science, and engineering. It includes modules for statistics,
optimization, integration, linear algebra, Fourier transforms, signal
and image processing, genetic algorithms, ODE solvers, and more. It
is also the name of a very popular conference on scientific
programming with Python.
The SciPy library depends on NumPy, which provides convenient and fast
N-dimensional array manipulation. The SciPy library is built to work
with NumPy arrays, and provides many user-friendly and efficient
numerical routines such as routines for numerical integration and
optimization. Together, they run on all popular operating systems, are
quick to install, and are free of charge. NumPy and SciPy are easy to
use, but powerful enough to be depended upon by some of the world's
leading scientists and engineers. If you need to manipulate numbers on
a computer and display or publish the results, give SciPy a try!
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