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Rich is a Python library for rich text and beautiful formatting in the terminal.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Documentation that simply works
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
NumPy aware dynamic Python compiler using LLVM
Bayesian Modeling and Probabilistic Programming in Python
Efficiently computes derivatives of NumPy code.
A Python toolbox for performing gradient-free optimization
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
📘 Automatic documentation from sources, for MkDocs.
Exploratory analysis of Bayesian models with Python
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
The Python ensemble sampling toolkit for affine-invariant MCMC
Display tabular data in a visually appealing ASCII table format
Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/
A toolkit for machine learning from time series
BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.
Synchrosqueezing, wavelet transforms, and time-frequency analysis in Python
Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python ⚡
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/