EGraphs in python, why we need them #137
Description
Abstract (2-3 lines)
E‑graphs are powerful data structures for representing equivalences via rewrite rules, enabling expressive and efficient program optimization. In this talk, we’ll explore Python's egglog library—bindings to the Rust-based egg-smol—and showcase why integrating e‑graphs is essential for modern symbolic, numeric, and ML workloads.
Brief Description and Contents to be covered
E‑graphs underpin techniques like equality saturation, empowering compilers, synthesizers, and verification tools to explore many equivalent program representations simultaneously. Python’s egglog library delivers these capabilities in a familiar, high-level API—bridging powerful rewriting abstractions into the broader scientific and ML ecosystem.
Pre-requisites for the talk
Link to slides:
ToDo
Will you be doing hands-on demo as well?
Jupyter note book with examples
Link to ipython notebook (if any):
ToDo
About yourself
I am a research fellow at Microsoft program synthesis group. I research mostly on AI for code with keen interest in formal methods and program synthesis.
Are you comfortable if the talk is recorded and uploaded to PyData Dellhi's YouTube channel?
Yes