Coding Is Like Cooking

Last night at GothPy we had a play with Django, a web application framework for Python. I’m fairly familiar with Rails, so it was interesting to see a different take on solving the same kinds of problems.

I downloaded Django for the first time when preparing for the meeting, and spent about a day going through the tutorial and trying stuff out. At the meeting were a few people who have used Django before, notably Mikko Hellsing, who has worked with it daily for several years.

It was so much easier learning the tool from people who knew it than by reading the documentation. Constant code review and real time answering of questions is just brilliant for learning.

At the meeting we decided to implement a very very simple web application, similar to the one that Johannes Brodwall performed as a Kata at XP2010 together with Ivar Nilsen. He calls it “Java EE Spike Kata” since he does it in Java with no particular web frameworks, just what comes with Java. (There is a video of him doing it on his blog, and sample solution here on github).

I thought we should be able to implement the same little application in any web framework, and it might be interesting to see differences, so I though we should try doing it in Django. It just involves two pages. One page “Add User” which lets you create a new user and save it to the database, and another page “Search User” which lets you search for users, and presents results. So the scenario is to create a user, search for them, and see they are returned.

When I work on a problem in Rails I usually start with a Cucumber scenario for the feature, and I discovered there is a python version of Cucumber called Lettuce. We could have course have just used Cucumber with python, but given the big “WARNING – Experimental” notice Aslak wrote on this page, I thought we could give Lettuce a try.

So at the meeting we all worked together with one laptop and a projector, (me at the keyboard), and we started with a Lettuce scenario. We implemented step definitions using Django’s test Client, which is a kind of headless browser that understands how to instrument a Django application. Then we spent a couple of hours writing Django code together until the scenario was all green.

The code we ended up with isn’t much to write home about, but I’ve put it up on github here.

What we learned from this exercise
Of course since I know Rails much better, I found it interesting to compare the two web frameworks. Django seems similar in many ways. It was dead easy to get up and running, it gives you a basic structure for your code, and separates the model from the presentation layer.

The O-R mapping looks quite similar to ActiveRecord in the way you declare model classes backed by tables in the db. The presentation layer seems to have a different philosophy from Rails though. The html view part is rather loosely coupled to your application, and doesn’t allow you to embed real python code in it, just basic control structures.

You hook up the html to the controller code using url regular expression matching. I was a little confused about exactly how was supposed to work, since what I considered controller code was put in a file called “views.py”. Most of the code we wrote ended up in here, and I feel a bit unhappy with it. It seems to be a mixture of stuff at all levels of abstraction. The Django Form objects we used seemed quite powerful though, and reduced the amount of code we had to write.

The biggest difference I noticed compared with Rails was how explicit Python is about where stuff comes from. You always have to declaratively import or pass stuff before you can use it, so I found it straightforward to follow the connections and work out which code was executed and where it came from. I think that is because of Python’s philosophy of strict namespaces, which Ruby doesn’t have so much of.

I also liked the way Django encourages you to structure a larger web application into a lot of independent smaller ones, and lets you include and re-use other people’s small apps. Rails has plugins too of course, but I thought Django’s way made it seem very natural to contribute and re-use code.

Comparing Lettuce to Cucumber, they look almost the same, (by design). One small difference I found was that Cucumber step definitions don’t care if you write “Given”, “When” or “Then” in front of them, whereas Lettuce did. So I had steps like this:

Then I should see "results found"
And I should see "Name"

where the first step passed and the second step was reported as unimplemented by Lettuce. So Lettuce need a little more work to be really usable.

I was also pretty disappointed by the Django test client for implementing test steps. It seemed to interact with pages at an abstraction layer lower than I am used to – at the level of making post and get requests and parsing html as a dom. I missed Capybara and its DSL for interacting with web pages. I couldn’t find any equivalent. I probably should have turned to Selenium directly, but since we had no client side javascript it seemed overkill. (Francisco Souza has written about using Lettuce with Selenium compared with the Django test client here).

When it comes to unit-level testing, Django provides an extension to the normal unittest tool that comes with python (unittest was originally based on JUnit). We didn’t do much with it at the session, and it seemed to work fine. It’s nothing like RSpec though, and I miss that expressiveness and structure for my tests whenever I work in Python.

Overall
All in all it was fun to look at Django with a group and to get some really helpful comments and insights from people who know it far better than I do. The Kata we chose seemed to work ok, but I should really do it again in Rails since I spent the whole time comparing Django with Rails in my head, not Django with Johannes’ Java code 🙂

My conclusions are basically that Django looks like a good alternative to Rails. It would take time to learn, and surely has strengths and weaknesses I can’t really evaluate from one short session looking at it. However, I’d fairly sure I’d have to do some work improving the testing tools if I was going to be happy working with it for real.

I was at the local Ruby User Group last night, and I coded up KataMontyHall (see below) as a prepared Kata in front of the group. I got some great comments and feedback while I was coding, and I think the solution I ended up with was better than any I had created by myself during my practice sessions. I also got some new ideas about different approaches which I plan to try out and see if they improve the code even more.

Dave Hoover was visiting from the US, on his way to a speaking engagement at Öredev. He and I were both surprised to discover a common interest in the Monty Hall Dilemma. Dave has previously worked on it, and he showed us some code that he wrote 5 or 6 years ago when he was still learning Ruby. He even wrote an online version of the game when he was first learning ajax, that you can play yourself!

The Monty Hall Dilemma
There is a gameshow hosted by Monty Hall where contestants try to win a big prize, which is behind one of three doors. The contestant begins by choosing a door, but not opening it. Then Monty steps forward and opens one of the other doors. He reveals a goat (!). Then the contestant has the choice of either sticking with the door they have already chosen, or switching to the other unopened door. Whichever door the contestant decides on will be opened, and if they find the prize, they get to keep it. (I’m not sure what happens if they get the second goat!) So what’s the best strategy? Stick or switch?

People are biased towards sticking with what they’ve chosen, and the vast majority of people stick with the door they choose originally. Intuitively there should be an equal chance of the prize being behind any of the three doors, so it shouldn’t matter if you stick or switch. However, in this case, your intuition is wrong. You are twice as likely to win the prize if you switch to the other unopened door.

I am not the only one to think this result is incorrect, apparently famous mathematicians have also refused to accept it. What finally convinced them, was a computer simulation. Hmm I thought, that sounds like an interesting piece of code 🙂

Pigeons are smarter than Humans
I heard about the Monty Hall Dilemma listening to the quirks and quarks podcast. Apparently humans are strange, because they don’t learn to switch doors. Some researchers set up the same problem for pigeons, with birdseed behind one of the doors, and found the birds quickly learnt to switch doors. You can read the research for yourself!

So if you, like me, are keen to prove yourself more intelligent than a pigeon, why don’t you spend some time writing a little program that simulates the game? If you get it right, your version of KataMontyHall should clearly show that switching doors is the best strategy 🙂

On the wednesday of Agile Testing Days it was my turn to speak, and together with Fredrik Wendt we presented “The Coding Dojo as a forum for teaching Test Driven Development”. The talk was mostly aimed at developers, and the basic idea is to encourage them to learn TDD, and that going to a coding dojo might be a good way of doing that.

Michael Bolton
The first keynote of the day was by Michael Bolton, someone I’ve never met before. His talk really made me think. He presented himself as an “agile skeptic”, and had some criticisms of agile practices like automated unit and functional testing. He talked about testing as something that humans do – it is a “sapient activity” requiring an engaged brain. He said “Automated acceptance tests do not answer questions about value” – that is whether the software will be valuable to the people who are going to use it. He preferred to call them “rejection checks” – that is they check whether the software will be rejected, but do not test whether it will be accepted. Only a human can do that. Michael went on to question the large level of investment that agile teams make in these kinds of tests. He thought that effort could perhaps be better invested, when studies show only 6-15% of problems are regression issues.

Michael emphasized the role of testers in projects as “skilled investigators” who provide a service giving you information about a software product. He drew on an analogy with a film critic – they don’t tell you if the film has passed or failed, they tell you about the attributes of the film that will appeal more or less to certain audiences.

I liked the way Michael talked about testing as an investigative activity, and the role of testers as intelligent humans. I think he undervalues the feedback developers get from automated functional tests though. Agile teams do a lot more refactoring than other kinds of teams, and I think without automated tests they would have a lot more than 6-15% regression issues. I do think it is useful to evaluate investment in automated tests against other investments though. Some of the tools we have, particularly for functional/system level testing are not very cost effective to use.

I also think that testers can only start doing a “film critic” kind of role when the software is largely free of basic defects. These should be caught before a skilled tester gets their hands on the software, by developers properly checking their work, and automating those checks.

A little while ago, Fredrik Wendt and I put together a little survey and sent it to all the people we know who have attended coding dojo meetings here in Göteborg. There are several groups in the city which run these kinds of meetings from time to time. We wanted to know what kinds of things people are learning from practicing code katas in a group, and get some feedback and comments to help us to develop the groups we run.

The survey got 29 responses – thankyou to everyone who participated! I was very encouraged to see that the overwhelming majority – 90% – said they would recommend the dojo to other people who wanted to improve their programming skills. There were lots of comments too – I won’t include them all – but I particularly liked:

Fredrik and I set up JDojo@Gbg about a year ago, as an free coding dojo for Java programmers, sponsored by Iptor. We advertized it as a taught course – 5 sessions, once a month, come and learn TDD. We ran it twice together, and now Fredrik is continuing it together with Ola Berg.

The second sort of coding dojo going on in the town is various language user groups. It must be four years since I pestered Niclas Nilsson and CJ that we should do code Katas at Got.rb (Göteborg Ruby User Group). Inspired by the success of that group, and together with Andrew Dalke and Johan Lindberg, I set up GothPy (Gothenburg Python User Group) about two years ago. More recently, Jonas Nicklas set up Got.js (Göteborg javascript user group) and Jörgen Lundberg set up Scala Geats (Göteborg Scalaenthusiaster). So there are several small, language specific groups that meet and do dojo evenings occasionally, interspersed with other activities.

The third kind of coding dojo meetings going on is where people run them internally at their employer, which lots of people do from time to time. In addition, Fredrik and I are both facilitating these kinds of groups at clients, as part of our work coaching teams and encouraging them to be more agile.

I was pleased that people from all these sorts of groups filled in the survey, and that many people had been to more than one kind.

Most of the survey respondents had been to 4 or 5 dojo meetings:

We asked several questions about perceived skill level before and after participation in dojo meetings. We wanted to know what people thought they were learning, basically.

As you can see, people were fairly good at the programming language in question before the dojo(s), and only reported marginal improvements, 0.3 on average, on a five point scale.

When it comes to the IDE used in the dojo, again, we are looking at a modest improvement, also 0.3 on a five point scale.

Using Mock Objects is a topic that doesn’t always come up in dojo meetings, I personally have certainly had more of a focus on classic TDD. The feedback shows that people didn’t feel they were that good at it before the meetings, and not that much better afterwards – an average 0.5 increase on a 5 point scale. From some of the comments, I think this is an area to focus on more in future. To that end, we’re having a GothPy meeting next week looking at Mockist TDD 🙂

Refactoring is an essential part of Test Driven Development, and in fact any modern programmer’s toolbox. I was pleased to see that people thought the dojo had helped them to improve this skill too – 0.5 on a five point scale.

So it looks like going to a dojo encourages you to write unit tests more often – 0.6 (on a five point scale) more often on average.

This result is the most pleasing to me, since I think TDD is such an important skill, and it can be so difficult to get going with. People are moving from a low level of skill up to a medium level of skill – a whole 1 point (on a five point scale) on average! No-one is claiming to be a TDD expert yet though, I will have to repeat the survey in a few years and see if anyone is brave enough to claim that by then 😉

Fredrik and I are off to Agile Testing Days in a week or so, where we’ll be presenting a bit about what we’ve been doing at these various groups, and what we recommend for others starting their own coding dojos. We’ve learnt a lot by running these meetings, and had fun too. Hopefully these survey results might encourage you to find a coding dojo and improve your programming skills!

I’ve been working full time in Ruby now for about a month, and I think I’m beginning to get the hang of it. In many ways it’s not so different from Python.

I took some of the code I talked about struggling with in my last post, and set about translating it into Python. I wanted to see if the bugs were more obvious in a language I was more familiar with. Unfortunately before I was finished with the translation, my machine died and refused to restart, complaining about a disk error… so I may well have lost all my work. (ARRRGH!!) Anyway, before that happened, I was getting the feeling that the bugs weren’t very obvious, even in a language I knew better.

What I did find though, was that it was quite hard to make the methods as short in Python as they were in Ruby. I could make them as short, the language has the necessary features to do it, but when I did so, they just stopped looking like good Python to me.

The other thing that I found was that RSpec lets you write really readable and well organized tests. Translating them into unittest made them just a travesty of their former selves.

I’ve just listened to this talk by Gary Bernhardt, who is experienced in both Python and Ruby, and who has clearly thought quite hard about these kinds of issues and knows both languages very well. He has even tried to write a RSpec clone for Python, called Mote. (He says himself that it isn’t as good as RSpec, and that it is because Python lacks blocks, and won’t let him monkeypatch core classes).

Anyway, about half way through the talk, Gary shows this code example, first in Python:

'\n'.join(obj.name
    for obj in (
        repository.retrieve(id)
        for id in ids)
   if obj)

Then the equivalent code in Ruby:

ids.map do |id|
 repository.retrieve(id)
end.compact.map do |obj|
 obj.name
end.join('\n')

Gary makes the point that the Ruby code is easier to read – you can follow it from top to bottom and see what it does. The thing is, I don’t think many people would write code like that in Python. I might write it more like this:

objs = [repository.retrieve(id) for id in ids]
objs = filter(lambda x: x, objs)
names = [obj.name for obj in objs]
'\n'.join(names)

This code is four statements long, rather than one, and has two local variables (“objs” and “names”) which the other two code snippets lack. In real code, you would probably be able to come up with rather more descriptive names, drawn from the problem domain. When I compare this code with the Ruby, I don’t think it is any less readable. The filter(lambda x: x, objs) is not as nice as the Ruby call to “compact”, but on the other hand, I think the two additional local variables make it clearer what is going on.

I’m wondering whether the trouble I was having locating bugs in these small methods was because they were cramming so much into one statement, and almost completely lacking in local variables. That seems to be the Ruby way of doing things – maybe I will just get used to it and learn to read it just as well eventually? I guess I am going to find out!

Anyway, I’m really hoping the friendly support technicians manage to save the contents of my hard disk, I want to use the code in an exercise at the upcoming Gothenburg Python Conference – GothPyCon. I am hoping to run a workshop where half the room gets the buggy code with small methods, and the other half gets the same code refactored into longer methods. You get half an hour to find the bugs, then swap to the other codebase and find them again. Then I was hoping to have a discussion about which codebase was easier to debug, and/or split into pairs and re-implement the code from scratch, and see if we could come up with other designs that solved the problem more elegantly and transparently.

If issues like this interest you – design, refactoring and testing -, I really hope you will come along!