Hi Python developers, We are happy to announce our first release of PyStructure, a structure and dependency analyser for Python code (written in Java). It is now in a state where it can parse and analyse real-world projects (with limitations, see below) and show the results in Structure101g, a dependency visualiser.
To try it out with your projects, download pystructure.zip from the following address and follow the instructions in the README file: http://pystructure.ifs.hsr.ch/release/ We are two students working on this as our bachelor thesis. The project page can be found at: http://pystructure.ifs.hsr.ch/ We are very eager to hear your feedback about our project. What do you think about the idea of a 'structural analyser' for a dynamic language like Python? Does it work for your project (probably not very well at the moment)? Cheers, Reto Schüttel Robin Stocker About PyStructure ----------------- Our project's goal is to develop a structural analyser for programs written in the Python programming language. The analyser should be able to parse an application's source code, analyse it and then generate a graph representing the internal structure of the project. As Python is a dynamic language most of the interesting details (i.e. type) are not known before the application is running. The analyser has to 'guess' the correct type by analysing the code base. The project is licensed under the LGPL (v2 or later), see the COPYING file. Current Limitations ------------------- Although the engine already supports a wide variety of cases it still lacks some very important features: - No support for inheritance Currently the engine ignores everything that involves inheritance. For example if a method is implemented in a base class it won't be found if it was called on an instance of a sub class. - Type of list/dict elements is not known The type of container elements cannot be determined yet. For projects which heavily rely on lists this means that a lot of types can't be determined. - Only little support for built-ins Only a few built-in operations are recognised. For example the type inference engine doesn't yet know that len("str") returns an integer. We are working on tackling these issues in the next two milestones and we hope to improve the accuracy of the engine significantly. Possible Applications --------------------- Our library (especially the type inferencer we use) might be interesting for other applications. For example: - Code completion and navigation in IDEs And it might improve the accuracy of tools which: - Detect unused/dead code - Look for possible bugs in code (like FindBugs for Java) - Do type checks and optimisations at compile time References ---------- - DDP: Demand-Driven Analysis with Goal Pruning by Lex Spoon http://www.lexspoon.org/ti/ - Headway Software http://www.headwaysoftware.com/ -- http://mail.python.org/mailman/listinfo/python-list
