The query module is finally in the main SymPy repository. I made substantial changes since last post, most of them at the user interface level (thanks to Vinzent and Mateusz for many insightful comments). Main function is ask(), which replaces the old expression.is_* syntax. You can ask many things ...

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After some failed attempts, I just found how to change the language settings dynamically in django, and I thought it could be useful to someone. Just use function activate() from django.utils.translation. For example: [cc lang="python"] from django.utils.translation import activate activate('es-ES') [/cc] will change global ...

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Three months after I began to write sympy.queries, I feel it's about time to include it in sympy's trunk, so today I sent for review 4 patches that implement the complete query module. It's been a lot of fun, but it has also caused me some ...

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The 0.6.5 release of SymPy is taking longer than expected because some bugs in the testing framework, so my query module is not merged into trunk (yet). In the meantime, I am implementing a refine module (very little code is available yet). The refine module implements a refine ...

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Last days I've been busy preparing the first public beta of SymPy 0.6.5. Most of the time was spent solving a bug that made documentation tests fail under python2.4, but now that this is solved, I hope that by the end of the week we could ...

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Background: DPLL is the algorithm behind SymPy's implementation of logic.inference.satisfiable After reading the original papers by Davis & Putnam [1], I managed to implement a more efficient version of the DPLL algorithm. It is 10x times faster on medium-sized problems (40 variables), and solves some wrong result bugs ...

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After some hacking on the queries module, I finally got it right without the limitations of past versions. You can check it out from my repo http://fseoane.net/git/sympy.git, branch master. It now relies even more on logic.inference.satisfiable(), which is just an implementation of the ...

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The DIMACS CNF file format is used to define a Boolean expression, written in conjunctive normal form, that may be used as an example of the satisfiability problem. The new logic module (sympy.logic) can read the content of a cnf file and transform it into a boolean expression suitable ...

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Yesterday I finally merged the logic module in sympy's official master branch, and should be released together with SymPy 0.6.5. Next thing to do: profile the code and write some docs before the release.

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Most annoying problem in my implementation of the query system is that it will not solve implications if the implicates are far away from each other. For instance, if the graph of known facts is something like this

Integer ----> Rational --> Real --> Complex
  ^  ^
  |  |
  |   -------
  |         |
Prime      Even
  ^
  |
  |
MersennePrime

Then it will not know ...

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