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Science & Computing

We are a community of scientists and engineers building high-quality, open-source scientific Python packages. Our tools are designed to bring production-grade numerical methods, mathematical routines, and engineering utilities directly into Python — with clean APIs, rigorous testing, and thorough documentation.

  • soerp3

    Second-order error propagation (uncertainty analysis) for Python. Transparently tracks uncertainty through mathematical calculations using the first eight statistical moments.

    License: BSD-3-Clause  |  PyPI: pip install soerp3

    Documentation   Source

  • sparse_grid

    Pure-Python implementation of regular sparse grids over box domains. Provides hierarchical index generation, coefficient conversion, and fast function evaluation using hat basis functions.

    License: BSD-3-Clause  |  PyPI: pip install sparse-grid

    Documentation   Source

  • polpack

    Special functions and recursively-defined polynomial families for Python. Fortran-backed routines for Bernoulli, Chebyshev, Gegenbauer, Hermite, Laguerre, Legendre polynomials, and more.

    License: LGPL-2.1  |  PyPI: pip install polpack

    Documentation   Source

  • smolpack

    Multidimensional quadrature over the unit hypercube using Smolyak's sparse-grid algorithm with Clenshaw–Curtis rules. Delayed and standard variants provided.

    License: LGPL-2.1  |  PyPI: pip install smolpack

    Documentation   Source

  • sdepack

    Runge–Kutta numerical integration of stochastic differential equations. Solvers from first-order Euler–Maruyama to fourth-order stochastic RK methods using Kasdin coefficients.

    License: MIT  |  PyPI: pip install sdepack

    Documentation   Source

  • deltaFlow

    Power system analysis tool for steady-state and dynamic simulation of electrical networks. Built for engineers and researchers working on grid analysis and planning.

    License: Open Source

    Documentation   Source

  • NULAPACK

    NUmerical Linear Algebra PACKage — lightweight, high-performance routines implemented in Fortran with Python and C++ interfaces. Developed under the nulapack organisation.

    License: GPL-3.0  |  PyPI: pip install nulapack

    Documentation   Source

  • pydoe

    Design of Experiments for Python — full-factorial, fractional-factorial, Plackett–Burman, Box–Behnken, central composite, and Latin Hypercube designs. Developed under the pydoe organisation.

    License: BSD-3-Clause  |  PyPI: pip install pydoe

    Documentation   Source

Get Involved

All packages are open source and openly developed on GitHub. We welcome bug reports, feature requests, and pull requests.