Ruffus is designed to allow scientific and other analyses to be automated with the minimum of fuss and the least effort.

pandarallel allows any Pandas user to take advantage of their multi-core computer, while Pandas uses only one core. pandarallel also offers nice progress bars (available on Notebook and terminal) to get an rough idea of the remaining amount of computation to be done.

This package provides a Python interface to the QDLDL LDL factorization routine for quasi-definite linear system.

This package provides a Python package for time series classification.

spin is a simple interface for common development tasks. It comes with a few common build commands out the box, but can easily be customized per project.

The impetus behind developing the tool was the mass migration of scientific Python libraries (SciPy, scikit-image, and NumPy, etc.) to Meson, after distutils was deprecated. When many of the build and installation commands changed, it made sense to abstract away the nuisance of having to re-learn them.

PyQtGraph is a Pure-python graphics library for PyQt5, PyQt6, PySide2 and PySide6. It is intended for use in mathematics, scientific or engineering applications.

This package is an implementation of the Promises/A+ specification and test suite in Python.

This package provides a stable interface for interactions between Snakemake and its report plugins.

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python.

Plotly's Python graphing library makes interactive,publication-quality graphs online. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.

An efficient Python implementation of the Apriori algorithm, which uncovers hidden structures in categorical data

The fast-histogram mini-package aims to provide simple and fast histogram functions for regular bins that don't compromise on performance. It doesn't do anything complicated - it just implements a simple histogram algorithm in C and keeps it simple. The aim is to have functions that are fast but also robust and reliable. The result is a 1D histogram function here that is 7-15x faster than numpy.histogram, and a 2D histogram function that is 20-25x faster than numpy.histogram2d.

A Snakemake executor plugin for running SLURM jobs.

paramz is a lightweight parameterization framework for parameterized model creation and handling. Its features include:

• Easy model creation with parameters.

• Fast optimized access of parameters for optimization routines.

• Memory efficient storage of parameters (only one copy in memory).

• Renaming of parameters.

• Intuitive printing of models and parameters.

• Gradient saving directly inside parameters.

• Gradient checking of parameters.

• Optimization of parameters.

• Jupyter notebook integration.

• Efficient storage of models, for reloading.

• Efficient caching.

This package provides common functions and classes for Snakemake and its plugins.

Datatree is a prototype implementation of a tree-like hierarchical data structure for xarray. Datatree is in the process of being merged upstream into xarray.

Hist is an analyst-friendly front-end for boost-histogram.

Deepdish is a Python library to load and save HDF5 files. The primary feature of deepdish is its ability to save and load all kinds of data as HDF5. It can save any Python data structure, offering the same ease of use as pickling or numpy.save, but with the language interoperability offered by HDF5.

geosketch is a Python package that implements the geometric sketching algorithm described by Brian Hie, Hyunghoon Cho, Benjamin DeMeo, Bryan Bryson, and Bonnie Berger in "Geometric sketching compactly summarizes the single-cell transcriptomic landscape", Cell Systems (2019). This package provides an example implementation of the algorithm as well as scripts necessary for reproducing the experiments in the paper.

Xarray (formerly xray) makes working with labelled multi-dimensional arrays simple, efficient, and fun!

Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures.

Scikit-image is a collection of algorithms for image processing.

Thi package implements a functionality for mean-preserving interpolation of 1D data (for example, time series) with splines.

PyAMG is a Python library of Algebraic Multigrid (AMG) solvers. It features implementations of:

• Ruge-Stuben (RS) or Classical AMG

• AMG based on Smoothed Aggregation (SA)

• Adaptive Smoothed Aggregation (αSA)

• Compatible Relaxation (CR)

• Krylov methods such as CG, GMRES, FGMRES, BiCGStab, MINRES, etc.

Dvc objects provides a filesystem and object-db level abstractions to use in dvc and dvc-data.