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Alexis Métaireau
9df3b183b6
- Added the ability to display book cover for the category "Lectures" if ISBN cover is available. - Moved author's name into a small tag for better hierarchy and readability. - Implemented a feature to indicate link sizes depending on the number of articles associated with a given tag. - Implemented a mini footer element displaying an RSS feed icon. - Improved category display using description dictionary. - Added a new plugin "isbn_downloader" to fetch ISBN information when needed. - Included the count of articles for each category. - Implemented changes for better layout and readability of tags and categories. - Adjusted the layout of the webpage, improving the overall look of the page. - Included "requests" in the requirements.txt for supplanting dependencies required by the new plugin and/or features.
62 lines
2.7 KiB
Markdown
62 lines
2.7 KiB
Markdown
# Using dbpedia to get languages influences
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While browsing the Python's wikipedia page, I found information about
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the languages influenced by python, and the languages that influenced
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python itself.
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Well, that's kind of interesting to know which languages influenced
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others, it could even be more interesting to have an overview of the
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connexion between them, keeping python as the main focus.
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This information is available on the wikipedia page, but not in a really
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exploitable format. Hopefully, this information is provided into the
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information box present on the majority of wikipedia pages. And… guess
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what? there is project with the goal to scrap and index all this
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information in a more queriable way, using the semantic web
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technologies.
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Well, you may have guessed it, the project in question in dbpedia, and
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exposes information in the form of RDF triples, which are way more easy
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to work with than simple HTML.
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For instance, let's take the page about python:
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<http://dbpedia.org/page/Python_%28programming_language%29>
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The interesting properties here are "Influenced" and "InfluencedBy",
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which allows us to get a list of languages. Unfortunately, they are not
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really using all the power of the Semantic Web here, and the list is
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actually a string with coma separated values in it.
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Anyway, we can use a simple rule: All wikipedia pages of programming
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languages are either named after the name of the language itself, or
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suffixed with "( programming language)", which is the case for python.
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So I've built [a tiny script to extract the information from
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dbpedia](https://github.com/ametaireau/experiments/blob/master/influences/get_influences.py)
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and transform them into a shiny graph using graphviz.
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After a nice:
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$ python get_influences.py python dot | dot -Tpng > influences.png
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The result is the following graph ([see it directly
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here](http://files.lolnet.org/alexis/influences.png))
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While reading this diagram, keep in mind that it is a) not listing all
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the languages and b) keeping a python perspective.
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This means that you can trust the scheme by following the arrows from
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python to something and from something to python, it is not trying to
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get the matching between all the languages at the same time to keep
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stuff readable.
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It would certainly be possible to have all the connections between all
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languages (and the resulting script would be easier) to do so, but the
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resulting graph would probably be way less readable.
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You can find the script [on my github
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account](https://github.com/ametaireau/experiments). Feel free to adapt
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it for whatever you want if you feel hackish.
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