numba.jit is a function decorator that tells Numba to compile a Python function into native machine code using just-in-time (JIT) compilation. It can be used to speed up the execution of the function by compiling it to machine code, which can be faster than interpreting the Python code.
numba.njit is a function decorator that is similar to
numba.jit, but it has stricter requirements for the types of input and output that the function can accept and return. This means that
numba.njit may be more restrictive in the types of functions it can compile, but it may also be faster and more memory-efficient than
In general, you should use
numba.njit if you know that the function you are trying to compile has a simple and well-defined input and output, and you are willing to make any necessary changes to the function's signature to meet the requirements of
numba.njit. Otherwise, you can use
numba.jit, which is more flexible but may be slower and less memory-efficient.