Anatomy of a command

Creating an IronPython command to launch the command prompt isn’t much, since you can have a shortcut to do just that.
You might have noticed that the command subclasses “BaseIronPythonCommand”. This is an abstract class that implements the basics and just leaves the Name and the Execute method for you to implement:

There’s also an interface you can implement directly (IIronPythonCommand) if you want to assume control of everything.
BaseIronPythonCommand’s implementation is quite simple. Most of it is boilerplate for a Blaze plugin, leaving only the name and execution to be done in the script:

GetName is the name used to invoke the command. It should be something unique and descriptive. A long name is good, and you can teach Blaze a shortcut to it by typing the shortcut and selecting the command on the dropdown box. This teaches blaze about the shortcut.
GetDescription returns a description for the command, to be shown on the line below it on the interface.
AutoComplete returns a completion for the given string. This means you can transform “off” into “office” inside your command.
Execute tells the command the user has selected it. The command returns either a program to execute in the form of a path concatenated with the arguments, null if the command has executed itself.
Any one of these can be implemented in ironpython, although for basic commands you only need to implement GetName (or a property called Name) and Execute.

Tutorial: How to create your own plugins for Blaze-IronPythonPlugins (BPP)

On the first post in this series I presented Blaze IPP, which allows for scripting of a launcher using IronPython. Here I tell you how you can write your own plugins from scratch. It will be a short post.

First of all, I assume you’re already running Blaze with the plugin installed.

Let’s create a new directory under “Plugins” to store our new plugins. This way if any future upgrade on IPP brings an ironpython file with the same name, your plugin will not be overwritten. We’ll call it LocalIronPythonPlugins:

Now, configure IPP to also monitor that directory. Call Blaze, right click on it and in the “settings” open the “Plugins” tab. Select “IronPythonHostPlugin”, “Configure” and add the newly created directory (you can either browse to it with “b” or you can paste the path into the text box):

Now that we have a clean directory to work with, let’s create a file called “OpenCommandLine.ipy”. Open it and add the following code:

As you can probably guess, this will create a new command named OpenCommandLine, and when you select it it will open a new command prompt. IPP is clever enough to know that if a command returns a string, it is a program to be executed.

This is just a simple example to get you started. Since this is IronPython, you can use the entire .Net framework and fetch things from the web, open the registry, connect to a remote host or start a service, to give a couple of examples.

Creating plugins in IronPython for Blaze, an application launcher.

Everyone loves the start menu from Windows Vista/7, but compared to Launchy, Quicksilver or any other application launchers it’s a bit anemic. No wonder, since it’s just a search over your start menu and indexed locations.

But even any one of those is a bit lacking in support for runtime extensibility. You can create plugins, but it involves C (or Objective-C in the case of Quicksilver) and restarting the app. Not very friendly for those cases where you just want to pick up the currently selected object and throw it over an scp connection autocompleted from your favorites.

Enter Blaze + IronPythonPlugins. Blaze is a .Net application launcher for Windows that includes a learning facility that tries to complete repetitive tasks for you. IronPythonPlugins is a plugin itself for Blaze that hosts simple plugins written in IronPython.

If you want to try it just download the latest version from here. It includes a version all ready to use. Start the app, call it with Ctrl+Alt+Space and try a couple of plugins:

• Open windows explorer, select a text file, call blaze and type “edit with notepad2”. If you have notepad2 in your path, it will be launched with the selected file opened.
• If you use putty (the ssh terminal), “putty <name of session>” will launch putty with that session. Here session is autocompleted, so if you have a session called “my.home.box”, typing “putty home<tab>” will autocomplete to “putty my.home.box”.
• Type “random-text <number>” and your clipboard will have up to <number> random letters. Useful to generate test data.

There are a couple more plugins in the “Plugins\IronPythonPlugins” directory, so if you’re interested in how it’s done, open them in your editor of choice. In the next few days I’ll do a couple of posts on how you can create your own plugins without having to guess from the already existing ones.

If you want to change anything edit the file, save it and Blaze will automatically pick it up, together with any other .ipy file in that directory that has changed. If you open Blaze’s configuration page for the plugin, you can add other directories to search for .ipy files. Useful to keep your personal plugins separated from the “official” ones.

Sadly errors are still only sent to a System.Diagnostics.Debug, so if you edit a file and can no longer use it, open DbgView, edit the file again to force blaze to reload it and be on the lookout for output starting with “Error with file”. There will be a stacktrace telling you what you did wrong.

So, try it, have fun and comment on it. I’d love to hear what other people think of it.

Toggling with an IEnumerator and yield.

Instead of using a state variable to jog around and check what is the state of a window, why not just use an infinite collection?

public partial class Admin : Window
    {
        private IEnumerator _toggler;

        public Admin()
        {
            InitializeComponent();
            _toggler = Toggler().GetEnumerator();
        }

        public void Toggle()
        {
            _toggler.MoveNext();
        }

        private IEnumerable Toggler()
        {
            while (true)
            {
                Show();
                yield return new object();
                Hide();
                yield return new object();
            }
        }
    }

I wonder if this is a good pattern, or just me being "clever".

Using ironpython to generate nhibernate mapping files from a fluent configuration

I admit, this is a bit of a goldberg machine, but here's the context:

In my current project we need to store a bunch of events related to some 20 entities. Those events are the same for all entities, and they all need to be stored in the database. We use NHibernate to handle the "talk to the database" part, and fluent-nhibernate to configure the mappings via conventions for the most part. There are some entities which are either manually mapped or have specific overrides for particular cases (manually mapping some entities and automapping others is a mistake I think I'll avoid in the future).

For the most part this setup does wonders. We can add and change our entities and the mappings are generated without we thinking much of it. Since development speed has a larger priority than runtime speed in this project, we don't have much problems with the default mappings that are generated.

Except in the case of those events. Since the events are the same for all the entities, the event classes are open generics. Now, nhibernate can't map open generics, but can map closed generics, which is how we do it. We just iterate through all the types in the assembly that correspond to our entities and map those with fluent. The problem then becomes one of performance. As of now there are about 500 generated classes, and those take a while to discover and map. Since we're using fluent nhibernate to configure it in runtime, this means that each time the app is restarted there's a small downtime (on the scale of about 1 minute). While that's not much for an app in production, while developing one tends to restart the app a bit often. That's a problem in the day to day work.

I used our integration test suite to time the mapping, and on my pc it took about a minute to run. On the other hand, if we already have an .hbm file to feed to nhibernate, we can shave about 30 to 40 seconds. That's less than half the time for a simple trade-off of having to know when to generate the mappings.

To generate the mapping we could have created a new console project to just call the correct methods on our session provider factory, which would be a bit overkill. All we needed was to setup the environment and ask fluent for the mapping file.

And here is something that IronPython shines in.

Just create an .ipy file, add references to the correct assemblies, and since there's a clear separation of concerns (or so we hope), it's easy to configure fluent and ask it to generate the mappings for us. Most of the time you'll use .net code like you do in c# or vb.

There are only a couple of issues here:

- We need to remember to regenerate the hbm files when classes/mapping changes

- We need to remember to recompile both before and after regenerating hbms. Since we're loading the assemblies with ironpython outside of visual studio, the script doesn't know if the assemblies are stale or not.

Most of this can be avoided by having a build server rebuild the hbm files on its own and fail the build if they don't match with the latest in the source control. Of course, we could just have it commit the files, but that's one step I'm not fully comfortable with.

Notes and reflections about the second annual scrum meeting in Portugal

A month ago I attended the second annual Scrum Meeting in Portugal, and ended up taking some notes about two of the presentations.

Here they are, both for the team at weListen, and for the world at large.

Notes on "A Practical Roadmap to Great Scrum:A Systematic Guide to Hyperproductivity" presented by Jeff Sutherland

This was the presentation that changed the way I perceive scrum. Where before I saw scrum as an agile software development methodology like xp, now I see it as a management and process template. This means a team should use scrum and complement it with technical practices. Apart from that, the largest focus to me was on 3 velocity multipliers for teams and 2 required practices for hyper-productive teams.

The 3 velocity multipliers are ready, done and self-organization. Ready and done shield an iteration from churn. A story only enters development when it is ready, and by the end of the sprint it should be done. Ready means that the story is understood and sized by the team with input from the client, and done means the same story is tested and approved to be deployed. Self-organization ties nicely into the two required practices mentioned: talk about problems and fix the same problems.

Two classes of problems mentioned: bugs that take more than 8 hours to fix, and stories that take more than twice the calendar time than estimated ideal time. For each bug or story in this situation, do a root cause analysis to figure out the underlying problem. This can be multitasking (a dev assigned to several projects), final inspection or testing done too late or interruptions and form the basis of an impediment list for the team together with the product owner and scrum-master to solve.

There were several interesting data points mentioned. In a given company, the peak of productivity was measured on 60 hour work weeks in waterfall projects, and on 30 hour work weeks with double story points delivered. This means an productivity increase of about 3 to 4 times. Part of the presentation used Systematic, a dutch software company as the source for several data points for scrum teams. They noticed a linear scale in developer productivity for project sizes, going against Brook's Law, although I think the Law mentioned adding people to an already late project, and didn't mention scale. They apparently implemented scrum using Mary Poppendieck's lean tools as described in her book.

Some "required truths" about hyper-productive teams were discussed, and I found them interesting insights. The ones that stuck to my mind the most were:

• Everyone must be trained in scrum. This is so that all the players follow the same playbook and the concepts and practices are well understood.
• Backlog must be ready to implement before the sprint, and done by the end (tying into the concepts of ready and done mentioned earlier) .
• Pair immediately on a task if there's only one person capable of handling it, to avoid bottlenecks in the throughput.
• Short sprints (often just one week)
• Servant leadership, where the product owner and scrum-master are a resource of the team, instead of using the team as a resource.
• No multitasking. This one I'm a bit curious as to how realistic it is, considering maintenance work, and teams with many past projects.

Overall it was a very interesting presentation. There are several videos on youtube with Jeff Sutherland about scrum. This one is very similar to the one I saw.

Notes on "Scrum and TFS 2010" by Mitch Lacey

This was mostly a storytelling and demo about new features in TFS. I did end up asking Mitch about the importance of accounting for time originally estimated, time in task and time remaining for small and recent to scrum teams, as to me it seemed a bit too much bureaucracy for a small team. The answer was enlightening, since those numbers are particularly important for those teams as a way to surface problems (either with estimation, delays, interruptions or other causes). This means I might start looking into accounting for such numbers. "You can't manage what you don't measure". When a team gels and is proficient, the numbers may not matter as the team starts getting into the groove and noticing impediments becomes intuitive.

OCD and filenames, as pertaining to TV series

I like all my file names to be similar, and this applies to both mp3 and series. For mp3 I use the wonderful foobar2k to tag and rename files, but for series I ended up coding my own formatter. All this assumes a linux system (as is my home server, flatline)
First of all, to extract the video files from the rars:

find -name "*rar" -type f -exec rar e {} \;

This extracts all rars from under the current directory (and subdirectory) into the working directory.
If the files already come uncompressed, but are in subdirectories:

find -name "*mkv" -type f -exec mv {} . \;

Replace mkv with avi if that's what you've got.
Now, sometimes the files come in different formats. Some have [season][episode], others [season]x[episode], and I'd like for them all to be in the same [title]S[season]E[episode] format.
For that all you need is the following python script:


It can take 2 arguments: the directory where the file names are, and a title that overrides the one found in the file names. Hope this is helpful for someone else :)