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.

Documentation at https://melpa.org/#/python-pytest

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 Mako template bindings for the Pyramid web framework.

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 SAML Python Toolkit lets you add SAML support to your Python software.

This package implements a functionality to share a state / intermediate results across test steps.

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

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

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.

This package provides a Pytest plugin which leverages @pytest.mark.parametrize decorator separating test cases from test functions.

This plugin defines Pytest markers to ensure that some tests, or groups of tests run in a specific order.

This package provides Pytest plugin which splits the test suite to equally sized sub suites based on test execution time.

This package provides a plugin for Pytest which adds the ability to retry flaky tests, thereby improving the consistency of the test suite results.

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