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.

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.

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.

This package contains bindings for the ADBC Driver Manager, as well as a DBAPI 2.0/PEP 249-compatible interface on top. This can be used to load ADBC drivers at runtime and use them from Python. Backend-specific packages like adbc_driver_postgresql wrap this package in a more convenient interface, and should be preferred where they exist.

A Flake8 plugin that checks for the line continuation style to be in the preferred method according to PEP-8, specifically:

The preferred way of wrapping long lines is by using Python's implied line continuation inside parentheses, brackets and braces. Long lines can be broken over multiple lines by wrapping expressions in parentheses. These should be used in preference to using a backslash for line continuation.

importlib_metadata is a library which provides an API for accessing an installed Python package's metadata, such as its entry points or its top-level name. This functionality intends to replace most uses of pkg_resources entry point API and metadata API. Along with importlib.resources in Python 3.7 and newer, this can eliminate the need to use the older and less efficient pkg_resources package.

pytest-random-order is a Pytest plugin that randomizes the order of tests. This can be useful to detect a test that passes just because it happens to run after an unrelated test that leaves the system in a favourable state. The plugin allows user to control the level of randomness they want to introduce and to disable reordering on subsets of tests. Tests can be rerun in a specific order by passing a seed value reported in a previous test run.

TerminalTextEffects (TTE) is a terminal visual effects engine. It can be installed as a system application to produce effects in your terminal, or as a Python library to enable effects within your Python scripts/applications. It also includes a growing library of built-in effects which showcase the engine's features, including complex character movement via Paths, Waypoints, and motion easing, with support for quadratic/cubic bezier curves, complex animations via Scenes with symbol/color changes, layers, easing, and Path synced progression, and variable stop/step color gradient generation. Runs inline, preserving terminal state and workflow.

PyEGA3 is a tool for viewing and downloading files from authorized EGA datasets. It uses the EGA data API and has several key features:

• Files are transferred over secure https connections and received unencrypted, so no need for decryption after download.

• Downloads resume from where they left off in the event that the connection is interrupted.

• Supports file segmenting and parallelized download of segments, improving overall performance.

• After download completes, file integrity is verified using checksums.

• Implements the GA4GH-compliant htsget protocol for download of genomic ranges for data files with accompanying index files.

This package provides a Python library intended for use in automated tests. One difficulty when testing software is that the code under test might need to read or write to files in the local file system. If the file system is not set up in just the right way, it might cause a spurious error during the test. The pyfakefs library provides a solution to problems like this by mocking file system interactions. In other words, it arranges for the code under test to interact with a fake file system instead of the real file system. The code under test requires no modification to work with pyfakefs.

The goal of pathlib2 is to provide a backport of standard pathlib module which tracks the standard library module, so all the newest features of the standard pathlib can be used also on older Python versions.

Pathlib offers a set of classes to handle file system paths. It offers the following advantages over using string objects:

1. No more cumbersome use of os and os.path functions. Everything can be done easily through operators, attribute accesses, and method calls.

2. Embodies the semantics of different path types. For example, comparing Windows paths ignores casing.

3. Well-defined semantics, eliminating any inconsistencies or ambiguities (forward vs. backward slashes, etc.).

Browser resources implementation for Zope.

Software Heritage Mercurial Loader

Vanilla HTML components for Dash.

Core component suite for Dash

Core component suite for Dash.

Vanilla HTML components for Dash.

Check your wheels have the right contents.

This package contains test vectors for the cryptography package.

Pabot is a parallel executor for Robot Framework tests.

Interactive visualization method for ancestral recombination graphs.

Poetry plugin to export the dependencies to various formats.

This package provides a Google Authentication Library plugin with oauthlib.

sphinxcontrib-qthelp is a Sphinx extension which outputs QtHelp documents.