Sean Tibor:
All right. Hello, and welcome to Teaching Python. This is a special Python edition. My name is Sean Tiber.

Kelly Schuster-Paredes:
I'm a coder who teaches and my name is Kelly Schuster Perez. And I'm a teacher who coaches.

Sean Tibor:
I'm I'm a coder who's tired. It's been a week.

Kelly Schuster-Paredes:
So tired. Monday is not going to be easy. Yeah.

Sean Tibor:
Well, we're dialing in from Sunday morning at Python. We have been here since Wednesday afternoon, Wednesday evening. In your case, Kelly and I have to say, I think we made a very full weekend out of Python completely every day.

Kelly Schuster-Paredes:
We were like, we should record. We should record. But there was never any time to record. And we missed out on recording a lot of great conversations with people. But it was worth it.

Sean Tibor:
Yeah. It's all the reason to be here live and in person next year. Right?

Kelly Schuster-Paredes:
Exactly.

Sean Tibor:
So I guess to start at the beginning, we both came in on Wednesday. I got here a little bit before you did. And I got to have a fantastic dinner with some new friends and some old friends. And it was very vegan. It was good, but it was something new and different. And that's kind of the theme of Python is checking out new and different things.

Kelly Schuster-Paredes:
Absolutely. And I was envious of that. I haven't really had a Sean restaurant. I did not Sean the rest of the trip at all either.

Sean Tibor:
Yeah, that was pretty clearly established.

Kelly Schuster-Paredes:
Steaks and hot dogs. And let's talk about food first before we get into the most important thing. I mean, cauliflower, Brussels sprouts, sweet potato, Nokey and Bruges, Belgian fruits and hot dogs. That was pretty awesome.

Sean Tibor:
There's so many good things. I mean, the coffee we found good coffee shop. So for next year, we have a good lay of the land. Three Pines coffee is great. They have a sign up that says no, we don't have WiFi or decaf. They're very serious about their coffee this morning with a couple of coffee, which is also delicious.

Kelly Schuster-Paredes:
That was really good. I had Chia pudding with blueberry. Compost. Talk about a healthy end to the weekend.

Sean Tibor:
Nice. And never let it be said that we teaching Python. Don't put the important things first in our podcast.

Kelly Schuster-Paredes:
Definitely. For next year, people have to book in advance. Whitehorse.

Sean Tibor:
Yeah. Whitehorse was really good. The bartenders were a lot of fun, very chatty and entertaining and great food selection. So even if you don't want to try any of their drinks, their foods were amazing.

Kelly Schuster-Paredes:
Amazing. Absolutely. So on with the fun.

Sean Tibor:
Yeah, I know. So if you're not familiar with it, maybe you haven't heard of it. But Python US is kind of the biggest Python conference around the world. There are many regional ones that happen around the US. Around the world. We've met people from all over that come in for Python. US this year is a little bit smaller, I would say, than previous years. This is the first in person one since 2019. And now 2019 was our first Python. So this one's about maybe half the size of what it was in 2019. But I think under the circumstances of emerging from Covet and the Pandemic, that this is a pretty good turnout. And I have to say, the people that are here are incredibly into it and excited about it, and everybody is here to get along and learn new things.

Kelly Schuster-Paredes:
Absolutely. And if the newbies that were there this year, I think it was easier transition into Python. I think more people were able to talk to each other. It was less overwhelming. And I felt completely safe. And we had masks and everything was well spaced out. And I just think that they did a great job of getting this all back together under a one roof.

Sean Tibor:
Yeah. And I know that it was also a hybrid event. And sometimes you don't see those, Sean, when you're here at the conference. But there were, I think, over 800 virtual attendees this year also. So a lot of the talks were live streamed to the virtual registrants. And I know that a lot of those sessions will be posted to YouTube later on.

Kelly Schuster-Paredes:
I'm hoping so, because there were so many that we missed when we were speaking and when we were in other places. So I can't wait to watch this.

Sean Tibor:
Yeah, it was really cool. So I guess we'll start with day one, which was the education summit for us that Thursday. This week was a day long education summit with educators of all kinds from around the country and around the world. And we ended up running it kind of at the last minute, they asked if Kelly and I and Daniel Chen Doctor Daniel Chenna Chen fun to say now if we would step in and take over the hosting of the event, because the Elizabeth Wix could unfortunately not make it. And so we took over. And I think it turned out really well. I think we had about 50 people there and a lot of phenomenal conversations, some great talks in the morning. Unfortunately, those were not recorded, but we do have the presentations from all of the speakers available on the PyCon US website. So if you go to the education summit, you can at least see the speaker notes and see who talked and maybe reach out to them to get a little bit more information.

Kelly Schuster-Paredes:
Yeah. I mean, that was a great conference for me. I think that's the highlight for me with Python getting to speak to educators from all over the world and from all levels of education, just to see a lot of people like you who came in from the industry and now want to start supporting and make a change to curriculum and have more people coding Python people in the data science. A lot of conversations were happening about how do we get data science and Python into the educational system met a lot of people about talking about that, which was really cool, and just being with I know this is kind of bad, but being with your kind, being with the people that get it when you're grading and you're struggling and your failures and your happy moments. So it's kind of a nice day all around. Very comfortable and cozy.

Sean Tibor:
Yeah. I think that was one of the things that we saw was the number of people that said I'm kind of on my own in my school district or in my school teaching what I'm teaching, whether it's a teacher who is moving into the technology and coding space or whether it's a technologist who's coming into the teaching space, there aren't a lot of us around. So to come together as a group for the day is really important. And I know we say this every year, and I think we need to find a way as a community to make this happen. We always talk about keeping things going throughout the year. So it's not just an annual meet up. I think we have to analyze this and do some reflecting on why have we never kept this really going throughout the year, and what can we do differently this time to make that happen? Because it is really obvious every time we get together that we need to do this more than once a year.

Kelly Schuster-Paredes:
And probably going to put a shout out to anyone who is thinking about data science. We were asked if we can make some connections for a friend of ours that we met from South America who teaches in Brazil, and she's starting to teach data science in her high school. And we have another high school person that is also going to be doing some AI and data science, and they wanted to make some connections and to see if anyone else is in their predicament where they don't really know where to go yet, and they want to communicate and collaborate and see where they're going with data science. Yeah.

Sean Tibor:
And there was some cool outreach, too. It looks like Anaconda is getting behind more data science in education. And so we met a person from that team that's coming in to try to do some outreach and make connections. So there's some really interesting good things happening, and I think it's really on us to figure out how we make that move forward 100%. Yeah. So overall, really good. Our talk was on Busting Curricular methods of teaching Python. I think it was a lot of fun.

Kelly Schuster-Paredes:
That was too much fun. I think that was one of out of the five presentations we did this week, that one, to me was just an easy one, a fun one. And I wish it was recorded because we had a lot of laughs. I was quite the comedian.

Sean Tibor:
Yeah. It's tough playing straight man to you sometimes, but, yeah, it was really good. And I think a lot of head nodding people, seeing a lot of the same things, but also for people who are teaching at different levels or in different areas, they can see some commonality, but they also saw a different approach to things that they could apply in their work. So, for example, I know Ruben Lerner talked a lot about how he was really impressed with all the things that we're doing. Ruben is teaching all over the world to adults, and he brings a lot of humor and everything into his teaching, which I think really connects with the same things we're doing. So we are going to put the links to the slide deck, at least in our notes as well. But you can see all the speaker notes on the Python US Education Summit page.

Kelly Schuster-Paredes:
That'll be really useful. I think I'm trying to remember the six of them, and I was interested in all of them. It was pretty cool, just even down to Dr. Daniel Chen data and how he actually built out his curriculum. It was really nice.

Sean Tibor:
Yeah. It was a really interesting data oriented approach to designing curriculum that I was really impressed with, even brought in some product design persona work that was very familiar for me from my marketing days. But it was pretty cool to see how he brought it all together.

Kelly Schuster-Paredes:
Well, it was quite interesting. I was reflecting on his presentation about the personas. We often do this in schools thinking about our curriculum as a whole. And a lot of schools will say if we plan our curriculum for the child that is at our school from PK to twelve, what does that child look like? Where do we want that child to be in the 12th grade year? And what Dr. Chen did and his presentation was actually said, what is that person going to be like in my class, in my course? And I think if we fine grain, that kind of talk in each level, in each grade level, in each curriculum level, in each division, I think that would be a big game changer. What does a 6th grader look like? And who is that 6th grader that I'm teaching in my course? And how can I make sure that I reach that child every day in every class?

Sean Tibor:
Yeah, it's a really interesting thing, and it works particularly well in product design. And I think this is helpful from a design perspective because it's really hard to completely personalize your curriculum and your approach and your design for an individual that you haven't met yet. But it's much easier to have a set of a few personas, different like, targets, people that have different needs and different approaches, different beliefs and behaviors to give them at least three or four different options. And they'll pick and choose from each of those personas to take what works best for them. So it's an interesting way to go from a monolithic approach where you're designing for one type of student designing for three or four students, you can actually far better address the individual needs of a lot more students without having to try to think about and get overwhelmed by dozens or hundreds of different students.

Kelly Schuster-Paredes:
Absolutely. Thinking, sorry, I'm processing, but we're going to move on because I'll process for a little bit. I'm just thinking of how I can apply that in my classroom. Like, I keep going on using that general approach and still keeping the personalization within the curriculum. Yeah.

Sean Tibor:
I've always thought of it as like casting stones into a pond. Right. You're trying to aim for that one target of the three or four that you have. But the ripple effect and the interaction between the different stones that you toss is what makes it individualized and personalized for that learner. So there's a way to do it that feels like you're not being personalized, but it actually when you're receiving it is incredibly personalized. I think we need to do a podcast episode about this.

Kelly Schuster-Paredes:
I think so. I think so. What does the 6th grade new Python student look like? What does the 8th grade persona of a student who's gone through the classes? What would that look like? What would a graduating senior look like who's had JavaScript, Python. Compsi, AI, whatever they do in post APS.

Sean Tibor:
Yeah. And it's interesting because we've always thought of our differentiation and learning as being like a gradient scale or levels of achievement or that there's like a ranking of it. Right. Like the most advanced, the least advanced. But in reality, when you do these personas, they don't have to be ordered in their level of proficiency. It could be someone who's very comfortable and experienced, even if they don't have a lot of knowledge yet, versus someone who is apprehensive or afraid and doesn't really want to learn. Right.

Kelly Schuster-Paredes:
You know, Daniel, we need to call you back. You're going to have to come in here and help us write a person I would love to do or help us write a survey. Can you imagine a mindset, a mindset perseverance skill set, cognitive skill set, mirroring within the curriculum in order to analyze our students and our future students would be really cool.

Sean Tibor:
Yeah. We should move on, though. This is supposed to be a recap.

Kelly Schuster-Paredes:
Okay.

Sean Tibor:
So Friday, Friday. Friday was our keynote day, which was super cool.

Kelly Schuster-Paredes:
Super cool.

Sean Tibor:
So we actually skipped the Friday keynote Saturday. I'm thinking, okay, so we'll forget Friday. If Friday, we skip that one because we were working on a presentation. So we had our presentation on Saturday. We spent a lot of Friday kind of roughing it out. And I described it kind of like if you walked into the mechanics garage, all the parts for the car were there, but they were all laying on the floor. Right. So it was our job on Friday to put them all back together. So we spent some time figuring out how all these pieces fit together for our talk on Saturday. And then we also spent some time going to different talks on Saturday and seeing what people were talking about.

Kelly Schuster-Paredes:
We did the boost, too. So I have to say there are some of the booths were really interesting. There was a company and I need to go back and look at all the companies. But this company was aggregating a bunch of data sets that you can pull from online. So you would not have to bring down the data from your computer and get a security key or whatever. But you work within the browsers and you can use this to test data science. You can do this to test your AI data sets, NumPy, all that stuff. And I was really interested to see and it's actually secure. And I say secure. I mean, it's student safe, so there's not going to be bad images in there. And I thought that was really interesting fact that you have this data collection that you can use and you're not worried about finding an inappropriate image that a student might use. So that was cool to me. And then again, good to speak to Pie, Charm and Anaconda, and that was really cool. And talk about more of the things that they're going to do with the data science and education outreach program.

Sean Tibor:
Yeah. I mean, there's a lot of it's interesting. There's a couple of different categories of vendors that tend to be a Python with their different booths and everything. So I'd say there's like developer tools, which is like security and supply chain. And here's things that make your job as a developer easier, smoother, faster, whatever that is. But then there was also sort of like now a data science tool chain that's coming out. So data science tools that help you either spin up compute resources so you can process through your data sets faster databases for machine learning and AI and data science. So there's this whole separate category that's really targeted at data science and data analytics. And I would put kind of Anaconda in some of those categories as well. There's a small education segment between I would say no Starch Press and real Python. And then there's also sort of like the broad base useful for everyone or enterprise type stuff like your AWS and your Microsoft. And it's really interesting to kind of walk around, just see all the different things that people are doing and offering that you may not see in your day to day work. Right. That was pretty cool. And I got some stuff for both my new day job around security and supply chain and building out platforms, as well as some stuff for teaching and education. So I was able to get a lot of different things out of the Expo Hall.

Kelly Schuster-Paredes:
Yeah. And the ones there was a couple of project management agile tools, which I thought was really interesting and coming from the educator side, where they're trying to push in some more agile learning into it, I thought that was really interesting. So some cool products, and they're offering at like $7 a student where they can plan out their software. So that was really interesting for me because most of it in the Cleveland was only for businesses and there wasn't even offering for education. They didn't really realize that. But in that past two years, three years, there's more of an understanding that education is going to happen.

Sean Tibor:
Yeah. I would say a good example of this is the Code Anywhere Booth. I don't know if you got a chance to look at them. I'm not sure it's quite ready for, say, like a teacher who's just learning about technology to set up and configure it. You might still be better off with like, a replica or something like that. But Code Anywhere looks like it could be really good at kind of that advanced high school computer science or post secondary College level, where you could create configurations for coding environments, and then the student can click on a link and it creates the environment for them automatically. So it's like a little bit more advanced version of like a Google Colab where you can create the environment for someone with all of the packages that you want and the base configuration and everything. They can do all their coding in there and have access to a computer online that could do it. I was a little bit intimidated by in terms of putting myself in the shoes of another teacher. It seems like there's a lot of configuration files that could be kind of intimidating for someone to get started with, but maybe with a really good tutorial or some support, it would be a doable thing.

Kelly Schuster-Paredes:
Yeah. So let's talk Saturday in PY script.

Sean Tibor:
Oh, yeah, that was super cool. So that was the day we actually went to the keynote because we had our talk ready to go. But we went to the keynote, and the first keynote was with Sarah Sean. I'm not entirely sure how to pronounce her name, but she's an Einstein fellow and worked on the Event Horizon telescope team, and she walked us through how we got captured the first images of a black hole at the center of the Mad Seven Galaxy, which combines two of my nerd passions around space and Python and data. And so she talked through the whole step by step process. And I really thought the best part of that talk was not just getting to the answer, but validating the answer and really proving beyond a shadow of a doubt that the data meant what we thought that it meant that we removed all the bias that we possibly could out of it. So it wasn't just here's the image go nuts. It was, how do we know that this image is real and that we haven't introduced our own human bias into it. It was really cool.

Kelly Schuster-Paredes:
I thought it was neat how they spent seven weeks apart without communication from the other teams around the world just to make sure that what they saw was really what they saw. And then after seven weeks of analyzing their own data, I don't know, I was trying to assimilate to something in the real world, but you're in a room talking about some solution, and then all of sudden a you come out outside and you throw down your cards and everyone has the same solution. It's just kind of remarkable that four teams had the same image out of all the data points that they had collected for that team area.

Sean Tibor:
And the story that she told her was really important, too, because it's easy to think of this as science and dispassionate, and we don't talk about the people behind it. Right. But she said that they worked in her team for seven weeks, and these people are all over the world collaborating remotely, putting it together, and they have no contact with anyone else, and they're having that moment of doubt like, this almost feels too easy. Did we come to the right answer too fast? And what happens if our data doesn't match the other teams? And they were applying a set of techniques. Other teams were applying a different set of techniques, and they were asked to send in one picture that they came up with. So they send in their best image of what they thought was the best representation of the data that they had and the techniques that they applied to it. And she said that when they met together in person, they put all the photos on one slide and they put it up at the same time for all the teams to see. And all the four pictures matched really, really well. I mean, obviously there were differences with the different techniques, but you could tell they were all looking at the same thing and had come to the same conclusion.

Kelly Schuster-Paredes:
That was cool.

Sean Tibor:
And then we went out for Karaoke.

Kelly Schuster-Paredes:
That was really special to me. I sent the picture of the black hole to my kids, and I was like, this was made possible by Python, and both my kids rent cool exclamation point, all capital letters. So that's kind of special. Just to let them know that here's a black hole, all the things that happen. And Python did it.

Sean Tibor:
Yeah.

Kelly Schuster-Paredes:
So PY script.

Sean Tibor:
Py script is really cool. So if you haven't seen the announcement already, this was brand new, announced at Python. Python. And it was really something that I think is going to be powerful. And we've seen attempts at this before, but I think there's something interesting about this approach. This is Python running entirely in the browser, so it doesn't have a separate download, it doesn't have anything else. It's just running Python in your browser, and it interacts with your browser. So it acts almost like JavaScript in your browser, where you can interact with the Dom and HTML. You can manipulate the HTML elements, you can move things around, you can change stuff. But it's running full Python interpreter, as I think it's called the WebAssembly as a web assembly component in your browser. So it's running real Python in the browser with all the great things that that brings along with it.

Kelly Schuster-Paredes:
Yeah, I was impressed by that. It's obviously still in free Alpha, something we can't use. But what was really impressive for me was the idea that they want to make it so that kids can use it so that we are preparing the next developers. The next I don't know what he put on there, 10,000 developers.

Sean Tibor:
Right.

Kelly Schuster-Paredes:
It was a big number, but I think that was really interesting, that there's that forward thinking for the kids and where they're going to be going because you need new developers to come out of the school.

Sean Tibor:
Yeah. And actually I was showing it with one of my students that I tutor this morning. She wanted to learn about JavaScript. And I was like, well, there's this brand new thing if you want to look at it, so we can understand how you would interact with code in the browser. And so we played around with some of the demos. We looked at it. And what's great about it is that it just adds some extra Tags. So you have like a Pi script tag that you can use in HTML to be able to get this to render information and data in your web browser, to be able to manipulate JavaScript. You have hooks into JavaScript libraries. They show demos of WebGL and visualization and all these things. So just like Python can hook into C and C and Fortran, now you can hook into JavaScript, too. So it's pretty cool to see that.

Kelly Schuster-Paredes:
Yes. So after that, Tray Hunters, that was great. And what a great reflection. Add on to a last minute add on in our slide show to add Trey Hunter's idea of asking why things happen in Python. And I think that's a huge question that every educator can put into their classroom easily. Why do you think this happens? Or why did this error happen or what's happening in the list or what's happening in the tuples? It made my head kind of spin. And I was sitting there reflecting saying a couple of years ago at Cleveland, I would not have any idea what he was talking about, but I felt very comfortable sitting in his talk and going, yeah, why does that happen? And he had a lot of questions for us. Great talk.

Sean Tibor:
Yeah, it was really good. And I think that will be one of the talks that people want to check out on YouTube when it becomes available. It's not just the specific audience that he's talking about. He really addressed nicely that idea of being curious about looking at Kelly, why does it do that? Or this is weird, this isn't what I expected. So anytime that your expectations are not quite met to ask that question, why is this happening and what's causing this to happen? And then digging a little bit deeper and digging a little bit deeper and exploring that curiosity.

Kelly Schuster-Paredes:
Which is something that we used in our talk 100% trying to think where we went after that.

Sean Tibor:
There were so many things I did see some cool talks about later on. On Saturday, I saw Anthony Shaw's talk on Python improvements. So making your code faster by avoiding some anti patterns in your Python code. And I guess the short summary of it is if you're looping over things a lot of times, hundreds of thousands or millions of times, it makes your code a lot faster if you apply some speed improvements and speed optimizations. And he had some specifics in there about the things that he saw that are pretty common. But then he also showed you how to identify and measure improvements in your own code so that you could discover the things that were slowing down your code the most with some code profilers, but then also how to address them and how to fix them. So it's pretty cool to see that because it felt like it was some computer science topics and things that people talk about a lot with compiler design, but turned into really practical real world examples where I could say, oh yeah, I've definitely done that in my code before.

Kelly Schuster-Paredes:
Yeah. And I forgot to mention I had a conversation with Anthony at dinner and really got my brain thinking and I was giving him a hard time. But to be honest, I was given a hard time because he was challenging my thoughts of what I could do in computer science. And he explained to me some of the lessons he did in his classroom that he's helping or doing one of the many things he's doing and talking about lessons with the binary and how a computer works and going through the whole process of the inputs and outputs and having that understanding prior to even coding, which if I had a longer course, I think 100%, I'd be implementing all those lessons in the beginning because they were so critical to really help the students see what's going on in a computer. And I don't think they get that a lot in much of what they do in the education system. So there's a couple of activities I was talking about the Ethernet and switches and breadboards and just the start of hardware without doing any of the coding, which was really cool.

Sean Tibor:
Yeah. It's interesting because I think there's a balance to be struck there. There's a right level of foundational knowledge and preparation work. So preparing the students to think about coding. But then there's also a bit of like we need to jump right in sometimes and make things happen and get coding, get hands on the keyboard as early as possible in the process. And I think it depends a lot on the instructor. It depends a lot on the students and where they're coming from. And finding that right starting point is sometimes rather tricky.

Kelly Schuster-Paredes:
100% I do not recommend or support the lecture of binary use and graphing out a whole bunch of binary numbers. And that, to me, is part of the reason why I didn't get into computer science, really, is that it was kind of dry and boring. The doing part was fun for me, but I do agree with the approach that Anthony was telling me in his lessons of how he was getting the kids to just think what's happening prior to coach. So I'm going to explore more options with that. Hopefully he'll share out some of his lesson ideas and his hands on talks. Not sure I can do it justice like he did, but it'll be interesting to see yeah.

Sean Tibor:
I think it's a good question to ask. Right. So we have some ideas there around how to make that work, and I'm sure that all of our listeners do, too. Again, it comes down to what suits your personal style and the work in the classroom and the persona of the child and your persona of the child. Exactly. So I think not to save the best thing for us, but I have to say I'm really excited about the way our talk turned out at Python. We've been working on it for a while. We've been thinking about it for a while. And it's kind of amazing to me that we went from writing our first lines of Python code four years ago to speaking at the Python event here in Salt Lake City four years later.

Kelly Schuster-Paredes:
It was incredible. That room was huge.

Sean Tibor:
I walked in there on, I think, Wednesday or Thursday when I first got in just to kind of get the lay of the land and see what things looked like. And I walked in that room and wow, there's a lot of chairs in here.

Kelly Schuster-Paredes:
While I was sitting on the stage watching people stroll in and seeing Gilo coming in, I didn't tell Sean because I thought he had seen him walk in, but I was just like, oh, my God.

Sean Tibor:
Our talk was learn Python like a twelve year old. And the whole goal of our talk and I hope everyone kind of expected got what they expected out of the talk. But our talk was about applying the things that make a twelve year old so effective at learning the parts of their brain physiology, the parts of their schedule, and the way they approach learning and applying that to the way that we learn as adults while still taking advantage of all of the learned advantages that we have as an adult to be able to make our learning more effective. And I think it was interesting because as we were developing this talk, the thing that kept becoming apparent to us was it was really about how the brain works and it's about how we learn things. So it's that cognitive psychology that's really important to learning and getting our brains to work in a more effective way by kind of hacking that cognitive psychology loop.

Kelly Schuster-Paredes:
Absolutely. And to be honest, the best part of the talk was talking to the people. Afterwards, a University of Chicago student came up to me and said, our talk really hit her and made an impression because as a computer science major in University of Chicago, she went into this computer science class and she had never coded before, and she felt really inadequate. She was saying that she had a lot of stress because a lot of the other students that were in the University had already coded before and she didn't know anything. And a lot of that stress tended her learning. And so we were talking about, what can she do to help remove that anxiety? And then another person came from a developer professional development company and said a lot of the things that we shared were really important for her and her design of curriculum. And one of the things that she was trying to work around was how do we get those adults who are afraid to say, I'm having issues share their issues? And one of the things I said to her was, Why don't you try the old adage of you put a post it and have a posted board of issues or failures and make that a thing that's known that I can post my posted anonymously of what's hurting or what's hard or what's stopping me or what's making me fail. And then you can have a group conversation about what's happening and why and how we can solve it. And it was just really neat that we made an impact. And a lot of educators were really excited to share what they did.

Sean Tibor:
Yeah, I was a little worried because our time slot was late in the afternoon on the second day of talks a little worried that no one would show up and people showed up. So it was really wild and exciting and fun. And I'm glad we did it. And I know that our talk will be posted to YouTube sometime in the next few weeks, and I'd love to see it myself because it's a little different when you're doing it instead of watching it. But I couldn't be happier with the way it turned out, especially at the end of a long week of presentations and travel and conversations and all the things that go into making a week like this happen. I have to say I'm glad that I did it with you. It was good to have a partner to do it.

Kelly Schuster-Paredes:
I would not have wanted to do that by myself. That was nerve wracking. Plus, all those people that get up there and do that.

Sean Tibor:
Yeah, maybe next year you can go solo. But yeah, it was a really great conference overall. I know that the organizers have worked really hard to put it on speakers have worked really hard to put it on. Everyone who just came and put themselves out there to be a part of this have worked really hard. And you can tell that there were a lot of first time ribbons, People who are coming to Python for the first time. And it's hard to do that for the first time, Especially if you're a beginner or someone who doesn't know Python that well to be able to go to a conference about Python and say, I'm still learning Or I'm new at this Or I'm a beginner because I think one of the things that a lot of people take away Is realizing that everybody's still learning and everybody's finding something new.

Kelly Schuster-Paredes:
100%.

Sean Tibor:
All right. So I think that's our recap for Python. Plenty more to come on Twitter. Lots of new people that we met. I even met the author of my favorite math with Python book, and each Shaw came up to us after the talk.

Kelly Schuster-Paredes:
Wow.

Sean Tibor:
So it was just really cool.

Kelly Schuster-Paredes:
He was out the talk. I didn't get this. Oh, wow.

Sean Tibor:
Yeah. He was so excited that we knew of his book, and I told him how much we used it. So that's the magic of Python. It's just meeting all these people that are the actual people behind the names.

Kelly Schuster-Paredes:
Oh, we can't forget Al Sweigert.

Sean Tibor:
Yeah, we did.

Kelly Schuster-Paredes:
I'm sorry. I did not forget you. That was a highlight. And seeing you at Ed summit.

Sean Tibor:
Yes, there you go. Speaking of books, but that's the coolest thing about Python is like that there are real people out there that are part of our community. Pycon is a fantastic way to meet them, and one of the things that I want to do over the next couple of years Is start attending more regional PyCon Because not everyone can come to the big PyCon us. There are phenomenal people out there doing work in the regions, and it'd be great to meet them and make more connections.

Kelly Schuster-Paredes:
Yeah, maybe pikon Africa or Python Australia.

Sean Tibor:
If we're asked to be guest speakers, I will figure out a way to go figure out. All right. So I think that does it for this week. Keep an eye on our show notes, Our Twitter feed, and our website for more updates from this week. We're going to be posting slide notes and videos and everything we can possibly think up to share with you all the stuff that's happened this week. But again, thank you for coming with me, Kelly. Thanks for presenting with me. It's been really great. And now it's off to the airport.

Kelly Schuster-Paredes:
Yeah, it was great.

Sean Tibor:
All right. So for teaching Python.

Kelly Schuster-Paredes:
This is Sean and this is Kelly signing off.