Francesco Bonazzi
Highly skilled Software Engineer and Data Scientist at Intesa Sanpaolo Bank, based in Milan, Italy. With a strong foundation in computational subjects, I hold a PhD in Physics with a specialization in computational modelling of biophysical processes. Having transitioned to the banking sector, I have applied my expertise to drive innovation in financial-related projects for numerous years. Additionally, I contribute to the open-source community as a maintainer and developer of the SymPy library, a widely-used computer algebra system.
@upabjojr
GitHub/GitLab profile URL – LinkedIn – Photo – euroscipy-2025/question_uploads/foto_petra_SWdvhVc.jpg
Session
This presentation explores an experimental integration between SymPy (symbolic mathematics) and MatchPy (associative-commutative pattern matching), both open-source Python libraries. By leveraging MatchPy's efficient pattern matching, which allows for multiple matches with a single expression tree visit, the combined system enhances SymPy's ability to solve equations, compute derivatives and integrals, and handle differential equations. An experimental RUBI formula integration algorithm implementation demonstrates the practical benefits.