Learning programming: so I've learned the basics of Python, what next?

I strongly disagree with the approaches usually recommended online, which involve some mixture of sites like CodeAcademy and looking into open source projects and lots of other hard-to-motivate things. Maybe my brain works differently, but those never appealed to me. I can't do book learning and I can't make myself up and dedicate to something I'm not drawn to already. If you're similar, try this instead:

1. Pick a thing that you have no idea how to make.
2. Try to make it.

Now, when I say "try"... new programmers often envision just sitting down and writing, but when they try it they realize they have no idea how to do anything. Their mistake is that, actually, sitting down and knowing what to do is just not what coding is like. I always surprise people who are learning to code with this fact: when I'm writing code in any language other than my main ones (Java, mostly..), I google something approximately once every two minutes. I spend most of my time searching for how to do even the most basic things. When it's time to actually make something work, it's usually just a few minutes of coding after much more time spent learning.

You should try to make the "minimum viable product" of whatever you want to make first.

If it's a game, get a screen showing - try to do it in less than an hour. Don't get sidetracked by anything else; get the screen up. Then get a character moving with arrow keys. Don't touch anything until you have a baseline you can iterate on, because every change you make should be immediately reflected in the product. Until you can see quick results from your hard work you're not going to get sucked in.

If it's a website or a product, get the server running in less than an hour. Pick a framework and a platform and go - don't get caught on the details. Setting up websites is secretly easy (python -m SimpleHTTPServer !) but if you've never done it you won't know that. If you need one set up a database right after. Get started quickly. It's possible with almost every architecture if you just search for cheat sheets and quick-start guides and stuff. You can fix your mistakes later, or start again if something goes wrong.

If you do something tedious, automate it. I have a shell script that copies some Javascript libraries and Html/JS templates into a new Dropbox folder and starts a server running there so I can go from naming my project to having an iterable prototype with some common elements I always reuse in less than five minutes. That gets me off the ground much faster and in less than 50 lines of script.

If you like algorithms or math or whatever, sure, do Project Euler or join TopCoder - those are fun. The competition will inspire some people to be fantastic at coding, which is great. I never got sucked in for some reason, even though I'm really competitive.

If you use open source stuff, sure, take a look at that. I'm only motivated to fix things that I find lacking in tools that I use, which in practice has never lead to my contributing to open source. Rather I find myself making clones of closed software so I can add features to it..

Oh, and start using Git early on. It's pretty great. Github is neat too and it basically acts as a resume if you go into programming, which is neat. But remember - setting it up is secretly easy, even if you have no idea what you're doing. Somehow things you don't understand are off-putting until you look back and realize how simple they were.

Hmm, that's all that comes to mind for now. Hope it helps.

The LessWrong site is written in Python, is available on GitHub, comes (*) with a fully configured VM image to avoid the pain of setting up a functional system, and has some outstanding feature requests. This might be an excellent way to hone your newly acquired skills, since you have easy access to a community of users (in fact you're one yourself).

(*) Came, as of eighteen months ago - it's possible that "bit rot" will have happened meanwhile.

Check out OpenHatch if you're interested in getting into open-source development. They've put together a directory of open-source projects needing bug fixes or other contributions, organized by difficulty and language. They also run several workshops and have a helpful and friendly IRC channel (#openhatch on Freenode).

You said that people told you that you "should" become a computer programmer. But it only makes sense if you enjoy programming 8+ hours a day (and have aptitude for it). Did you have fun learning Python or was it a chore?

Probably belongs in the latest Open Thread.

Depends on what you're interested in. If you're a mathematician, Project Euler is a collection of recreational mathematical problems that need to be solved with programming (some can be solved with pen-and-paper in a reasonable amount of time, but the majority require the processing power of modern PCs) - in other words, a good way to learn to re-phrase mathematical thinking in terms of the programming language you're trying to learn.

Consider taking some of your routine computer activities (batch photo manipulation, organising files, filtering email, etc) and automating them. Python is a great language for that, it can easily interface with system shells on just about any OS and has a ton of well-supported libraries for just about everything. Yes, you'll be reinventing inferior solutions to problems that have been solved long ago, but the point is to learn.

A fun way to explore more advanced features of Python is the Python Challenge. It's a series of online riddles that you're encouraged to solve using various features of Python.

Go to Kaggle and enter a data competition. It is super, super easy to start (usually you just have to submit a solution which is a bunch of 1's and 0's) but to win, or even increase your rank, requires learning of real, practical data skills. I believe some companies even do recruiting through kaggle competitions.

If you go this route, download the scipy superpack which includes scikit-learn. You can spend five minutes reading about e.g., Naive Bayes classifiers, and then five minutes later you can be checking out how it works on your data!

Chris, if your goal is to get a job, it may help to think about what an employer wants to see when to make you an offer for a good first job.

Don't let this distract you from the joy of learning, or from learning material that is not directly relevant, but it may provide a motivator. In the end, you'll be providing value to someone, so you may as well start thinking of it now.

Why not choose an open-source project that is well-known, and which has been historically open to accepting patches. Then find some bug that you can fix. There are tools to help you find all this. Then submit a patch, and you can honestly say that you contributed to the famous project.

I've recently been looking into the Python Natural Language Toolkit, and thinking the book would make a good set of exercises for the linguistically-minded aspiring Pythonista.

1. Learn a framework for developing web applications. Specifically, learn Django.

   This is because most new applications are web applications, and because you can write a satisfying application without knowing much. Also, you get immediate feedback on your code -- you can see whether or not the app is coming out the way you want.

   Django is recommended because (a) it is written in Python, (b) it is relatively popular, and (c) it is similar to Rails, which is very, very popular and thus easy to get hired for.

2. (in parallel with 1) Decide on an application that you want to write, and write it. Put the code on Github or Gitorious or Bitbucket (as you go -- not just once you finish).

3. If you are exited about getting involved in free and open source software, it's usually best to work on a project that you actually use. That way, you at least understand some of how users expect the program to work. Unfortunately, the programs that you use are likely to be the ones used by zillions of other people, so much of the low-hanging fruit will be already plucked. But maybe you have a more obscure interest which involves software? For instance, I have added features to electronics schematic software, vector graphics software, an interactive fiction virtual machine, a search engine, and a bunch of other random stuff. If you don't see a feature you want to add or a bug you want to fix, just take a look on the bug tracker and see if anything catches your eye. Don't worry if you can't fix any given bug; if it were easy, someone would have done it already!

I'm in a similar boat; also starting with Python. Python is intuitive and flexible, which makes it easy to learn but also, in a sense easy to avoid understating how a language actually works. In addition I'm now learning Java and OCaml.

Java isn't a pretty language but it's widely used and a relatively easy transition from Python. But it, I find, makes the philosophy behind object oriented programing much more explicit; forcing the developer to create objects from scratch even to accomplish basic tasks.

OCaml is useful because of the level of discipline it imposes on the programer, e.g. not being able to mix an integer with a floating point, or even--strictly speaking--being able to convert one to another. It forces one to get it right the first time, contra Python's more anything goes, fix it in debugging approach. It also has features like lazy evaluation and function programing, not supported at all in the case of the former (as far as I know) and as a kind of add on in the case of the latter, by Python. Even if you never need or want these features experience with them goes some way to really understating what programs are fundamentally.

If you've learned the basics, the next step is to exercise the basics on small but increasing challenges; so that you can mentally decompose large challenges like GitHub projects into attackable pieces. A year ago, I would have suggested the Euler challanges, but today I'd recommend the Matasano Crypto challenge. Why? 'cause chicks dig hackers. Also, security engineering-type thinking is very compatible with lw-style rationality. It's no coincidence that Wei Dai is a top contributor both here, and in real-world cryptography circles.

Consider volunteering in an academic lab that does computational research- such as bioinformatics, or computer science research. This will get you practical programming skills, but also other useful skills and knowledge related to the specific research being done.

I'd consider interactive graphics. Nothing else has such instant feedback; it's very obvious if something is working or not and you can easily figure out what's wrong. Using Javascript and Canvas in a web browsing you can get up and running with 2D interactive graphics very quickly and you just have to hit refresh to see the changes you make (I don't know what Python offers in this area). I think it's a great way to learn various programming abstractions too. By working at a low level, you're not forced to use abstractions, but you can see why they're useful once you start writing more complicated programs and also develop an appreciation of their limitations. If you go straight into a framework, you go in at the deep end and have to learn somebody else's way of doing things without really understanding why they're doing it.

Build something you need. What you don't know, you'll learn in the process.

Learning two languages at once can help you generalize. You may as well learn JavaScript, as you'll have to do it eventually. You might try Haskell. I don't know if it's a good language to learn on, but it might be a fun experiment--a functional language this early in your programming career,but then again it might be a little too confusing.