I came back yesterday from the third Italian PyCon (aka pycon3) which was held in Florence and all I can say is that has been an amazing experience. I had the chance to meet a lot of new great people as well as the BDFL (which won’t be back in Europe for quite some time, as he said). Here follows a resume of what I think were the most interesting talks.
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The last time I blogged about a new course I’m following at my university. This course, held by Pasquale Lops and Giovanni Semeraro, is very interesting at the point that I’ll be developing a custom information retrieval engine as part of my internship project. I can’t tell much more at this point since the internship haven’t started yet and I’m not sure I can release more details about this project (we’re still in the process of deciding if and how the whole thing will be released to the world).
In the meantime, I’ve been doing several experiments on this topic mostly about the memory usage and the performances of such system on limited hardware. This practically means implementing the algorithms you’ll be using and measuring the computational time they require.
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It has been about a week since I began doing a deeper study of information retrieval. Actually, everything just began with a new course at my university about that and I just fallen in love almost immediately. The fact is that this thing really got me interested, and I began doing some experiments (one involves django as well, keep reading to know more).
In this week I learned a lot of things about information retrieval, text categorization, natural language processing and machine learning. But the most relevant thing is: the principles are easy, their implementation is not. The fact is that most of the techniques are relatively simple but you usually have to deal with very large datasets and this could be challenging, since one of the main requirements about information retrieval is time. It’s really much more important that you give less results in one second rather than giving better results in one hour. No one will ever care to use your system if it takes an hour to get some result. And if you’re considering to store your data in a database forget about normalization, it wouldn’t really take you anywhere.
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Today I just ended one of my side projects: pytagram. Basically it generates an SVG file (that can successively be saved as eps/pdf/whatever and eventually manually manipulated) starting from a tree-like plain text file. This can be useful for generating cheat sheets or quick references to classes or functions that belongs to some project.
I did this for generating a django quick reference (here it is) since it has a lot of functions and I know what’s their purpose, but I can never remember the names (and now two A4 papers are right in front of me).
If you’re interested in this, check out the google code project page and grab your copy from the SVN repository.
There are tons of things that can be changed/optimized (i.e.: add some optional short explanation of the function, add more examples, easier way to change colors, …) but now the code is working quite well so that can be already useful to the people out there.