Numba on GitHub

Numba is a Just-In-Time compiler for Python that can speed up your Python code by an order of magnitude. The GitHub page for Numba is a treasure trove of resources, including documentation, examples, and community contributions.

Quick Links

Features

Just-In-Time Compilation: Numba translates a subset of Python and NumPy code into fast machine code.
Easy Integration: Numba works seamlessly with NumPy and can be used with existing Python code.
Wide Range of Applications: Numba is used in various fields such as scientific computing, data analysis, and machine learning.

Usage Examples

Here are some examples of how Numba can be used:

Vectorization: Speed up NumPy operations.

from numba import vectorize

@vectorize
def add(a, b):
    return a + b

print(add(1.5, 2.3))

Loop Unrolling: Speed up loops.

from numba import jit

@jit(nopython=True)
def loop_unroll(n):
    result = 0
    for i in range(n):
        result += i
    return result

print(loop_unroll(1000000))

Community Contributions

The Numba GitHub repository is a community-driven effort. Users contribute by fixing bugs, adding features, and sharing their experiences.

Conclusion

Numba is a powerful tool for speeding up Python code. The GitHub page is a valuable resource for learning more about Numba and its capabilities.