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scipy

SciPy is an open-source Python library for scientific computing. It extends NumPy with a collection of algorithms and high-level functions for mathematics, science, and engineering. It is designed to work with NumPy arrays and provides efficient implementations of numerical routines for linear algebra, integration, optimization, interpolation, signal and image processing, statistics, and more. The library combines Python wrappers with compiled code (C, Fortran, and Cython) to deliver performance and a coherent API across domains.

Core subpackages include scipy.integrate, scipy.optimize, scipy.interpolate, scipy.signal, scipy.linalg, scipy.spatial, scipy.stats, scipy.fft, scipy.ndimage, and scipy.io, among others.

History and governance: SciPy originated in the early 2000s as a successor to Numeric and an extension

Use: SciPy is a foundational tool in academia and industry for numerical analysis, data analysis pipelines,

The
project
emphasizes
interoperability
with
other
scientific
Python
tools
such
as
Matplotlib
for
plotting
and
pandas
for
data
handling.
of
NumPy.
It
was
developed
by
a
community
of
researchers
and
developers,
with
core
contributors
such
as
Eric
Jones,
Pearu
Peterson,
and
Travis
Oliphant.
The
project
is
released
under
the
BSD
license
and
is
maintained
through
a
community-driven
process
on
GitHub,
with
tests
and
continuous
integration
supporting
releases.
simulations,
optimization,
and
signal
processing.
It
is
widely
used
in
scientific
research
and
engineering
workflows
and
often
serves
as
the
core
of
broader
Python-based
scientific
ecosystems.