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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.
Donfig is a python library meant to make configuration easier for other python packages. Donfig can be configured programmatically, by environment variables, or from YAML files in standard locations.
Bracex is a brace expanding library (à la Bash) for Python. Brace expanding is used to generate arbitrary strings.
The Traits library is designed to enhance object-oriented programming in Python by providing a way to define and manage attributes of objects more effectively.
dask-jobqueue makes it easy to deploy Dask on common job queuing systems typically found in high performance supercomputers, academic research institutions, and other clusters, like PBS, Slurm, MOAB, SGE, LSF, and HTCondor.
This package provides utilities for downloading several URL as one, as well as supporting multi-part URLs.
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.
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.
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.
Mayavi is a general purpose, cross-platform tool for 2-D and 3-D scientific data visualization.
This package provides common CLI patterns on top of Click.
A Python module to read Matlab files. This module works with both the old (< 7.3) and the new (>= 7.3) HDF5 based format. The output should be the same for both kinds of files.
TensorFlow is a flexible platform for building and training machine learning models. It provides a library for high performance numerical computation and includes high level Python APIs, including both a sequential API for beginners that allows users to build models quickly by plugging together building blocks and a subclassing API with an imperative style for advanced research.
ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.
NumPyro is a lightweight probabilistic programming library that provides a NumPy backend for Pyro. It relies on JAX for automatic differentiation and JIT compilation to GPU / CPU.
This module contains classes for the object model defined by the Static Analysis Results Interchange Format (SARIF) file format.
TensorFlow is a flexible platform for building and training machine learning models. It provides a library for high performance numerical computation and includes high level Python APIs, including both a sequential API for beginners that allows users to build models quickly by plugging together building blocks and a subclassing API with an imperative style for advanced research.
ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.
This is a collection of independent Python modules providing utilities for various projects.
JAXopt provides hardware accelerated, batchable and differentiable optimizers in JAX.
Hardware accelerated: the implementations run on GPU and TPU, in addition to CPU.
Batchable: multiple instances of the same optimization problem can be automatically vectorized using JAX’s
vmap.Differentiable: optimization problem solutions can be differentiated with respect to their inputs either implicitly or via autodiff of unrolled algorithm iterations.
This library implements support for mixed precision training in JAX. It provides two key abstractions. These abstractions are mixed precision policies and loss scaling.
ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.
This package provides tools for Makefile execution powered by pure Python.
Protocol buffers are a language-neutral, platform-neutral extensible mechanism for serializing structured data.