Description
Numerical Python projects can mark hot functions for ahead-of-time or just-in-time acceleration. This developer tool and library integrates with compilers such as Pythran, Cython, or Numba, so scientific code can keep a Python source interface while selected functions run faster.
It is used through source annotations and build commands, not as a normal app. Developers should expect compilation dependencies and review generated or native code paths before trusting performance or deployment results.