Welcome, Leah’s origin story

Leah 0:00

Through that process of learning myself how to program, how to process data, how to make workflows more efficient, and I learned it all the hard way. I decided that I really wanted to give back to the community and help others learn some of those hard skills that are also superpowers to empower them in their careers and in their research.

Julian 0:21

Hello and welcome to the Pie Blights Podcast, where we talk about Python, career, and mindset.

Advert 0:27

We're your hosts. I'm Julian Sequera. And I am Bob Belldibles. If you're looking to improve your Python, your career, and learn the mindset for success, this is the podcast for you. Let's get started.

Julian 0:40

Welcome back to the Pie Bytes Podcast, everyone. This is Julian, and I'm here with a very special guest today. This is Leia Wasser, who is the executive director and founder of Pi OpenSci. And we will dive into all of this in a moment. But first, Leia, welcome to the Pie Bytes Podcast. I'm so excited to have you here today. Um, yeah, why don't you introduce yourself to everyone who doesn't know who you are?

Leah 1:04

Thank you so much, Julian. I am super excited to be here today. My name is Leah Wasser, and as you mentioned, I founded an organization, a nonprofit organization called Pi OpenSci. And our focus is on making open source, well, making scientific open source more inclusive for people everywhere around the world. And we run a peer review program. We have a whole bunch of different um, I'll talk about Pi OpenSci in a little bit. Let me introduce myself.

Julian 1:40

No, no, that's fine. Go for it. Go for it. But yeah, I'll tell you what, let's let's do some background on you first, and then we'll jump into Pi OpenSign a bit. No, no, I love it. Okay. I love it. Okay. Yeah.

Defining open science and reuse

Leah 1:51

Um, so yeah, so I founded Pi OpenSign, but before I did that, I actually um have a PhD in ecology. So I'm trained as a scientist, and I am not someone that's ever actually taken like computer science or data science, but I fell into this space by mistake because as a researcher doing my PhD, I had huge amounts of data. I was working with um remote sensing data. It was really large, and I needed to use something that wasn't Excel. And so that was really my introduction to programming. I had a friend that said, hey, I use this thing called MATLAB and look what it can do. And he wrote this little script that processed files that I was manually trying to update and like get into the correct formats. And it was just a superpower. I mean, I was like, How did you do that? You processed all my data and it ran in like 30 seconds. And I was like, I need that superpower. And so I'm gonna learn how to code. And that's really where my whole career trajectory changed for me. I found data-intensive science, but it was hard to learn it. And so through that process of learning myself how to program, how to process data, how to make workflows more efficient, and I learned it all the hard way. I decided that I really wanted to give back to the community and help others learn some of those hard skills that are also superpowers to empower them in their careers and in their research.

Julian 3:21

That is so cool. I love that. I love how everyone has that pivotal moment where they get exposed to code in some way, whether it's a classroom in school or someone at work, you know, as you were saying, say, saying, hey, look, I did that in two seconds. What are you spending half a day crunching that data for? You know. And then you just get infatuated with it and you see how it works in many different levels, whether it be for work, for just playing, for fun around the house, whatever it is. I I I love it. So this is really cool. So so you're self-taught. So all of this stuff, uh, when it comes to the code side of it, you're you're self-taught.

Leah 3:58

Yeah, yeah, I'm completely self-taught. And you know, in some in some spaces, that can be challenging because maybe some of those fundamentals I'm I've been learning as I go. But on the other hand, being someone in science, and when I was doing my PhD, data science wasn't a thing like it is now. So there weren't programs all over the place. And so for me, going through that process and being humbled by that process, I think it helped me better understand someone else going through that process and trying to make programs and classes and workshops more inclusive to different types of learners just became something that I was really passionate about because I don't want other people to struggle the way I kind of did. I kind of fumbled my way through and got to a great output. And so if I can help other people, I just that makes me feel really, really good.

Julian 4:50

Oh, that's cool. I I love hearing that. The the um not everyone has it, but that innate desire to, well, I went through the fire, and here's what I wish I had when I was doing it. I'm gonna do that for other people. That's that's really special. That's kind of what led Bob and I to start Pie Bites, right? And do what we do with coaching and and all of that. And so hearing this, but from the science side of it is super exciting to me. I love hearing it. Um, okay, so look, we'll we'll dive into this, um, into this a little bit. I've this so everyone listening, as you know, I do zero prep for these podcasts. I I like it to be very casual, very relaxed. So Leia has very kindly sent me through a couple of things, but I am there's so much to cover off here. So there's gonna be no structure. We're just gonna weave and go through this stuff and see what happens um and see what kind of conversation we lead to. But I think the first question I had, Leia, as someone who's not uh on the science side of Python, and we've had people through our programs that are scientists, and so they would understand this. So to those people like Robert, I apologize. I look like a fool saying this stuff. But um, but what is could you define when I see the term open science, right? So what is that about? And I imagine that this is going to lead us into a conversation about Pi OpenSide, but what what is open science in general? Is is there a definition for that?

Why Python for scientific work

Leah 6:20

Yeah, that's a great question, Julian. And it's in some ways, there's a lot of different types of definitions in terms of how broad they are of open science, but really from a data science and code perspective, if we zero in on it, it's really about making a scientific data workflow or a research workflow such that someone else can reproduce it or reuse it. And the fundamental idea of open science is that if you have scientists, researchers, people all over the world that are studying different things, it would be much more powerful work if someone could take the work that they had already done and build directly on top of it without having to recreate that workflow. So there's a transparency piece of it from, you know, a publication side where the methods are really visible and you can see how, let's say, it was a data set that was processed, that becomes very transparent if someone else can look at it. But there's this other, even bigger and more powerful feature that open science provides, which is really people being able to build on top of each other's work. And that really accelerates or can speed up the rate that we're discovering and learning new things about the world that we live in.

Julian 7:34

That's really cool. The I like how this very much, I mean, I assume that's where the term open comes from with like with open source, right? So when I think about open source, I think about what we traditionally, you know, connect with just applications people build, and then the community comes in, builds on top of it, as you've said.

Leah 7:54

Yeah, exactly.

Julian 7:55

And that works perfectly with the science model and scientific research and the way uh peer review works, and the science is not generally built by one person, or scientific theory isn't just one person, it's through years of research from other people, and they work with each other and build upon what each other do. So this is uh have done. So this is really, really cool. I I I've never thought about this from a coding perspective. So in that case, then based on what your experience with that, and you said you've you've been teaching uh data for over 20 years, use several languages. Um I guess this is a simplistic question I'll ask anyone, but why Python? How how have you landed on Python in this space?

Founding PyOpenSci: the gap

Leah 8:38

Yeah, that's a great question. Um, why Python? So, yes, I've bounced around between a bunch of like several different languages. Um, I started in, well, I started in MATLAB because I had friends that knew it. And so it was like that was my kind of gateway drug, so to speak, to the superpower. And um, and then I ended up in the R space because I I built a program at an ecological observatory. And there are some parts of science that use different programming languages. So R is really popular in the ecology kind of natural science space. And that was actually my home base for a while. And so I worked at a place called Neon. It was an ecological observatory, and we just knew a lot of our users of the data were going to be using R. So I ended up switching to Python. I built a program at CU Boulder, and the main reason that we switched was using a lot of um earth systems data, a lot of remote sensing. And Python is just widely used in that space. And so I switched over. There's a lot of um built-in support for larger data sets, and it was a it was really valuable for that. And also from a career perspective, it's one of the most, if not the most popular languages in the world in tech. You know, we did surveys and research and stuff. So it just made a lot of sense for students thinking about getting jobs to use Python. Now, what I didn't know when I made that switch is that there's also this incredible community around Python and coming back to like the open, the idea of openness and like inclusion, I love the community. I mean, I really, really do. And so part of me, I've stayed because of just the job demand and wanting to help people, empower people with careers when I was at CU. But then also I just I absolutely love it.

Julian 10:37

Yeah, that's cool. Yeah, I think it was. Did you did you see the uh Python documentary recently? Have you watched that?

Leah 10:44

Yeah, yeah.

Julian 10:45

I I think it was who was it? I think it was Brett Cannon that says in there he didn't mean to coin the term, but come for Python, come for the language, stay for the community. Stay for the community, yep. Yeah, I I definitely I see that here more than anywhere else in any other language or even any other industry, right? Of all the different things that you see and do, you just you go to a PyCon and you just feel you're at home.

Leah 11:08

Yes. So yes, that and it's it's so cool and it's so hard to explain to people. Like if you had said that to me or like Brett had said that to me, or anyone when I just was starting to use it, I wouldn't have understood. And then, yes, you go to a PyCon or any Python meeting, we have SciPy, and just the vibe of those meetings is is incredible, and people in those communities are like now my close friends, you know. It's I I love that.

Julian 11:37

Yeah, I I secretly love it just because it means now everywhere I travel, I have people that I can sleep in on their couch without having to buy it to travel pass too, huh? Or at least someone to go out to dinner with me. So yeah.

Leah 11:54

I have a friend, yeah.

Julian 11:57

So now I have someone in Boulder I can come and come and hang out with.

Leah 12:02

You do have a friend in Boulder.

Julian 12:05

Um, all right, so so this is cool. So tell me then, you know, Pi OpenSide, and you you briefly touched on this, you almost ruined it at the start of the episode where you almost told everything about it. Oh my gosh. We have to start this all over again. Terrible. Um so where did so okay, so just describe if you can for everyone. Um, what is Pi OpenSci the company, right, that you've created and the group that you've created? What is it? But then what I'll touch on after you get into that is why you created it as well, because there's so much mindset, and you know, um, I'm the mindset guy at Pi Whites, and I love to dive into the why because I think it's really inspiring for people to hear motivations and challenges and how you persevered. But I'm getting ahead of myself. So go for it. What is what is Pi OpenSci and how did this come about?

Community, Slack, and peer review

Leah 12:58

Okay, yeah. Um, I love that question. So Pi OpenSci is a nonprofit organization, and our mission is to broaden participation in scientific open source. And we do that by breaking down both social and technical barriers of entry to using Python and open source. And I started PyOpenSci. Um, I guess it was well, I started up PyOpenSci. It's a similar story to how I started programming, where I just saw a need in the in the ecosystem. So I was using R for years, and R just had a very user-friendly get started with the language. Students loved it. It was straightforward to figure out what packages to use. It was just an easier, at least for me, to navigate ecosystem. And when I started teaching Python, I just saw so many pain points that my students were dealing with. And it's funny because a lot of those pain points were things like I didn't understand how a tool that we were using, a package we were using to process some data type, worked. And so I ended up digging through code bases on GitHub to figure it out. And I would look at documentation, and it wasn't maybe simple or like straightforward enough for someone that was a beginner to use. And I just saw all these pain points and I thought, what would happen if there was a community to answer some of these questions and create some resources to help other people in this space get started? And so that was really the initial motivation going to PyPy and seeing thousands of packages, and maybe 20 of them did the same thing, and which one do we want to use to process this scientific data set? And those are there's a lot of energy that went into figuring out what packages to teach and use. And it's not a great use of researchers' time if they have to do that every time they go to sit down and do their work, or if every time they want to package up their code and share it, they have to wade through a lot of confusing documentation. So Pi OpenSci is really about filling this gap, which is a technical gap of how do you share code? How do you make your package something that someone else can use, or your code into a package that someone else can use? And also, how do you find packages that are still maintained and high quality and useful in the research space? And so that's where peer review comes in. Um, we have a process where we co-develop learning resources around how do you package your code? How do you start to think about testing and CI and all of these other technical things that can be really overwhelming for someone that really just wants to write good code that someone else can use?

Julian 15:49

A quick break from the episode to talk about a product that we've had going for years now. This is the Pybites platform, Bob. What's it all about?

Advert 15:56

Now with AI, I think uh there's a bit of a sentiment that we're eroding our skills because AI writes so much code for us. But actually, I went back to the platform the other day, solved 10 bytes, and I'm still secure of my skills because it's good to be limited in your resources. You really have to write the code, it really makes you think about the code. It's really helpful.

Julian 16:15

Definitely helpful as long as you don't use AI to solve the problems. If you do, you're just cheating. But in reality, this is an amazing tool to help you keep fresh with Python, keep your skills strong, keep you sharp so that when you are on a live stream like Bob over here, you can solve exercises live with however many people watching you code at the exact same time. So please check out pybitesplatform.com. It is the coding platform that beats all other coding platforms and will keep you sharper than you could ever have imagined. Check it out now, pybitesplatform.com and back to the episode. Hmm. So, and I've got a question based on what you just said, but there's a community then aspect to this where there's people who come together, right? And um, how do how do scientists that come to your platform to Pi OpenSci how do they communicate with each other? Do you just have like a simplistic question? Is there like a chat area or something like that or a forum?

Academic credit and JOSS DOIs

Leah 17:14

Yeah, yeah, absolutely. We have a Slack community, um, and it's a smaller community. We have about, I think it's around 300 people in our Slack. And it is a community of people that when I started uh working on Pi OpenSci, it was just a few of us having meetings and it's grown into this really beautiful thing. In fact, I'd say that the community piece of Pi OpenSci is the most powerful part because everyone in the community, they just they just care. Like they care about helping other people with their pain points, and they're excited and enthusiastic and supportive, and they can disagree, but we can talk through things. And so yes, the community is the most beautiful piece of Pi OpenSci.

Julian 18:05

That's cool. It's always the people you look after the people and things just happen. I I think that's that's very cool. So okay, so I had the question I was thinking as as you mentioned this, and now that I see how the community works like that, uh so people uh would come to Pi OpenSci uh some let's I'm just picturing a couple of use cases here, real-world scenarios, right? People might come there because they they have to do something in their scientific field, and they might be confused about what package to use, or they've done that search that you mentioned on like PyPI, where you've gone, oh no, there's 20 packages that do the same thing. One hasn't been updated in five years, one was updated last week, which one do I use, right? So they might come to your community to uh get some clarification on that, see what people are thinking. Um, but then also the other uh another use case would be or scenario would be people coming there to discuss which ones of which of those packages to do reviews on them with peers, so peer review, and then decide, yeah, okay, we agree as a group that hey, for this application, this package is probably the most robust or efficient. Is that those two valid scenarios of how people might engage with you?

Leah 19:24

Yeah, the first one is a little bit less rare for someone to come in and say, you know, what tool processes this type of data? What we get a lot of in terms of questions are um maintainers, we have maintainers from around the world. And so maybe they are trying to figure out how to run their tests in CI. Or maybe they're trying to figure out there's Pixie and there's UV and there's PipEx and there's Pip and there's you know all these different tools, and they're like, I don't even know where to start. What should I be using? Do I need lock files? Like there's those types of questions are a lot of are often the types of technical conversations that you'll see are, hey, I've got this like thing happening with this GitHub pull request and git's doing, you know, and so maybe it's those types of conversations. Can someone help? So we have a lot of those kinds of conversations in in our Slack. We also the peer review piece is very important. So the we have a completely volunteer-led peer review process. We have about 20 editors and lots of reviewers. And so people will also submit their package to us. And that's another common scenario where they have a software package, they want to improve it, they also want other people to find it and see it. And so they might come to us and if it's ready for peer review, then they'll dive in and go through this really constructive process that is not about critically, you know, evaluating and like putting down someone's code, like, oh, this isn't good enough. It's about how can we make this better? How can we make this more usable? It's a constructive process, it's a supportive process. And so through that process, they will improve their package, and then more people will be able to use it just through those updates and enhancements to docs and those types of things that happen through every peer review. So that's cool, a very common use case for someone to come to us.

How to get involved and sprint culture

Julian 21:30

That is cool, and and kudos to to you and the uh you said 20 volunteers that that that are doing this. That's very altruistic, right? And something that could have such a huge impact on the world, some of these libraries and packages. And it's all just peer-reviewed in public for free, not sponsored by any anyone or any place. Uh, that is really cool. That is an incredible message. And uh sadly, probably one of the things that just goes under the radar a lot that a lot of people don't realize is kind of work goes on behind the scenes to make these things so efficient and improve over time, right? Um, so are you doing anything to like as people do this kind of work and come to you with these things and and come to the community and go through peer review? Um, my very rudimentary caveman level understanding of the science world and how all of this works. Um how are you highlighting? So just forgive me, and for everyone listening, my understanding when you talk about science, whether it's oh, we had this, we laughed about this the other day. I called I couldn't figure out the word chemistry, right? That was I think it was. I think I was trying to say chemistry and I couldn't couldn't think of the the word. Um but whatever field whatever field of science you're in, as uh one of the I guess levels of measurements of success is how many papers you've written, how many publications you've been in, that kind of thing. So are you is there a way as people spend all this time peer reviewing open source packages and stuff? Is there a way to highlight that so that that counts as uh and I'm doing rabbit hears for those of you listening, not watching, um, so that that counts towards someone's I know status or stature in the scientific world?

Social barriers, impostor syndrome

Leah 23:24

Yeah, that's such a good question, Julian. So uh one of the there's my dog. One of the other challenges, she's quiet all day, and then I have a meeting and she barks. Um so one of the challenges in academia, and it's actually one of the reasons why I left academia, and I have a lot of respect for this space, but what you just hit upon is really a common pain point where there's a lot of emphasis when terms of your CV and your credentials that's placed on a publication. But the challenge there is that a publication is only one piece of the broader scope of work, which is a tremendous amount of work, like that got you to that paper. And if you're thinking about and asking for making workflows reproducible and open, so supporting that open science idea that's going to accelerate the science and allow other people to build on top of your work in this world where we have climate change and all of these huge, profoundly huge challenges, environmental challenges, human challenges, building on top of people's work is integral. So why isn't why aren't the other pieces that go into that paper valued? Why is it just the paper? And that's a fundamental tension in academia that you'll see where, yes, the paper is the valued thing. And you have people that are, you know, publishing papers all the time with all of this infrastructure that supports those publications not being acknowledged. Packages like NumPy and pandas that are used in the scientific ecosystem and beyond that don't have the support or the visibility that they should have in a paper that was used, use those tools to process that data. So the idea of peer review is one that's familiar in academia, but in academia, peer review isn't always the most fun or constructive process. It can be a hard process. Um, and so what if we take that concept of peer review, which has some valid or which has some very good components of other people reviewing something that you've done and apply it to software? And what if we elevate the status of software to being something that's critical to science? So it's the paper, but it's also all the pieces that went into that paper. So that's what we're trying to do from a you know larger scale impact on academia is elevate that um importance of software in the academic space. And we partner with an organization called JOS, the Journal of Open Source Software. So that's an actual journal that if you go through our peer review and you're in scope for JOS, then you can also get a publication and a DOI out of that review process. So imagine now we're reimagining peer review as a constructive process. So it's not, it's critical, but it's constructive and helpful. Your package is being improved through that process, and you can get that academic, you know, the rabbit ear is let's bring them back and get that credit through the DOI from Joss. So it's really a win-win. And the idea is to really just push and question the academic model of the paper is the only thing that that is valued.

Julian 26:45

That's cool. I love that desire and that goal. Um, so you know, rather than wait to the end of the podcast, um, I think this is the perfect time to just say how how can people listening, and we have scientists in our community who will be listening to this, and I'll be sending this episode too as well. Um, so how can people get involved to not just obviously participate in Pi OpenSide, but also support you with the things that you're doing? What's the best way to support you other than just maybe spreading the word, or is that it? And what what do you think?

Leah 27:20

Yeah, that's great. So um definitely spreading the word about us. If you're interested in getting involved, um, if you go to our website, we're always looking for reviewers and editors. So if that's something that someone's interested in, that is a way to get involved. If you're newer to the open source space, but still are interested in reviewing, and reviewing is a great way to learn more about how packaging works and what it's like to use someone else's tool. Um, we also offer support for people that are newer that want to get involved in peer review and just kind of boost some of their critical like evaluation of code or usability of a package, some of those skills. Um, we also hold, if you happen to attend meetings like SciPy or PyCon, um, one of the other things that we do is we host beginner-friendly sprints. And what that means is that um, and we get a lot of non-scientists to those events too. And the beauty of those events are we will help you learn about like creating your first contribution. So using Git and GitHub, and we normally um have a lot of people that attend attend those events. So those are a couple of ways to get involved. And then the final thing would be to just keep an eye on our events page on the website. Um, we hold events periodically, and you could potentially join one of those if you were interested.

Julian 28:41

Are those more virtual events or in-person as well?

Leah 28:45

Um, it's a mixture, it's mostly virtual, but sometimes um, so for example, in the summer when we've got PyCon and PyCon US and SciPy, when we're going to a lot of meetings, we'll have in-person events, and then the rest of the year it's mostly online.

Julian 29:02

Cool. That's wicked. I I love hearing that. Okay, so we'll we'll make sure we have links and everything to all of this um after, but I'm immediately just thinking, all these cool things we can do together. That's that's gonna be awesome. So um no, so I love that. And okay, so that's the technical side, and I love that there's almost you know, coaching involved there and support and everything. Um, one of the things you mentioned, you know, a few conversations ago is you said um there's a social aspect to this that you support people through. Is I I mean, not to generalize, is this are you talking more along the mindset side, confidence? You know, what does that look like in in this space?

A pivotal nudge: packaging mindset

Leah 29:43

Yeah, so the so the social side of things, I think confidence and imposter syndrome are huge. I mean, unfortunately, not that I would want that to be the case, but I just understand my experience moving from R to Python was hard. And I also understand that I've been in the data science science space for a long time and I still walk into rooms where maybe I'm the only female or maybe I'm the only person like of like a certain background or maybe it's just I walk into a room and I'm just really intimidated because it's a bunch of maintainers and I'm like, you all are very smart, you know, and and I don't I wonder if I will say the right smart thing or I will say the what I perceive as not the smart thing to say. And so it's a what I'm talking about is imposter syndrome. And so the idea of Pi OpenSci making scientific open source more accessible is really core to our mission and our values. So if someone comes in and they're new, we want to welcome them. If someone comes to a sprint and they are super unsure of their GitHub skills and they're like, well I can't I can't do this, we get them to their first pull requests. Like they will make a pull request and it will get most likely merged and we start simple. And so those types of things having another human or human multiple humans who are just available to answer questions and there's no stupid question like all questions are good questions, ask them. Just creating that supportive environment can really impact someone's career. And it really impacted my career just finding people in the community that kind of helped me get started. And I wouldn't imagine that if you asked like the 20 year old Leia if like she would be where she is now, I would never expect to be in this space in this really highly technical space. So the social infrastructure especially with what's happening in the world not I don't want to get into that but I just think that having social connection in the tech space is really really important. It can really help you with your career trajectory and your confidence.

Julian 32:08

Yep. No, I I really appreciate that message because we we often talk about the same kinds of thing right where we say don't code in a silo right make sure you're coding around people share when you're getting when you're stuck on something and don't be afraid to do it because we all started there too and we get it. And we can help you shortcut the things that you're stuck on with a lesson that took us maybe five years to figure out or learn. We could help you with that in two seconds. So um just like you were talking about maintainers will come to you and say well look I've got to work on environments here. Do I use UV? Do I use uh whatever else right to what's the best thing to use well you would have gone through the fire to figure that out as a community or even just as yourself right so um and creating I think creating that environment is so important on that learning journey because we just I think and you even said it you yourself are someone so established so you know you've gotten so much done and accomplished so much and you'll still walk into a room and feel like oh man everyone here is is you you in intrinsically just go everyone here is smarter than me what am I doing here? Right? I do the same thing. And and so um but the second someone creates that space and that's why I I always say that at PyCon I love that they have that C shaped rule. Do you remember that? It's the Pac-Man yep Pac-Man that's it yeah so yep so if you have a say everyone listening if you have a circle naturally when you're talking in a group you'll create a circle right but if you leave a chunk out like picture Pac-Man um if you leave a wedge out of that that creates space for someone to come and stand and join that circle and join in the conversation. So creating space for people to participate to contribute to learn to be vulnerable to be comfortable being vulnerable is so important on that learning journey and I think that's what makes the difference between a really solid supportive community and just a kind of I don't know dumping ground of knowledge you know and um so yeah uh Pi OpenSci sounds incredible like that. I'm I'm so excited to hear all these things. Um so the next thing I wanted to touch on and geez this sounds so formal now um next thing I want to touch on uh before we jump in because you you're the package owner of you you maintain two packages and we'll get to that in a second. But as you created Pi OpenSci yourself I mean you just did this right this is something you saw a gap as you said and you said I'm going to do something about this you don't you didn't have to do that and most people wouldn't do that right so getting to the mindset which is my jam and everyone technical listening you're gonna have to listen to this what what drove you to do that because you could have easily and maybe even much more easily just said ah it's that's just how it is so what drove you to actually do this and now grow this giant community and have such an impact on the world I mean one pivotal moment maybe or one thought that made you go I'm gonna do it like was there anything like that?

Leah 35:43

I have to think about like whether there was like a pivotal moment but I I'd have to say that just years of experience here's a pivotal moment. When I was in the R ecosystem a colleague from a another community called the Carpentries which they do a lot of data science training um open science training and someone in that community I was working on a workshop for students and we were trying to help them process really complex data. It was remote sensing data hyperspectral very complex and hard to process and I wanted to make it easier and I'd written all these scripts and I was like well this is how you do it. And he looked at me and he said well you should turn that into a package and I was like well I'm not a software developer. How do I do that? I mean I can teach people but I don't know about software. That's not my identity. He said oh you can do it and he sat down with me and showed me some tools and and like the next day I had a package that you could install. I mean it was much easier than I thought. And then I was like wow I just did that and then I ran a workshop at NEON and everyone used my package and it made processing the data a lot easier and there was like 40 or 50 people and like everyone could use the same workflows to just open the data and get that processing started. And I think I always think about that moment as like a step into open source for me, but also this understanding of how impactful knowing or like having community colleagues can be in terms of helping you do something that maybe doesn't feel possible or maybe feels just a little bit out of reach. And so I think with Python when I switched from R to Python I just saw this huge gap where a lot of scientists were struggling with similar problems. And I remembered that impact that like this one person in this community had on me and I thought well this doesn't seem to exist in Python what would happen if we just created it. And so it started as just a proof of concept where I brought a few people together and then every year it kind of grew and grew. And you know what was really cool is this summer I went to the SciPy meeting and PyCon US but but SciPy really struck me the Scientific Python meeting in Tacoma, Washington we've had we've been running sprints for years beginner friendly sprints and we've been running workshops for years and we had a community session and we filled this huge room. I mean I couldn't believe how many people came to the room and we the the session was about what are your pain points in scientific python? Like what are the things that we should work on together and I have pictures from that and just watching people talk and they were excited and they we collected a lot of data in terms of like what should we work on next. And then coming from that meeting we held a sprint at the end of the meeting and we took over an entire room we had I mean the first sprints that we held were like maybe one or two people showed up and then this year it was like we literally took over a whole room we were moving tables. I had people come to the sprint that just wanted to help other people and so I'm telling you the story because it wasn't that that moment of understanding how another human can help change your career trajectory impacted me. And I just love being able to give back to other people more than I love doing science. I love science but I love helping people do their science without all of these technical pain points or filing some of those down more. It just it just inspires me as a person.

Parting advice and where to find Leah

Julian 39:41

Oh that is so cool. That's the perfect way to sum up all of that because and and I think you know it's people that attract people right and so having someone like you who's clearly just so passionate about lifting people up and I everyone listening is used to me saying that because that's one of our core values at Pipites right we we lift people up and I I just hearing that in what you're saying is just it means that you come to Pi OpenSi you're you're going to get that support. You're going to find people who at least point you in the right direction and not make you feel like an idiot for asking a question and stuff. So I think that's incredible. And isn't it just so it it really promotes that concept that you never know which interaction you have that's going to lead to something big even if it's five years down the track right um and so just out of curiosity this person from oh sorry what did you say it was called Carpentries or something?

Leah 40:44

The Carpentries yeah the carpentries okay that person who said to you you should turn that into a package are you still in contact with them yeah I mean I I haven't talked to him for for years and I I don't know if he knows like that the scope of the impact he had in terms of my stepping into open source.

Julian 41:03

Yeah but I definitely still like see him at meetings and you know yeah you should totally tell him that because I I sit there and I'm like because you sometimes a flippant comment you might make just being kind to someone like hey you know yeah you actually like if someone presents on stage and you come up to them after say mate that was a fantastic presentation like thank you for that I needed to hear that and then that's all you say you never see them again that might be the catalyst that gets them to go you know what I'm gonna keep doing this and I'm gonna deliver 20 more presentations and that's what happened to you you should turn this into a package yeah look at what you built it's awesome. Hey everyone a quick break from the episode to introduce you to our brand new coaching program the PieBytes Developer Cohorts now these are cohort programs typical of a bootcamp style interface of working together with a group of other people except it's got that unique pie bytes twist on it where you are going to be building all day every day there is very little material that you will be consuming so you won't be stuck in that tutorial paralysis. The point here is that you will be building from day one and alongside other people also building the same app in their own repositories you can all talk you can all share you can all grow together and of course you'll have a PieBytes coach supporting you the whole way so if you are interested just check it out click the link below it is pybytescoaching.com and we will see you in the next cohort.

Leah 42:35

All right so we're we're kind of we're getting to the end of this we're getting to time um we're gonna have links for how everyone can find you join the Slack community support uh get involved whatever it is um so that's really cool more importantly what book are you reading at the moment oh my gosh yeah did you prepare a book i i i didn't but I can tell you um I don't know the formal title but it's a book on the development of the open AI the company chat GPT um it's all about Sam Altman and it is fascinating it's scary and fascinating at the same time um you know I have to say we haven't talked about AI in this chat but it's a really popular topic in our community because there's just so many challenging ethical and I I heard even you talking on your I think your recent podcast about just like the learning challenges that AI presents and you know I'm just fascinated and terrified by what could happen to our society and our spaces as LLMs become more um predominant. And so I'm reading this book because I also love to understand how humans work and how their brains work and you know what were their paths to where they are now and what motivates them. And so it's a it's a really good book. Maybe it's Empire of oh I'm sorry I can't remember the title I could look it up but it's a great book.

Closing and community invite

Julian 44:11

We'll we'll ask an LLM we'll ask Chat Chapter with the books. Yeah let's ask that's Claude no no that's cool I I look that's that's another episode I could definitely talk about and yeah last episode I I think the only point I'll make now to uh reciprocate what you're saying is just everywhere I go everyone I talk to has an opinion or thoughts on it and if you really think about it that doesn't happen very often in human history you know growing up I could talk about computers about anything I was interested in and people would gloss over and I don't know whatever yeah that's cool man yeah good on you but then you talk about you bring up AI and everyone has an opinion everyone has an experience with it which is cool and scary and yeah so that's that's something to talk we'll we'll have to do that another time I'd love to hear about it from your side of the fence in in the science scene. You know I hear about it from tech like coding or but also um IT in general you know talking networks and things like that so I'm I'm used to that conversation but I've never had that conversation from a scientific perspective where it's like well hang on if we're basing our science on what an LLM puts out and that's a very simplistic comment but if we do that is is that science I don't know you know so or is that valid is that a valid finding yeah and I'm sure there's opinions and stuff.

Leah 45:36

So anyway that's if you want to talk about that go join the Pi OpenSide Slack and have a chat nice plug we're actually we're building some policies and content around just especially for peer review it's really tricky when people can now create modules of code really quickly and has it been reviewed by a human and anyway there's like a whole discussion and bucket of topics we could talk about there but that has been very high on the like list of things we're working on.

Julian 46:06

Oh that's cool. That's cool. Yeah I'm looking forward to seeing it I will have to jump into the community I'll have no idea what people are saying but it'd just be super cool to see I've I've recently reinstalled Slack because of open teams um so I think everyone listening knows that we we partner with open teams on a few things. So I've reinstalled the devil on my computer and um we so we used to have a Slack community but we moved to a tool called Circle um because we just outgrew Slack and we had all these dead channels and stuff and anyway so um it just yeah to to go premium and Slack was going to cost us like my entire house worth of value per year. I was like oh my gosh that's not so um anyway so with with all that said and done Leia what what a pleasure to chat with you today and just have you here and sharing this this is a side of Python a a side of python sorry that was terrible let's don't don't edit that out all right you're keeping that in um this side of python that I don't get to see or hear about very often so I really appreciate you sharing all this the last thing I'll just say is the or question I have for you is there are so many people listening who have thoughts ideas see challenges like you have um over the years who want to get into this stuff.

Leah 47:30

What's what's maybe some parting wisdom to be to for a cliche that you might give to anyone listening to this yeah and I didn't prepare you for this before yeah no it's a great it's a great question I'm taking I'm taking a moment to think because I have a few different ideas. I mean words of wisdom for someone you know I I think a couple of things um stand out the first is you know just do something you're passionate about. I think for me the Pi OpenSide community it just we created it with a certain value system in place that I really care deeply about. And when you have that passion you kind of you don't kind of you attract others that have similar interests and passion that want to get involved in something like that. And also it just makes it easier when the when it gets hard because things do get hard when you're running an organization. And so passion's really important. I think the other thing in terms of words of wisdom would be don't give up. And so if I had started Pi OpenSide, you know I started it in 2018 and it was just an idea we didn't have any funding. It was kind of a side effort and I think I just kept trying and trying and trying to get funding or trying to kind of build out what does peer review look like and going to meetings and you know I never stopped maybe I got frustrated sometimes but you know follow your dreams and don't give up and my dream was just if I could make some small mark on the academic space and thinking about traditional academia values a little bit differently that would make me happy. And so that's that's what we're doing is just creating that supportive space. So follow your dreams and just keep trying and hopefully that helped that's helpful um to some of you out there and and then you know just yeah I'm gonna stop there no I I I really appreciate I I didn't want to cut you off at all because that's that's just wonderful.

Julian 49:42

I mean it aligns and it's nice again hearing from the scientific side of things that's similar to the kinds of lessons we promote in general Python coding and just um seeking success right because at the end of the day you never know what tomorrow brings right you never know if if you give up today what could have been the possibility possibility if you'd kept going to tomorrow um if you show up to a community if you take the effort and take the step to show up to a community like Pi OpenSci or the Pie Bytes community what potential connection might lead to some personal growth for you or get you closer to that goal tomorrow or next week but you have to keep showing up and you have to keep trying so I really love that that message and it's just applicable everywhere. So I think that's a perfect place to call it I think we've peaked. I think if we keep talking we're just gonna go downhill from here. So it was such a pleasure meeting you oh well we'll we've chatted before this but you know having you here on the podcast and um where can people find you just um loosely where can they find you to have a chat?

Leah 50:48

Oh yeah um so I'm on GitHub my uh username will put I'm assuming will be in the podcast page but it's Al Wasser so that's a great place to find me my email's there in my GitHub profile as well and I'm probably most most active on that platform. You're also welcome to join our Slack. So we have links um on our website to that and I'm you know anyone that's interested please feel free to join our community. It's a lovely community you don't need to be intimidated and we welcome even if you just want to lurk and check it out you know come come join us and join the conversations. Those are really the best places to find me. And if you happen to go to PyCon or a scipie one of those meetings we're probably there. So you can you know look us up there too.

Julian 51:34

Oh that's cool. I love it. All right well we'll have all those links below um I'll get you to send those to me as well and so I get them right. And uh yeah that's it. So Leia thank you again for being here everyone thank you for tuning into the episode this week I hope you found this insightful I I'm definitely inspired and um yeah we'll catch up on the next episode. Thanks Leah thank you so much Julian Hey everyone thanks for tuning into the Pie Bytes podcast I really hope you enjoyed it. A quick message from me and Bob before you go to get the most out of your experience with PieBytes including learning more Python engaging with other developers learning about our guests discussing these podcast episodes and much much more please join our community at pybytes.circle.so the link is on the screen if you're watching this on YouTube and it's in the show notes for everyone else. When you join make sure you introduce yourself engage with myself and Bob and the many other developers in the community it's one of the greatest things you can do to expand your knowledge and reach and network as a Python developer. We'll see you in the next episode and we will see you in the community