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SQLAlchemy seems to run quite a bit slower (2-3x) under PyPy. I've gathered some pstats profiles comparing the two. PyPy (latest nightly build) + SQLAlchemy (master ...

Avec Python, on multiplie le temps de traitement par 2.84 pour passer de 500 000 à 5 000 000. La consommation mémoire, quant à elle, fait fois 5. Avec Pypy, le facteur de temps est de 8 et celui de ...

Abstract: The use of Python as a high level productivity language on top of high performance libraries written in C++ requires efficient, highly functional, and easy-to-use cross-language bindings.