Efficient, reliable, and well-tested derivatives for scientific forecasting.

DerivKit provides a unified framework for numerical derivatives, Fisher/DALI expansions, and model forecasting — designed for cosmology but general-purpose across scientific domains.

DerivKit grew out of practical needs in cosmological inference — combining flexible derivative estimators with rigorous error control and clean, modern APIs.

• Documentation: https://docs.derivkit.org
• Website: https://derivkit.org

• derivkit — Core API for derivatives and forecasts
• derivkit-examples — Tutorials, demos, and benchmarks

If you use DerivKit in your research, please cite it as follows:

@software{sarcevic2025derivkit,
  author       = {Nikolina Šarčević
                  and Matthijs van der Wild
                  and Cynthia Trendafilova
                  and Bastien Carreres},
  title        = {derivkit: A Python Toolkit for Numerical Derivatives},
  year         = {2025},
  publisher    = {GitHub},
  journal      = {GitHub Repository},
  howpublished = {\url{https://github.com/derivkit/derivkit}},
}

DerivKit is released under the MIT License and actively maintained by
@nikosarcevic and the DerivKit team.