This package introduces a function decorator preventing a function from being called more often than that allowed by the API provider. This should prevent API providers from banning your applications by conforming to their rate limits.

The TraitsUI project provides a toolkit-independent GUI abstraction layer, which is used to support the “visualization” features of the Traits package. You can write a model using the Traits API and specify a GUI using the TraitsUI API (views, items, editors, etc.), and let TraitsUI and your selected toolkit back-end (Qt or Wx) take care of the details of displaying them.

Python library to build pretty command line user prompts.

Backport of pathlib ABCs.

Compute a single hash of the file contents of a directory.

This package provides classes and functions for performing customizable robust ICA.

Pyface contains toolkit-independent GUI abstraction layers, used to support the TraitsUI package. Thus, you can write code in the abstraction of the Pyface API and the selected toolkit and backend take care of the details of displaying them.

Envisage is a Python-based framework for building extensible applications, that is, applications whose functionality can be extended by adding 'plug-ins. Envisage provides a standard mechanism for features to be added to an application, whether by the original developer or by someone else. In fact, when you build an application using Envisage, the entire application consists primarily of plug-ins. In this respect, it is similar to the Eclipse and Netbeans frameworks for Java applications.

Easily pick a place to store data for your Python code.

This package provides a hierarchical data modeling framework for modern science data standards.

h5io is a package designed to facilitate saving some standard Python objects into the forward-compatible HDF5 format. It is a higher-level package than h5py.

This package provides a flexible utility for flattening and unflattening dict-like objects in Python.

Paste provides a variety of web development tools and middleware which can be nested together to build web applications. Paste's design closely follows ideas flowing from WSGI (Web Standard Gateway Interface).

This package provides functions for 3D coordinate transformations.

Implements iterative statistics operators for mean, variance, high-order moments, extrema, covariance, threshold, quantile (experimental) and Sobol' indices.

The Enable project provides two related multi-platform packages for drawing GUI objects.

• Enable: an object drawing library that supports containment and event notification.

• Kiva: a multi-platform DisplayPDF vector drawing engine.

Confit is a complete and easy-to-use configuration framework aimed at improving the reproducibility of experiments by relying on the Python typing system, minimal configuration files and command line interfaces.

This package provides common CLI patterns on top of Click.

Chaco is a Python package for building interactive and custom 2-D plots and visualizations. Chaco facilitates writing plotting applications at all levels of complexity, from simple scripts with hard-coded data to large plotting programs with complex data interrelationships and a multitude of interactive tools. While Chaco generates attractive static plots for publication and presentation, Chaco differs from tools like Matplotlib in that it also works well for dynamic interactive data visualization and exploration.

ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.

This module contains classes for the object model defined by the Static Analysis Results Interchange Format (SARIF) file format.

TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of probabilistic methods with deep networks, gradient-based inference via automatic differentiation, and scalability to large datasets and models via hardware acceleration (e.g., GPUs) and distributed computation.

Optax is a gradient processing and optimization library for JAX.

JAX is Autograd and XLA, brought together for high-performance numerical computing, including large-scale machine learning research. With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order.