The Python language is hard to optimize. Let's see how guards checked at runtime allows to implement new optimizations without breaking the Python semantic.
(Almost) everything in Python is mutable which makes Python a language very difficult to optimize. Most optimizations rely on assumptions, for example that builtin functions are not replaced. Optimizing Python requires a trigger to disable optimization when an assumption is no more true. FAT Python exactly does that with guards checked at runtime. For example, an optimization relying on the builtin len() function is disabled when the function is replaced.
Guards allows to implement various optimizations. Examples: loop unrolling (duplicate the loop body), constant folding (propagates constants), copy builtins to constants, remove unused local variables, etc.
FAT Python implements guards and an optimizer rewriting the Abstract Syntax Tree (AST). The optimizer is implemented in Python so it's easy to enhance it and implement new optimizations.
FAT Python uses a static optimizer, it is less powerful than a JIT compiler like PyPy with tracing, but it was written to be integrated into CPython.
Speakers: Victor Stinner