This package aims to simplify working with genomic region / interval data by providing a common interface that lets you access a wide selection of file types and formats for handling genomic region data---all using the same syntax.

Sanic is a Python web server and web framework that's written to go fast. It allows the usage of the async/await syntax added in Python 3.5, which makes your code non-blocking and speedy.

Readme Renderer is a library that will safely render arbitrary README files into HTML. It is designed to be used in Warehouse to render the long_description for packages. It can handle Markdown, reStructuredText, and plain text.

This package contains a collection of plugins for markdown-it-py like:

1. amsmath,

2. attrs,

3. container,

4. definition list,

5. dollarmath,

6. field list,

7. footnote,

8. textmath, and

9. wordcount.

Xapian is a highly adaptable toolkit which allows developers to easily add advanced indexing and search facilities to their own applications. It supports the Probabilistic Information Retrieval model and also supports a rich set of boolean query operators.

Python library and command line tool for configuring a YubiKey. Note that after installing this package, you might still need to add appropriate udev rules to your system configuration to be able to configure the YubiKey as an unprivileged user.

The aim of this package is to unify the plethora of existing packages integrating SQLAlchemy with Zope's transaction management. As such,it only provides a data manager and makes no attempt to define a zopeish way to configure engines.

This package provides Python bindings for the freecell-solver package. Freecell Solver is a program that automatically solves layouts of Freecell and similar variants of Card Solitaire such as Eight Off, Forecell, and Seahaven Towers, as well as Simple Simon boards.

The casa-formats-io package is a small package which implements functionality to read data stored in CASA formats (such as .image datasets). This implementation is independent of and does not use casacore.

Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims to be accessible and easy to use in many contexts.

This package provides a Cleaner for cleaning up HTML pages. It supports removing embedded or script content, special tags and CSS style annotations among other features. Its main purpose is removing superfluous content, it is not appropriate for security sensitive environments.

This package provides an MkDocs extension that lists all dependencies according to a mkdocs.yml file. This command guesses the Python dependencies that a MkDocs site requires in order to build. It simply prints the PyPI packages that need to be installed.

This Python package is designed to simplify the process of creating Python executables compatible with LaTeX restricted shell escape. Restricted shell escape allows LaTeX to run trusted executables as part of compiling documents. These executables have restricted access to the file system and restricted ability to launch subprocesses.

Anndata is a package for simple (functional) high-level APIs for data analysis pipelines. In this context, it provides an efficient, scalable way of keeping track of data together with learned annotations and reduces the code overhead typically encountered when using a mostly object-oriented library such as scikit-learn.

Beautiful Soup is a Python library designed for rapidly setting up screen-scraping projects. It offers Pythonic idioms for navigating, searching, and modifying a parse tree, providing a toolkit for dissecting a document and extracting what you need. It automatically converts incoming documents to Unicode and outgoing documents to UTF-8.

This package provides metadata objects which can be used to represent common constraints such as upper and lower bounds on scalar values and collection sizes, a Predicate marker for runtime checks, and descriptions of how we intend these metadata to be interpreted. In some cases, we also note alternative representations which do not require this package.

The rpy2 package is a namespace package. This is the part of that package that covers the "low-level" interface to R used in rpy2. This provides mappings to access R's C-API and utilities to do so safely. It is otherwise relatively easily to crash (segfault) a process by calling R's C-API.

This simple Django utility allows you to utilize the 12factor inspired DATABASE_URL environment variable to configure your Django application.

The dj_database_url.config method returns a Django database connection dictionary, populated with all the data specified in your URL. There is also a conn_max_age argument to easily enable Django’s connection pool.

SocksiPy - A Python SOCKS client module. It provides a socket-like interface that supports connections to any TCP service through the use of a SOCKS4, SOCKS5 or HTTP proxy. The original version was developed by Dan Haim, this is a branch created by Mario Vilas to address some open issues,as the original project seems to have been abandoned circa 2007.

A simple python package for fitting L2- and smoothing-penalized generalized linear models. Built primarily because the statsmodels GLM fit_regularized method is built to do elastic net (combination of L1 and L2 penalities), but if you just want to do an L2 or a smoothing penalty (like in generalized additive models), using a penalized iteratively reweighted least squares (p-IRLS) is much faster.

Pytest-examples provides functionality for testing Python code examples in docstrings and markdown files, with its main features being:

• lint code examples using ruff and black

• run code examples

• run code examples and check print statements are inlined correctly in the code

• It can also update code examples in place to format them and insert or update print statements

This package provides a reference implementation of SLIP-0039: Shamir's Secret-Sharing for Mnemonic Codes. This SLIP describes a standard and interoperable implementation of Shamir's secret sharing (SSS). SSS splits a secret into unique parts which can be distributed among participants, and requires a specified minimum number of parts to be supplied in order to reconstruct the original secret. Knowledge of fewer than the required number of parts does not leak information about the secret.

This package provides a Python library for building and analyzing recommender systems that deal with explicit rating data. It was designed with the following purposes in mind:

• Provide tools to handle downloaded or user-provided datasets.

• Provide ready-to-use prediction algorithms and similarity measures.

• Provide a base for creating custom algorithms.

• Provide tools to evaluate, analyse and compare algorithm performance.

• Provide documentation with precise details regarding library algorithms.

This package provides wrappers for the commands of Python 3.x such that they can also be invoked under their usual names---e.g., python instead of python3 or pip instead of pip3.

To function properly, this package should not be installed together with the python package: this package uses the python package as a propagated input, so installing this package already makes both the versioned and the unversioned commands available.