Rune holds a PhD in Computer Science and works as a freelance Python consultant specialising in big data and back-end development. When the pandemic hit, he kickstarted the learning platform Learn Python With Rune to teach others how to learn Python and apply it. He tells us about his career story & how to learn Python, how one should go about mastering this powerful programming language.
You might also enjoy this interview on how to code well.
Back in the days when I started university, I actually didn’t think of doing a PhD in the first place. I was just starting but I thought learning is awesome, so I immediately decided I wanted to get a PhD.
But while I was studying for my PhD, I realised it wasn’t really for me because it wasn’t really deeply about science. It’s more about publishing papers and getting funding to continue your career.
So after I finished my PhD, I started as a developer mainly in the security area (I’ve been working a lot in the security business.) I realised that the one thing that I liked was getting things done, getting projects done. So, I slowly became also a manager type person and worked a few years as a manager. Then I continued working in a SaaS company as an engineering manager for architecture and back-end teams and stuff like that.
I realised I missed programming a lot, and that’s actually where my journey with Learn Python With Rune started.
I wanted to learn programming again. As a manager, you slowly lose touch with programming because you’re not really doing any professional code anymore. And I kind of missed that.
So, a bit more than a year ago, I got the idea. It was actually when the coronavirus pandemic started. I had more time and was working from home, and I was like “I want to program again.” So, I started this small project. I started producing small projects, publishing them on a web page, and one thing led to another. And it just escalated.
Now, I work as a freelance consultant and they hire me and I do programming again in a freelance manner. And the reason I like that is because you kind of get more freedom. So, if you want to have some vacation, you just do it. It’s more freedom.
I had to start somewhere, right? I hadn’t been programming that much in Python professionally, but I’ had been programming in C a lot. C is a really low-level programming language and it’s very effective, but you can make so many errors, pointers and stuff like that. It’s just a pain when you don’t know much because you can just do what a processor can do.
But Python is abstracted away. And what happened with Python over the last maybe 10 years is that it has so many libraries. So you can do everything efficiently. It has been developed a lot, for instance, in data science and big data and stuff like that (I myself work with Python in the big data and back-end side of things.) And you can do all this processing now because you have the libraries that can do all the heavy work, but you just manage it in Python code so it can get beautiful.
It’s easy to understand, It’s readable. It’s almost super code. That’s the main reason I love Python. But there are also some things that I’m not so fond of.
It does hide some of the things away, some of the objects and how they are represented. When you are programming in C you know everything exactly on a byte level. In Python, it’s kind of hidden away.
And I see a lot of beginners having a hard time and struggling with what an object is and what object-oriented programming is, for instance. Because we say that, in Python, everything is an object, but really, is it?. I don’t know. It depends on the implementation. And then they confuse object-oriented programming on top of that.
So, I think it does a really good job, but there are some areas that are not easy to understand in Python. But the pain you get from that is way less than the efficiency and productivity you can get from writing code in Python.
Nowadays it’s difficult to start actually, in some sense, because there’s so much information out there. So my first advice is to ask yourself: what is it that you want to achieve with Python? What is it that you want to learn? What is it you want to code?
If you just start thinking “I want to program in Python,” then you start a little bit here, a little bit there. All the information is available. The problem is that it’s unstructured. So you get excited about this little bit here, and then you do that, but they are different types of using Python.
If you want to program back-end like I’m doing, then that is one kind of doing. If you just want to do data science, that’s a different way. You don’t really need to master programming that well, you just need to use some libraries and understand a little about math and so on.
So it really depends on what you want to achieve. I think people often go around too much. So, advice number one is figure out what it is that you want with it.
Then find one teacher, one style. It’s just easier. If you take a little bit of this tutorial on the Internet, then a different tutorial, people can do things very differently and it can be difficult to have a cohesive approach.
The third issue is about managing your expectations about how fast it is to learn. When you learn a new language, you can listen to it and understand it. But when you have to express yourself, it’s different. It’s difficult. You don’t know how to say things, but you understand it. And it’s the same with programming.
Suddenly, when you see the solution, how people solved it, you go “yeah, I understand it all and that makes total sense.” But when you have to write it, you might have no idea how to solve problems. And that’s kind of the same problem you have right when you start. You understand Python, but you cannot express yourself in it.
So, I think that would be my three main pieces of advice for beginners.
One: figure out what you want to do. Two: find one tutor or one style of programming, one book. Three: manage your expectations. It takes a bit more time to learn to write Python than to read it.
There are actually some aspects I think people overlook.
One of them is that, when you have a junior in a work environment, you need to help them. If you take somebody straight out of college, for instance, there are a lot of things they don’t teach in college. You know, how to do metrics, monitoring, how to ensure everything is healthy in your system. They don’t teach them that, so that’s one thing they’re lacking. It’s the experience.
Another thing that juniors tend to do is focus on building small systems. Most college-educated and self-taught people tend to do small projects because they’re easier and you have greater chances of success.
But there is an enormous difference between having one tiny system with one tiny server and a distributed system with tens and sometimes hundreds of systems that need to interact with each other and you need to figure out what to do.
What happens when you make changes to this small thing here? How do you rebuild it when it breaks? How do you build systems that scales in features and amount of users and volume of data?
Juniors usually can solve small-scale problems, whereas a senior developer can handle bigger scale problems.
Another aspect I noticed over the years is that juniors are often a bit afraid. When starting in a team, when starting to develop, a junior will not be so quick to contribute to it and will want people to check the code more often and to help them more, because they are a bit afraid.
So, when things go wrong, they don’t really have the confidence to just do stuff. and break stuff and put it back up again. They like that kind of experience and confidence.
My advice for new people is to build something bigger. Build something with somebody else.
You might have done tiny projects in college, or you may have worked together with other people for a bit. But try to make something bigger because you need to be able to build interfaces that interact with each other., where somebody builds one piece and somebody else builds another piece. That will teach you the kind of architecture design principles behind all of it.
I still think that’s a less important part today because there’s a tendency to go to all these microservices or services that are small in framework. And that makes them easier to understand, easier to debug, easier to maintain by other people.
So it’s not as difficult as back in the day when you had this one big monolith that was running everything. Right now, you have small services that are easier to understand, but it also moves the problem somewhere else. How do you find where the problem is when the system goes down? You need to have really really good monitoring to find things nowadays.
So you actually move some of the complexity over to the infrastructure guys or the SREs (Site Reliability Engineers). That’s why they are paid a higher rate now than they used to be. A good SRE is so valuable when you need to find problems in big systems.
He’s working on a new course portfolio focusing on how to use Python for financial analysis, so stay tuned!
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