Xvfb (X virtual framebuffer) is a display server implementing the X11 display server protocol. It runs in memory and does not require a physical display. Only a network layer is necessary. Xvfb is useful for running acceptance tests on headless servers.

This middleware provides cross-origin resource sharing (CORS) support for Falcon. It allows applying a specially crafted CORS object to the incoming requests, enabling the ability to serve resources over a different origin than that of the web application.

MySQLdb is an interface to the popular MySQL database server for Python. The design goals are:

1. Compliance with Python database API version 2.0 [PEP-0249],

2. Thread-safety,

3. Thread-friendliness (threads will not block each other).

Argon2 is a secure password hashing algorithm. It is designed to have both a configurable runtime as well as memory consumption. This means that you can decide how long it takes to hash a password and how much memory is required.

argcomplete provides extensible command line tab completion of arguments and options for Python scripts using argparse. It's particularly useful for programs with many options or sub-parsers that can dynamically suggest completions ; for example, when browsing resources over the network.

ipyparallel is a Python package and collection of CLI scripts for controlling clusters for Jupyter. ipyparallel contains the following CLI scripts:

1. ipcluster - start/stop a cluster

2. ipcontroller - start a scheduler

3. ipengine - start an engine

Citeproc-py is a CSL processor for Python. It aims to implement the CSL 1.0.1 specification. citeproc-py can output styled citations and bibliographies in a number of different output formats. Currently supported are plain text, reStructuredText and HTML.

This tool helps to install Rust into a temporary directory, allowing support of Rust-based Python builds. Cargo and rustc are installed into a cache directory, to avoid modifying the host's environment, and further activated using a set of environment variables.

This package provides a Python library to perform a 3-way merge between strings, based on diff-match-patch. This library performs merges at a character level, as opposed to most VCS systems, which opt for a line-based approach.

NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities.

Pygame-menu is a python-pygame library for creating menus and GUIs. It supports several widgets, such as buttons, color inputs, clock objects, drop selectors, frames, images, labels, selectors, tables, text inputs, color switches, and many more, with multiple options to customize.

The poetry-core module provides a PEP 517 build back-end implementation developed for Poetry. This project is intended to be a light weight, fully compliant, self-contained package allowing PEP 517 compatible build front-ends to build Poetry managed projects.

A library designed to represent tabular data in visually appealing ASCII tables. PrettyTable allows for selection of which columns are to be printed, independent alignment of columns (left or right justified or centred) and printing of sub-tables by specifying a row range.

This package includes WrapSpawner and ProfilesSpawner, which provide mechanisms for runtime configuration of spawners. The inspiration for their development was to allow users to select from a range of pre-defined batch job profiles, but their operation is completely generic.

Lexicon provides a way to manipulate DNS records on multiple DNS providers in a standardized way. It has a CLI but it can also be used as a Python library. It was designed to be used in automation, specifically with Let's Encrypt.

This is a Python library for the generation of email authentication headers. The library can perform DKIM, SPF, and DMARC validation, and the results are packaged into the Authentication-Results header. The library can DKIM and ARC sign messages and output the corresponding signature headers.

This Python library is a wrapper around tokenize from the Python standard library. It provides two additional tokens ESCAPED_NL and UNIMPORTANT_WS, and a Token data type. Use src_to_tokens and tokens_to_src to roundtrip.

Cloudpickle makes it possible to serialize Python constructs not supported by the default pickle module from the Python standard library. It is especially useful for cluster computing where Python expressions are shipped over the network to execute on remote hosts, possibly close to the data.

FFCx is a compiler for finite element variational forms. From a high-level description of the form in the Unified Form Language (UFL), it generates efficient low-level C code that can be used to assemble the corresponding discrete operator (tensor).

Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, the python and ipython shell, web application servers, and six graphical user interface toolkits.

pandarallel allows any Pandas user to take advantage of their multi-core computer, while Pandas uses only one core. pandarallel also offers nice progress bars (available on Notebook and terminal) to get an rough idea of the remaining amount of computation to be done.

The Levenshtein Python C extension module contains functions for fast computation of

1. Levenshtein (edit) distance, and edit operations

2. string similarity

3. approximate median strings, and generally string averaging

4. string sequence and set similarity

It supports both normal and Unicode strings.

fastparquet is a Python implementation of the Parquet file format. fastparquet is used implicitly by dask, pandas and intake-parquet. It supports the following compression algorithms:

• Gzip

• Snappy

• Brotli

• LZ4

• Zstd

• LZO (optionally)

CTranslate2 is a C++ and Python library for efficient inference with Transformer models.

The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU.