Robin Beer 0:01

The mission of Flexa is to create a virtual power plant, and what that means in simple words is that consumers like you and me, who need electricity, can get the electricity from the photovoltaic and battery plants and do so very cheap, so you can actually reduce your electricity bills and, while doing that, stabilize the grid, your electricity bills and, while doing that, stabilize the grid.

Julian Sequeira 0:25

Hello and welcome to the PyBytes podcast, where we talk about Python career and mindset. We're your hosts. I'm Julian Sequeira.

Bob Beldebos 0:32

And I am Bob Beldebos. 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. Hello, welcome back everybody. This is Bob Eldeboos. We are back with the PiBytes podcast and I'm here with Robin Beer again. Robin, how are you doing?

Robin Beer 0:53

I'm doing great Thanks. How are you?

Bob Beldebos 0:55

Yeah, great, yeah Nice to have you back. I think you've been on I don't know five episodes or more. You've hosted a couple, so people are probably uh well familiar with who you are. Um, so, but just in case, if there are new listeners, maybe, uh, you can quickly introduce yourself. And uh, yeah, we're going to talk today about your uh new work at flexa and what you do there and the impact on the environment and all the good stuff and, of course, the stack and a lot of python. So, welcome everybody and let's, let's get started. So, uh, robin, do you want to do a quick intro?

Robin Beer 1:32

yeah, sure, so, um, basically, I am a physicist, studied physics uh, afterwards focused on energy system optimization, co-founded one startup, a cure where we analyze the health of battery, which is still doing great. Just had a financial round uh, financing round. And, um, yeah, now I'm with a new startup uh, flexa. We will talk quite a bit about that, as you can read here and also recently became father.

Bob Beldebos 1:55

So lots of new challenges and exciting things to talk about yeah, awesome, a lot going on in your life, a lot of good stuff and, uh, do you have a win of the week?

Robin Beer 2:05

Win of the week. Yes, we had one crucial feature that needed to be implemented and we had a really great collaboration with a team and we discussed quite a little bit about what is the best optimal solution, let's say, what is a pragmatic solution, and I think we found a really good first iteration, first solution, and then we can iterate. A really good first iteration, first solution, and then we can iterate, of course, always on the next steps. So, yeah, that was an exciting one.

Robin Beer 2:31

Nice, always a knee deep into the Python and the developer features yeah exactly, I mean on a personal note, I would say my son is now getting dangerous in the sense that he starts to crawl and turn on the, on the belly, basically. So, yeah, now we really need to make sure the house is safe I thought you're going to say he's touching a terminal in python.

Bob Beldebos 2:54

It's kind of dangerous. You're getting there. It's that's for going faster. Yeah, sure, sure, yeah, nice, nice. So tell me a bit about uh, flexa then, and uh, how long have you been there? Why did you join, what's the mission of the company and what are you working on?

Robin Beer 3:08

yeah, cool. So, um, the mission of flexa is to create a virtual power plant, and, uh, what that means in simple words is that consumers, uh like you and me, who need electricity, can get the electricity from the photovoltaic and battery plants and do so very cheap, so you can actually reduce your electricity bills and, while doing that, stabilize the grid. And the way we do that is that we have all the different households in Germany, for example, which have photovoltaic systems and batteries, and instead of them just sending the electricity to the grid, we do it optimized for market participation. So we buy the electricity and we sell the electricity. We buy it when it's cheap, we sell it when it's expensive, and these times of when it's cheap and expensive, combined with the costs that you have in the grid, lead to a more reduced energy bill and also a stabilized grid. So let me know how much of that was clear to understand for non-energy transition people.

Bob Beldebos 4:15

Yeah, no, let's unpack it a bit more. That's very interesting. So there's almost like the. It resonates a bit like with shares, like buying and selling, so you have to kind of see when, when, it's the optimal uh time and I guess that you have to take. Yeah, you work with a lot of data, right, so a lot of you will face a lot of data problems, I guess absolutely, absolutely, and actually the comparison is good because there are similar mechanisms, exactly like with shares.

Robin Beer 4:44

There is one difference, which is that we can forecast the weather right, so we, for example, know at least a little bit how the weather may be tomorrow.

Robin Beer 4:55

So then we can already optimize for that and we can say, based on the current forecast, it is probably cheap to buy at that time and expensive to buy at that time, and actually also based on the current market prices for those periods. So then we can do place bids. But we can also sell those bids again, right, or do the opposite. And that can actually lead to funny things, like you can say that, hey, I want to sell at 12 o'clock because I have a battery, I have electricity that I can. Then you notice that actually it makes more sense to sell it a little bit later. So you can buy again for that period and then sell later and because you have the battery, you can actually really transport that value through the time. So sometimes you can make money without even using the battery. Sometimes you can make money by shifting the energy from one time to another time and yeah, that's all a very exciting and complex problem to solve.

Bob Beldebos 5:50

Yeah, no, it sounds fascinating. So, and there's double win, then right, Because the customer will save money, but there's also like an optimization with batteries and all that which is then good for the environment, right?

Robin Beer 6:02

Exactly, and I think the environment aspect is the one part. But what's really important to me is that we have come to a point where photovoltaic combined with batteries is the cheapest source of electricity. So there's a nice study and maybe we can link it which shows that nuclear energy, gas and energy, oil, coal, so on they are now more expensive if you would add new capacities than if you install PV and batteries. But that's only if you look at it from the perspective that you invest money in the beginning, you pay a certain credit for that and then it supplies you with electricity. Now, to manage that this also works in a cost-optimal way, of course, you need to run the photovoltaic plants and batteries in a optimal way, and that's what we are now working on, kind of. So how to run it so that it even stabilizes the grid and makes the whole energy system even more cheap wow, yeah.

Bob Beldebos 7:00

And and the batteries themselves? I mean they. I guess they have a life cycle and a cost as well. Right to renew them, or how does that work?

Robin Beer 7:08

Yeah, exactly. So depending on the chemistry and so on, it can get a bit more complicated. But in general you would expect the battery to have a certain lifetime. Same for the PV panels, but PV panels you can calculate with 30, 40 years of duration. You only need to change some technical aspects of it, like the inverters and so on. The batteries will probably not age that long, I mean hold that long, but maybe, depending on the battery, depending on how you use it, 5, 10, 20 years. So that's something that we also keep in mind that we operate the battery in a way that the lifetime is not negatively affected or, if it is negatively affected, that you get more value out of it by what you earn from the markets.

Bob Beldebos 7:51

then, uh, what you lose because you need to replace the battery earlier yeah, so it sounds uh pretty in line with what you were doing at the cure as well. Right, because you were um working with batteries there as well. So what? What um trends have you seen since in industry?

Robin Beer 8:05

yeah, I would say that especially in germany, but also in the world in general, there has been kind of like a battery explosion. So you see lots of batteries being installed right now, and that's on the one side, because batteries have become even more cheap. So similar to pv, but not as fast, a little bit with delay, but the batteries are reducing a lot in prices. So it's now much cheaper to buy photovoltaic batteries than 10, 20 years ago. I think PV panels have reduced by a factor of 100 in cost and batteries I'm not one person sure but also significantly. So you can imagine that the cheaper it gets, the more people want to invest because there are now more and more market opportunities that are viable for batteries.

Robin Beer 8:50

On the other side, in the German market, electricity market the prices have also increased quite a bit due to the Russian-Ukrainian war and in relation to that. So you have higher electricity prices, maybe also higher spreads. So spread is when the difference between the high price and the low price uh, during a day, for example, um, and they also are increased. Of course there's also more market opportunity for batteries. So there has, there are a lot of investments now and, um, yeah, this will also lead to cheaper electricity prices than overall, because, uh, the batteries exactly can supply electricity when it's in demand. So when people are willing to pay more and overall that should reduce the electricity price.

Working With Virtual Power Plant Technology

Bob Beldebos 9:34

Cool. So let's talk a bit about the programming language stack and maybe also how it is to work there. And because you're pretty used to working in startups, so, yeah, maybe start with the stack you're using. I guess it's a lot of Python, right? So, yeah, tell me a bit what you guys use.

Robin Beer 9:53

Yeah, exactly, great question. So, of course, to build such a complex system there's a lot of things needed, and we use, for example, a cloud provider, aws, to install all the infrastructure, and it needs to be very scalable to handle tens of thousands of households. And so our work on that is that we build some components of the whole VPP. We build some components of the whole VPP and for that we use Python as a language for everything actually Infrastructure as code, as well as just the algorithms and so on. And on the other side we have, yeah, of course, the typical Python libraries Pandas and Streamlit for dashboarding, for example, but also more machine learning libraries, for example, and then infrastructure school. We use polumi then to write the infrastructure in python code, and so what we do is really, uh, mostly work in python every day. We have a little bit of typescript code as well for some dashboards or some visualizations, but that's really just um, the thin layer on top, they would say and now those um dashboards.

Bob Beldebos 11:00

Is that more internal? Or what is used for the front end, for the end customer, or is there not too much interfacing?

Robin Beer 11:06

yeah, that's exactly the point, right yeah, we have some uh infrastructure dashboards, let's say for monitoring and so on, where we have a different stack. Right, there's more. The importance is that it's real time or has all the different sources covered. We have, for example, streamlit for internal dashboards, when we want to have a quick analysis or an overview over something which is more close to Jupyter notebooks, for example, but where you want to at least have that in a dashboard form. And finally, when we create reports or have something which we present to externals. We decided to go with typescript because then we are really more free in how we can design the dashboard, whereas with streamlet, for example, you would be a little bit limited and same with other monitoring services yeah, cool.

Bob Beldebos 11:54

Tell me a bit about some of the challenges you've had, and as far as you can share, of course, but I'm really curious. Yeah, tell me some of the complexities you're facing.

Robin Beer 12:07

Yeah. So I would say, on the one side it's a lot of moving parts, right? So we have thousands of households that all need to be aggregated, because you cannot trade households in the market. You need to trade bigger entities. Then we have forecasts for each one of these households. We also have forecasts for the ensemble of households, for example, and there are a lot of parts to improve.

Robin Beer 12:31

So you can spend an arbitrary amount of time. Let's say, to optimize one single part of this whole chain. Say to optimize one single part of this whole chain. Um, but you need to identify what is the most critical thing or the one that brings the best return on investment, sense of developer time. So, um, you need to have this awareness of the whole stack.

Robin Beer 12:50

Let's say, uh, on the one side from the tech perspective and on the other side from the energy perspective, so energy markets, but also physical, technical perspective.

Robin Beer 13:01

So how does a battery operate and at which parts is it very expensive, or does the battery age faster and in which parts it ages slower, and so on.

Robin Beer 13:10

So it has a very high dimensionality of problem in the problem space and therefore also high dimensionality in the solution space, and it's not always clear what is the best way, let's say, and it's also very hard for any single human being to have the depth of understanding in all of these dimensions.

Robin Beer 13:29

So it's really great to have a great team where we bring different skills together. So some bringing more the infrastructure knowledge, for example, or software engineering in general, some bring the energy perspective with some Python on top of it, and some bring more the data science perspective right, like how to analyze data, machine learning or classic data science and just mathematic as well. So we kind of need deep understanding on all these levels. So you need people that have a broad understanding of the tech stack, like I mentioned, but then also a deep understanding of one aspect of it. And, yeah, that makes it also really challenging in the sense of communication, of course, because if you come from the different domains, you understand something different of words that may be very similar, right. So creating that common language, common understanding of things, that's really exciting, challenging, but I think, uh, also really rewarding.

Bob Beldebos 14:25

So, yeah, that's great to work on yeah, it sounds like an environment where you can learn a lot and you have, like these, deep business problems, so it's far exceeds the code and algorithms. Right, you really have to know a lot about the environment and and the batteries and the physical stuff as well. Um, yeah, julian had a had a cool question as well about the load balancing across so many households, how it impacts the average person. Is it done in such a way that people don't even notice? And how do you deal with peak periods, dinner time and seasons middle of the winter heating versus summer cooling?

Robin Beer 14:59

Do you want to speak to that? Yeah, for sure. Shout out to Julian also great question.

Bob Beldebos 15:03

He's probably asleep right now.

Robin Beer 15:07

I mean Australia is also really advanced in terms of renewables, so similar to Germany and some other countries that really already have to solve problems that you get only when you're at a certain stage in the energy transition. And how we solve it is basically that, yeah, on the one side we have a big pool, it's right, so we do forecast for the different single households. But on the other side, when you aggregate it to a pool, they level each other out. Maybe so if we do the trades on the market, we need to do it for the whole pool. Maybe so if we do the trades on the market, we need to do it for the whole pool. So it means that maybe one household in one 15 minute delivery time uses a little bit less electricity, another one uses a little bit more, and so it statistically already balances itself to some degree, maybe because maybe you take the shower 15 minutes earlier or later in the morning or have some other consumption a little bit later or earlier.

Robin Beer 16:01

But of course there's also the aspect that maybe we use the forecast that said that at 2 am or maybe rather, say, 2 pm, the sun would shine with this amount, and then over the whole region we have this different amount of energy, or it comes 50 minutes later. So so then it's not so much anymore about balancing between households, but more how do we react to that situation in general? And when we do such a reaction, then of course the question is should we take more energy from the one set of households let's say, say that have one type of batteries or do we take it from another set of households? And how do we make all these parts sure? So we have a complex optimization algorithm, I would say, that keeps different things in mind.

Robin Beer 16:50

So on the one side, what I mentioned, the battery aging. On the other side, how the batteries, how the grid costs are, or how full the batteries, batteries are, and so on and so forth, so that ideally, we can always react well in the next delivery period or the next time. And yeah, that's a very complex part. So I hope it's a complex answer to a seemingly simple question, and that's always the case in this part. So if you look at this machine, how it works, uh, in detail, it's really fascinating yeah and um.

Bob Beldebos 17:25

Are there any resources if people are interested to dive deeper um?

Robin Beer 17:30

yeah, so there's a quite some research, of course. So if you want to look at it from the um, from the scientific perspective, from the data problem perspective, on the other side, there are some companies that have decent documentation. For example, in our case, empire describes some of the parts of how the energy market works and so on. Empire is the company that has all the PV panels and batteries that we help optimize, and, yeah, and then, of course, just reach out to me, so I'm always happy to answer questions. Join the piwise community and, uh, in the circle, we can have some discussions about this yeah, it's pretty easy to uh to find you.

Bob Beldebos 18:09

Do you want to share anything else about flexa or what you're working on or what maybe is coming and the trends over the coming years? What do you see? Yeah?

Robin Beer 18:19

so what I see is, uh, on the one side, uh, there are some movements uh that push again, push back against renewables, um, so I think it's.

Robin Beer 18:28

But now technically, in the energy system optimization community and so on, it's mostly uh agreement that, uh, the prices are falling quickly and the renewables are deployed, exponentially increasing and we will also see benefits in terms of the reducing electricity prices.

Robin Beer 18:48

But it takes some time right.

Robin Beer 18:49

So there may be some pushback. But on the other side, a lot of investors have invested in batteries because it's economically interesting and, um, it will be more and more interesting for me personally to see how everyone can invest in batteries, like you and me, if you have a bit of money and you think about investing in real estate or renewable energy or so that there will be more and more opportunities that you can also profit from this transition, because why should only the big investors profit from it? I think it's really exciting to look at this development and solve some of these complex problems. If people who are listening software engineers, data scientists also are interested in solving complex problems and facing complex problems and the joy of accelerating energy transition and doing something good, then also looking forward to talk to you because we are and facing complex problems and the joy of accelerating energy transition and doing something good. Then also looking forward to talk to you because we are always in search of talents and people who have drive and want to push things forward.

Navigating Startup Challenges and Growth

Bob Beldebos 19:49

Awesome. Well, that's cool. And maybe a last question before doing the books so you joined this startup and it's a pretty young startup, right? How many years?

Robin Beer 20:10

two parent companies, let's say Enpire and Entrix, and all together. So this is one piece of the solution which is very central, let's say, where we have a lot of insight in the whole tool chain. Entrix is also really exciting because they optimize batteries for big assets, so what we say megawatt scale. Entrix is a bit older and Enpire also, the parent company, is one of the few unicorns of Europe, so startups that have a valuation of a billion in English. So basically, yeah, it's a really exciting environment and so we are both kind of a very young startup where we had the pleasure to do things from scratch and still create resources from scratch, kind of. But on the other side, we have quite some support from mature company and startup yeah cool.

Bob Beldebos 20:59

So where is flexa based?

Robin Beer 21:01

we are based in munich. So I would say it's a very beautiful city in the middle of europe and you are quick in italy, quick in the different parts of germany, and there's a lot of mountains around for skiing in the winter or for biking in the summer, hiking, whatever you want to do. There's nature around so you can enjoy. And we also have the second office kind of in Berlin with EnPyL. So EnPyL is based in Berlin, so a lot of our colleagues are frequently going back and forth between Berlin and Munich. So that could also be an option. If you're more interested in Berlin, then maybe with NPAL it could work, or otherwise, munich is a great city so we're really happy. Also with the sun, it's a good place to be.

Bob Beldebos 21:42

Nice places to work, cool. So for the audience of Python developers, if they have the aspiration to join a startup and it's just fast-paced, and aside from having the domain knowledge which is required in this case, what are some tips to get up to speed quickly in such an environment and as a developer?

Robin Beer 22:02

Yeah, just to clarify, so you don't need to have all the domain knowledge. It's also fine if you have no background in energy at all. It's just important that you have, in one part of the things that I mentioned, a deep understanding and ideally also have a broad understanding or at least some touch with the other things. And I think that also is true in general as a software engineer Like we also do in the PDM program having a little bit touched all the different parts so that you know a little bit about CI, cd testing, docker, just software development in general, but also Python development, like having in the T-shaped employee, if you call it, this bar on the top, so that you know a little bit about these things, because this helps you to connect with everything.

Robin Beer 22:47

And this helps you also that you can be independent, that you can create PRs in different repos and do things on your own, and then you just get approval or feedback and then, of course, have one thing where you're maybe really deep understanding.

Robin Beer 23:01

So either it is just pure Python right that you know Python really well, or maybe you really like cloud infrastructure or data engineering, so you really like how to create data pipelines that are efficient and scalable and so on, or you are really deep into energy and you know this domain really well, and I think that's something I would recommend in general to developers Develop yourself in the broad direction so that you can do things alone and also can connect with different people, and then focus on something that you really like in more detail. And this something that you really like, as I said, could be either technical or also just a domain like energy, and maybe you're not the greatest developer, but you have a deep understanding of energy and a decent understanding of the basics of the other things. Then you can also become an entrepreneur or build your own product or so, and hire the people that are the experts in the other fields.

Bob Beldebos 23:54

Yeah, I think that's great advice Go deep, but definitely also stay wide, because it's not only the Python right you have to deploy, app know, docker, cicd and all these things we do in PDM we have in our certification checklist. But then it's also good to go deep on something and you might not know right till you land such a position, but, um, yeah, in order to to get up to speed, you need to have that wide orientation. So I think that's great, yeah, cool, um, yeah, I think. Lastly, uh, we always do the books, of course. So what are you? What are you reading and or learning?

Robin Beer 24:31

Yeah, good point. So at the one I don't know I have some time when my son is napping, then I also read a book, maybe because he's sleeping on my arm or so that's really a nice moment. So I started to read a little bit more again. And on the one side, tribe of Mentors, because oftentimes it's a short nap, right. So it's nice to read that book where you see how different people achieve what they achieved, and it's really inspiring Short biographies, you could say. And on the other side, the Python architecture patterns, a classic from the Python books, let's say, which describes some design patterns and so on, which are really helpful. That also, um, I have come across now when, whenever you build a more complex uh software, that uh has different, um, yeah, depths, let's say that you abstract different layers, and that's really helpful in this context as well the um ari percival right um design pattern yes, I need to check again.

Robin Beer 25:29

I'm bad with names, but we're really a riley one right with a snake, exactly.

Bob Beldebos 25:31

Yes, I need to check again. I'm bad with names. A Riley one right With a snake on it Exactly. And Tribe of Mentors by Tim Ferriss right.

Robin Beer 25:38

Yes, exactly.

Bob Beldebos 25:39

Yeah, I like that one Because he has his podcast and these are like short summaries or short bios. I should say right, so they're quick to digest and get all the lessons. Yeah, perfect to read one or two short biographies during a 15 minute nap of the sun before he wants to play with you again yeah, like the daily stoic, like you have this, this daily entry, and you can read in a one or two minutes and you have a valuable nugget.

Robin Beer 26:03

Yeah, yeah, yeah, exactly. And you also asked in terms of learning, um, yeah, I mean, there's so much right. We have great colleagues, uh, which have really deep knowledge in different directions. So every day I learn a lot about this day's cloud infrastructure, but also data science a little bit, then the energy field, of course, also going deeper, um, yeah, so I think it's very broad yeah, awesome.

Bob Beldebos 26:27

Well, a lot of good stuff, and we'll link uh any resources and research if people want to go deeper. Um, this was good for you know a general overview. Um, so, yeah, happy to to have caught up and thanks for sharing any any parting words or uh things.

Robin Beer 26:44

I didn't ask you want to share now it's your yeah, I would say, uh, I think it's great here to be in an environment where people are facing complex challenges, right, and complexity itself, and I think it does sometimes have to simplify to some degree, but I think, in general, it would be good if people are courageous to face complexity instead of running away from it, and it's possible to solve complex problems, like I mean, spacex showed it with the rockets here. It's also a very complex problem to solve and, yeah, as a society, I think in general, it would be good if we are more courageous towards complexity and debates, discussions that are productive and constructive. So, yeah, it makes me hopeful for the future to be in a place where this is done yeah, which brings us full circle to the mindset.

Bob Beldebos 27:38

I mean, on that note, like, have you been like completely stuck with something and like really feeling that uncomfort, and and if so, how do you deal with that?

Robin Beer 27:48

yeah, that was the question. That was the missing question I have the missing question for mindset and shout out to julie yeah, yeah, I tend to forget I mean probably almost every day, but not every day.

Robin Beer 28:02

So because we build something complex, it's also something that hasn't been done much on that scale before. I mean there were one or two companies maybe who tried, but also not in this depth that we do it. So whenever you do something that hasn't been done before, of course you have to figure out ways for problems that haven't been solved before, and that means that you cannot go to Stack Overflow or ask ChatterPT prompt ChatterPT on the solution, how it is usually done. So you can hallucinate yourself or maybe with the help of prompts with LLMs, things that could work. You try them out and then, because it's also complex in the different ways of infrastructure and so on, it can be that you get into really edge case of how you could use it, the tool and so on, and then documentation is not always great or sometimes you just don't read it so you get stuck.

Robin Beer 28:54

But yeah, it really helps for me to make a break. For example, the other day also, we were bouldering with a colleague and we said like okay, this is now a route that is too tough. I just don't get it, my arms are getting too sore, and so on. In the same way it can go with software development and sometimes it just helps to go away from the problem, maybe sleep, do some other things, and then the next day you tackle it again and it works. So, for example, today he wrote me like the route he tried on the other day when we went together. Today he just he just made it just worked.

Robin Beer 29:23

And I think that's also something where you can trust your brain that it will make connections that you don't see yet and and that helps. And the other thing is rubber ducking basically. So just explaining your problem to a rubber duck or a colleague may lead you to think about it in a different way, that you see a solution. That has happened a couple of times just alone in this week, where me, I called a colleague or a colleague called me, explained the problem and then said okay, I know the solution already. So if you're a developer and don't have a rubber duck yet, invest in the rubber ducks, maybe the best return and invest that you can get a rubber snake, yeah we should have a pie wise rubber snake.

Robin Beer 30:01

Uh, that would be amazing, we should add it to the merch shop.

Bob Beldebos 30:07

Um, that's not a bad idea actually. Um, yeah, it's. It's. It's kind of like teaching, right, like, uh, when you rub, rubber, ducking it, you have to explain it. And I read somewhere again today, like, until you can teach it to somebody, um, you, until you're fluent in that teaching of the concept, um, you won't be till then you won't have understood it fully, right and uh. So I guess that similar process happens when you're doing Robert Doug debugging and it, uh, it becomes clear. So, yeah, that's great, and stepping away, that's, that's so important and it's also very hard to do because we get so tenacious and you keep on, you keep on going and uh, but yeah, that's when you actually have to step back. Do you guys also pair program?

Robin Beer 30:55

yes, exactly, yeah, so, uh, that also helped quite a bit. It's, uh for us, I think, fluid. So sometimes we do it more, sometimes we do it less, again, because everyone is on their path, let's say, solving their part of the problem, um, but it's good to know that there's always the option to do it and colleagues that are also motivated to do it and have experience. So it helps you and I think, while it is important to step away at some point, or let's say, maybe just temporarily optimal, sometimes it really also just helps to bang your head against that wall long enough and just get that problem solved. But it's always like you should always. If you have tried it already one day and banged your head against it, then maybe the next day you can try some different strategies and one of them will work yeah, awesome, cool.

Bob Beldebos 31:41

Well, thanks for hopping on and and sharing really cool stuff you're doing. And, yeah, this is awesome and we'll link all the resources below and, of course, people. If you want to learn more, reach out to Robin. He's easy to find Just join our Circle community and hit him up. It's Robin Beer. All right, cool. Well, thanks for joining and have a great day.

Robin Beer 32:08

See you next time. Bye.

Julian Sequeira 32:12

Tuning into the PyBytes 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 PyBytes 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 pybytescircleso. 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.