Hi Tim, An additional remark: if you're looking for a tool that is able to extract a complete call graph from a random Python program, then it's impossible. Only approximations can be done, like e.g. done in pylint, I believe. Such tools are pointless in PyPy but could be useful in other projects. For example I can imagine a tool that would statically compile some version of a random Python program, including all necessary guards to check at run-time that the assumptions made are correct. When these guards fail, it would fall back to a regular interpreter. The difference with PyPy is that the latter uses a tracing JIT compiler to do at run-time (partially) the same job as I describe above. It does it by observation of the run-time behavior, which is a rather better estimator of the program's general behavior than a complex static analysis. And it dispenses us from writing any such analysis. This gives us a result that is not specific to a particular version of Python (or to Python at all). A bientôt, Armin.