The flufl.bounce library provides a set of heuristics and an API for detecting the original bouncing email addresses from a bounce message. Many formats found in the wild are supported, as are VERP and RFC 3464.

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.

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.

GraphQL implementation for Python. GraphQL is a data query language and runtime designed and used to request and deliver data to mobile and web apps. This library is a port of graphql-js to Python.

This module is primarily a backport of the Python 3.2 contextlib to earlier Python versions. Like contextlib, it provides utilities for common tasks involving decorators and context managers. It also contains additional features that are not part of the standard library.

The EditorConfig project consists of a file format for defining coding styles and a collection of text editor plugins that enable editors to read the file format and adhere to defined styles. EditorConfig files are easily readable and they work nicely with version control systems.

This package provides a mutable, self-balancing interval tree implementation for Python. Queries may be by point, by range overlap, or by range envelopment. This library was designed to allow tagging text and time intervals, where the intervals include the lower bound but not the upper bound.

This inspector is meant as a companion to the PyNWB validator, which checks for strict schema compliance. This tool attempts to apply some common sense to find components of the file that are technically compliant, but possibly incorrect, suboptimal in their representation, or deviate from best practices.

launchpadlib is an open-source Python library that lets you treat the HTTP resources published by Launchpad's web service as Python objects responding to a standard set of commands. With launchpadlib you can integrate your applications into Launchpad without knowing a lot about HTTP client programming.

cryptography is a package which provides cryptographic recipes and primitives to Python developers. It aims to be the “cryptographic standard library” for Python. The package includes both high level recipes, and low level interfaces to common cryptographic algorithms such as symmetric ciphers, message digests and key derivation functions.

When writing applications, finding the right location to store user data and configuration varies per platform. Even for single-platform apps, there may by plenty of nuances in figuring out the right location. This small Python module determines the appropriate platform-specific directories, e.g. the ``user data dir''.

Keyrings in this package may have security risks or other implications. These backends were extracted from the main keyring project to make them available for those who wish to employ them, but are discouraged for general production use. Include this module and use its backends at your own risk.

Scikit-build is an improved build system generator for CPython C/C++/Fortran/Cython extensions. It has support for additional compilers, build systems, cross compilation, and locating dependencies and determining their build requirements. The scikit-build package is fundamentally just glue between the setuptools Python module and CMake.

This package provides a full Python driver for the Keithley 2600B series of source measurement units. This driver provides access to base commands and higher level functions such as IV measurements, transfer and output curves, etc. Base commands replicate the functionality and syntax from the Keithley's internal TSP Lua functions.

TorchMetrics is a collection of 100+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. It offers:

• A standardized interface to increase reproducibility

• Reduces boilerplate

• Automatic accumulation over batches

• Metrics optimized for distributed-training

• Automatic synchronization between multiple devices

This package provides mock helpers for SQLAlchemy that makes it easy to mock an SQLAlchemy session while preserving the ability to do asserts.

Normally Normally SQLAlchemy's expressions cannot be easily compared as comparison on binary expression produces yet another binary expression, but this library provides functions to facilitate such comparisons.

Tortoise ORM is an easy-to-use asyncio ORM (Object Relational Mapper) inspired by Django. Tortoise ORM was built with relations in mind and admiration for the excellent and popular Django ORM. It's engraved in its design that you are working not with just tables, you work with relational data.

This package provides a fast implementation of the HTML5 parsing spec for Python. Parsing is done in C using a variant of the gumbo parser. The gumbo parse tree is then transformed into an lxml tree, also in C, yielding parse times that can be a thirtieth of the html5lib parse times.

Tortoise ORM is an easy-to-use asyncio ORM (Object Relational Mapper) inspired by Django. Tortoise ORM was built with relations in mind and admiration for the excellent and popular Django ORM. It's engraved in its design that you are working not with just tables, you work with relational data.

Tortoise ORM is an easy-to-use asyncio ORM (Object Relational Mapper) inspired by Django. Tortoise ORM was built with relations in mind and admiration for the excellent and popular Django ORM. It's engraved in its design that you are working not with just tables, you work with relational data.

Tortoise ORM is an easy-to-use asyncio ORM (Object Relational Mapper) inspired by Django. Tortoise ORM was built with relations in mind and admiration for the excellent and popular Django ORM. It's engraved in its design that you are working not with just tables, you work with relational data.

This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpropagation through ODE solutions is supported using the adjoint method for constant memory cost. For usage of ODE solvers in deep learning applications.

As the solvers are implemented in PyTorch, algorithms in this repository are fully supported to run on the GPU.

Astro-SCRAPPY is designed to detect cosmic rays in images (numpy arrays), based on Pieter van Dokkum's L.A.Cosmic algorithm. Much of this was originally adapted from cosmics.py written by Malte Tewes. This is designed to be as fast as possible so some of the readability has been sacrificed, specifically in the C code.

This package provides a drop-in replacement for the original LooseVersion. It implements an identical interface and comparison logic to LooseVersion. The only major change is that a looseversion.LooseVersion is comparable to a distutils.version.LooseVersion, which means tools should not need to worry whether all dependencies that use LooseVersion have migrated.