General Purpose Tools


estimagic is a Python package to fit large-scale empirical models to data and make inferences about the estimated model parameters. It is especially suited to solve difficult optimization problems. It provides several advantages over similar packages, including a unified interface that supports a large number of local and global optimization algorithms and the possibility of monitoring the optimization procedure via a beautiful interactive dashboard. It provides tools for nonlinear optimization, numerical differentiation, and statistical inference. (Documentation)


pybaum provides tools to work with pytrees which is a concept borrowed from JAX. Pytree’s refer to tree-like structures built out of container-like Python objects. We use pybaum in several of our packages. One notable example is estimagic. (Documentation)


dags provides tools to create executable dags from interdependent functions. (Documentation)