FontAwesome icons in PyQt and PySide applications.

This package provides a domain-specific language for modeling convex optimization problems in Python.

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

This package implements a functionality to work with Nested sampling, a popular numerical method for Bayesian computation, which simultaneously generates samples from the posterior distribution and an estimate of the Bayesian evidence for a given likelihood and prior. nestcheck provides Python utilities for analysing samples produced by nested sampling, and estimating uncertainties on nested sampling calculations (which have different statistical properties to calculations using other numerical methods).

Uproot is a Python library for reading and writing ROOT files. It uses NumPy and does not depend on C++ ROOT.

python-pandera provides a flexible and expressive API for performing data validation on dataframe-like objects to make data processing pipelines more readable and robust. Dataframes contain information that python-pandera explicitly validates at runtime. This is useful in production-critical data pipelines or reproducible research settings. With python-pandera, you can:

• Define a schema once and use it to validate different dataframe types.

• Check the types and properties of columns.

• Perform more complex statistical validation like hypothesis testing.

• Seamlessly integrate with existing data pipelines via function decorators.

• Define dataframe models with the class-based API with pydantic-style syntax.

• Synthesize data from schema objects for property-based testing.

• Lazily validate dataframes so that all validation rules are executed.

• Integrate with a rich ecosystem of tools like python-pydantic, python-fastapi and python-mypy.

This is a Python implementation of the APTED algorithm,which supersedes the RTED algorithm for computing the tree edit distance.

pyts is a Python package for time series classification. It aims to make time series classification easily accessible by providing preprocessing and utility tools, and implementations of state-of-the-art algorithms. Most of these algorithms transform time series, thus pyts provides several tools to perform these transformations.

This package provides fast computations for principal component analysis (PCA), SVD, and eigendecompositions via randomized methods

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.

The CMasher package provides a collection of scientific colormaps and utility functions to be used by different Python packages and projects, mainly in combination with Matplotlib. It offers several alternatives to commonly used colormaps, like chroma and rainforest for jet; sunburst for hot; neutral for binary; and fusion and redshift for coolwarm.

PyTensor is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is a fork of the Aesara library.

Numpoly is a generic library for creating, manipulating and evaluating arrays of polynomials based on numpy.ndarray objects.

scikit-fem is a library for performing finite element assembly. Its main purpose is the transformation of bilinear forms into sparse matrices and linear forms into vectors.

xarray-dataclass is a Python package that makes it easy to create xarray's DataArray and Dataset objects that are "typed" (i.e. fixed dimensions, data type, coordinates, attributes, and name) using the Python's dataclass. It's a successor of not maintained https://github.com/astropenguin/xarray-dataclasses.

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.

This package provides an extremely lightweight compatibility layer between dataframe libraries.

• full API support: cuDF, Modin, pandas, Polars, PyArrow

• lazy-only support: Dask, DuckDB, Ibis, PySpark, SQLFrame

This package provides a Pytest plugin that facilitates the comparison of images produced by PyVista, generating cached images from tests and comparing subsequent results against that cache.

The fastcluster package implements seven common hierarchical clustering schemes efficiently. The package is made with two interfaces to standard software: R and Python.

Trimesh is a pure Python library for loading and using triangular meshes with an emphasis on watertight surfaces. The goal of the library is to provide a full featured and well tested Trimesh object which allows for easy manipulation and analysis, in the style of the Polygon object in the Shapely library.

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

meshzoo is a mesh generator for finite element or finite volume computations for simple domains like regular polygons, disks, spheres, cubes, etc.

The TDDA Python module provides command-line and Python API support for the overall process of data analysis, through tools that perform reference testing, constraint discovery for data, automatic inference of regular expressions from text data and automatic test generation.

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.