Python Weekly #8 - I know Python - now what ?

I know Python - so now what ?

In this article I wanted to write a few words about a question that I have seen regularly on a number of different support forums. The question is generally of the form given in the title : New programmers have adsorbed the syntax and control structures of Python, and now want to know what to do with it.

Have you really learned Python ?

The first thing that springs to mind is whether the person asking the question has really learned the language at all. The syntax of Python is relatively simple, and the basic data types (str, list, int, bool etc) are relatively easy to learn and intuitive, but Python is so much more than that - for instance - do you know what this does before trying it :

>>> import antigravity 

This is just one (albeit just a bit of fun) of over 100 different importable modules that come delivered with python (The Standard Library) that allows you to do wonderful things with it. Beyond that there is the world of pyPi (python Package index) - a world of over 70,000 modules and packages developed across the world and freely available for you to use in  a few easy steps.

These package provide functionality that far extends the basic syntax, and it is all reusable for free.

Now I am not suggest you should know everyone of the 70,000+ modules on pyPi or all the details even of the 100+ modules that form the Standard Library, but you should be aware that they exist, how to find them, how to read the documentation, and at least have a working knowledge of some of the main ones (See my previous article Batteries included - 5 Standard Library Packages everyone should know). In the case of the pyPi contributions you should also know how to install these to your local environment (Hint : you will need to use pip).

Practice, Practice, Practice

The best way to learn anything and get proficient at it is to continue to practice. There are a number of ways to hone your skills in Python and these include :

• Project Euler : "a series of challenging mathematical/computer programming problems that will require more than just mathematical insights to solve. Although mathematics will help you arrive at elegant and efficient methods, the use of a computer and programming skills will be required to solve most problems". A heavy mathematical bent, but well worth trying some to hone your skills, especially when it comes to writing efficient and performant code. There are 526 Project Euler problems created at the time of writing.
• The Python Challenge : Billed as "The first programming riddle on the internet", this is a chain of problems which are solved by deciphering a set of clues, and then writing a short scripts to calculate/derive the answer - which is then the form of the URL for the next riddle". For the most part they rely on the standard library. There are 33 steps to the riddle currently.
• Python programming challenges : A small set of 7 programming challenges set to support the UK GCSE Computer Programming qualification (GCSE is aimed at students aged around 16).
• CodingBat Python problems : "CodingBat is a free site of live coding problems to build coding skill in Python created by  who is computer science lecturer at Stanford. The coding problems give immediate feedback, so it's an opportunity to practice and solidify understanding of the concepts.

These (and similar sites) allow you to practice without the difficulty of trying to come up with your own ideas - and if you had your own "Big Idea" then you wouldn't be reading this article.

What are you interested in ?

If you really want to get moving on your own big idea, then my advice is to look around you - is there something in your life, that you do that would benefit from a computer program to help you do it. This could be something from your work environment or your home life (Caution if you are going to tackle a work based problem - check that you wont be in breach of any work based security rules before you start. I would hate for you to loose your job because you followed my advice, identified a work problem and  installed Python on your work PC/laptop without permission).

The reason behind this advice is simple: If you need something, (or even think you need something) it is far more likely that you will work on it until it is complete (or at least good enough). If you start on something that you don't need, or you are not enthused about, you will be far less likely to complete it.

I will give you an example based on my first application developed in 2008.  I am an amateur photographer, and I use flickr to store the majority of my pictures. At the time the flickr uploader on the website was clunky, slow, unreliable and required a lot of work post upload to add tags, titles, to the pictures, as well needing to add pictures to folders etc. It was not suprising then that my first project was to write my own PC based uploader, that allowed me to take groups of pictures - add them into folders, add tags, titles, descriptions,  change permissions etc. and then to upload them to flickr at a single click.  This application required me to work with a number of different libraries and packages to complete the functionality including :

• pyGTK  - Python bindings for the Gnome Toolkit - A fulll featured GUI framework
• PIL - Python Image Library - an image manipulation toolset
• flickrapi - A Python interface onto the http based Flickr API.

I completed this - and used it "in anger" for several years (fixing bugs and adding more features) as I went along  until in around 2012 the web site based uploader was re-developed and is now far better than it was. My pyFlickr application although complete is now never used.

I have to admit that my development directory is littered with programming projects which I have started but never completed - mainly because at the end of the day I didn't need it.

Get Involved

If you haven't got a project that you need to write, but you still want to keep your Python skills fresh, then look around for a project that others have started but that you can work on (by it's very nature much of the work published on pyPi and other places is Open Source, and many projects are looking for collaborators, either to fix bugs or assist in developing new features). Find a project that interests you and contact the authors.

Many of the bigger projects will require some proof of experience and knowledge of python - a project you have completed yourself - or contributions to other projects. Nearly all projects will require you to have a good working knowledge of one of the python testing frameworks and knowledge of how to use the chosen method of change control, and I would suggest that you should be proficient in being able to profile your code in terms of performance and memory usage, and in being able to measure metrics like code coverage etc.