PyTorch is a Python package that provides two high-level features:

• tensor computation (like NumPy) with strong GPU acceleration;

• deep neural networks (DNNs) built on a tape-based autograd system.

You can reuse Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed.

Note: currently this package does not provide GPU support.

Macaroons, like cookies, are a form of bearer credential. Unlike opaque tokens, macaroons embed caveats that define specific authorization requirements for the target service, the service that issued the root macaroon and which is capable of verifying the integrity of macaroons it receives.

Macaroons allow for delegation and attenuation of authorization. They are simple and fast to verify, and decouple authorization policy from the enforcement of that policy.

pytest-perf makes it easy to compare works by creating two installs, the control and the experiment, and measuring the performance of some Python code against each. Under the hood, it uses the pip-run command to install from the upstream main branch (e.g. https://github.com/jaraco/pytest-perf) for the control and from . for the experiment. It then runs each of the experiments against each of the environments.

Pyinstrument is a Python profiler to help you optimize your code.

This pytest plugin provides fixtures to simplify Flask app testing.

This package provides a scalable Bloom filter implemented in Python.

This package provides a python API to read and write MIDI files.

This package provides a pytest plugin that allows multiple failures per test.

This package provides a plugin to test Python click interfaces with pytest.

This package provides a pytest plugin to check import ordering using isort.

This package provides a pytest plugin for generating NUnit3 test result XML output

The pytest-cache plugin provides tools to rerun failures from the last py.test invocation.

This package provides a pytest plugin for Sanic. It helps you to test your code asynchronously.

This package provides a pytest plugin to enable format checking with the Python code formatter "black".

This package provides a pytest fixture to mock httpx requests to be replied to with user provided responses.

python-pydantic enables specifying CLI via data models provided in the JSON format.

The goal of this project is to manage configuration for Python tools, such as rope and add support for a pyproject.toml configuration file.

This package provides a Pytest extension for sharding tests at the granularity of individual test cases, which can be run in parallel and on multiple machines.

This package provides a simple and lightweight Python SOAP library for client and server webservices interfaces, aimed to be as small and easy as possible, supporting most common functionality.

pytest-sugar is a plugin for py.test that changes the default look and feel of py.test, using a progress bar and showing failures and errors instantly.

A Python wrapper for the dialog utility. Its purpose is to provide an easy to use, pythonic and comprehensive Python interface to dialog. This allows one to make simple text-mode user interfaces on Unix-like systems

Redis fixtures and fixture factories for Pytest. This is a pytest plugin, that enables you to test your code that relies on a running Redis database. It allows you to specify additional fixtures for Redis process and client.

PyQt-builder is a tool for generating Python bindings for C++ libraries that use the Qt application framework. The bindings are built on top of the PyQt bindings for Qt. PyQt-builder is used to build PyQt itself.

The pytest-xdist plugin extends py.test with some unique test execution modes: parallelization, running tests in boxed subprocesses, the ability to run tests repeatedly when failed, and the ability to run tests on multiple Python interpreters or platforms. It uses rsync to copy the existing program code to a remote location, executes there, and then syncs the result back.