chase that work with a 5 minute break. Another 25 minute session can come next, with a 5 minute break after.
Ann shared how budgeting time like this had been really helpful in keeping on her track as she learns Python. And while 50 minutes a day of concentrated study isn’t going to turn you into a programmer overnight, over time – and with discipline – it can be a helpful step towards reaching your goal. I have been employing the Pomodoro technique since I learned it from Ann on a near-daily basis and have seen huge gains in my personal study.
3) That cool project? It took a lot of time, and there were plenty of bumps in the road.
Learners suffer from a lot of ailments, and discouragement at slow progress can be right at the top of the list.
But the fact is, complex projects do take a lot of time, even for experienced developers. Doug Hellman’s talk “How I built a power debugger out of the standard library and things I found on the internet” was, as he said, less about the actual code, and more about the process of building his project Smiley. When he got started, he asked himself, where do I start? What do I do first? What do I want to accomplish? And then: well, what do I know? He emphasized that throughout the nearly two-year period of building Smiley, he continually checked in with himself about what he already knew and what he wanted – or needed – to learn to make it happen.
In Allen Downey’s book Think Python, he draws a comparison between the act of debugging and programming itself:
For some people, programming and debugging are the same thing. That is, programming is the process of gradually debugging a program until it does what you want. The idea is that you should start with a program that does something and make small modifications, debugging them as you go, so that you always have a working program.
In Doug’s presentation about building Smiley, I heard all of this. So whether you’re a Python expert building a power debugger out of the standard library and things you found on the internet, or a new coder trying to solve a Codecademy puzzle, follow this same process. Start with what you know, make a list of what you want to learn, and continuously be open to the dynamic process. And, importantly: be patient with yourself!
4) Data Science Resources
Since Atlanta PyLadies said they were really, really, really interested in data science topics, I tried to attend as many of these talks as possible. Michael Becker’s “Data Science: It’s Easy as Pyǃ” was one of the standouts. I wanted to include an image of his resources slide since I thought it might be of interest to our PyLadies.
Here are those links:
5) It’s okay to bring exactly who you are to the experience of writing Python
My dear friend Anna recently asked me for a quote about why I love the Python/Django community for her sure-to-be-amazing upcoming DjangoCon talk. There’s so much to love about this community, but perhaps my favorite thing is that we can bring exactly who we are to the experience of building software together. From a non-traditional background as a cook, I’ve felt nothing but enthusiastic welcome from each of you. And I’ve also seen this diversity modelled in my colleagues, who play e-bassoons – like Lars pictured above – sew quilts, bake cupcakes, bring their families to conferences, and more.
It’s important to me that we don’t just have lives beyond our work, but that we share our lives *within* our work. To me, that makes all the difference.
When I was invited to give my first talk at a Python conference – PyTennessee – I knew that I really wanted to bake cookies and have them available before my talk. When I mentioned this to a friend, she discouraged me, saying that I shouldn’t. She was worried that I wouldn’t be taken seriously, or that it would somehow make me look bad.
I know she meant well, but after thinking on it a moment, I decided that I would bring eight dozen cookies. And not only would I bring them, I’d wear a flouncy Betsey Johnson dress while giving my talk. And you know what? Aside from my outrageous nervousness, it could not have been a better experience! I met amazing people, and we ate cookies and talked Python together. What more could you want?
So, please feel invited to bring exactly who you are to this activity. If the recent #ILookLikeAnEngineer debacle taught us anything, it’s that you can look like an engineer, no matter what you look like or what you do in your spare time! And don’t let anybody tell you differently – especially if cookies are involved.
Bonus Round: PyLadies are Everywhere!
Okay, so this one was mostly just for fun. But I wanted to share this image to illustrate that we PyLadies are all over, and we’re doing good things in our community to help women learn Python.