Numba makes Python code go fast. It works by decorating your functions with decorators that tell Numba to compile them. It is particularly effective for code that involves heavy numerical loops and NumPy array manipulations.
Official docs: https://numba.pydata.org/numba-doc/latest/index.html User Guide: https://numba.pydata.org/numba-doc/latest/user/index.html Search patterns: @njit, @vectorize, prange, cuda.jit, numba.typed
This is the "gold standard" for Numba. In this mode, Numba compiles the code without using the Python C-API, resulting in maximum speed. If it can't compile (e.g., because of unsupported Python objects), it throws an error.
Un compilador Just-In-Time (JIT) para Python que traduce un subconjunto de código Python y NumPy en código de máquina rápido. Desarrollado por Anaconda, Inc. Altamente eficaz para acelerar bucles, funciones matemáticas personalizadas y algoritmos numéricos complejos. Úselo para @njit, @vectorize, prange, cuda.jit, numba.typed, compilación JIT, bucles paralelos, aceleración de GPU con CUDA, simulaciones Monte Carlo, algoritmos numéricos y computación Python de alto rendimiento. Fuente: tondevrel/scientific-agent-skills.