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Scientific Computing Tools for Python
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What is SciPy?

Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
SciPy is a tool in the Data Science Tools category of a tech stack.
SciPy is an open source tool with 12.6K GitHub stars and 5.1K GitHub forks. Here’s a link to SciPy's open source repository on GitHub

Who uses SciPy?

62 companies reportedly use SciPy in their tech stacks, including Sendcloud, tarfin, and Iziwork.

294 developers on StackShare have stated that they use SciPy.

SciPy Integrations

SciPy Alternatives & Comparisons

What are some alternatives to SciPy?
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
R Language
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.
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SciPy's Followers
173 developers follow SciPy to keep up with related blogs and decisions.