Queuelib is a Python library that implements object collections which are stored in memory or persisted to disk, provide a simple API, and run fast.

Queuelib provides collections for queues (FIFO), stacks (LIFO), queues sorted by priority and queues that are emptied in a round-robin fashion.

autoflake removes unused imports and unused variables from Python code as reported by pyflakes.

By default, it only removes unused imports for modules that are part of the standard library. Removal of unused variables is also disabled by default. It also removes useless pass statements.

Retrieve a scale based on a given mode and starting note. Information about these scales can be found on Wikipedia.

This package defines a variety of Pygments lexers for highlighting IPython code.

This package provides a text progress bar library for Python. This version only differs from the original progressbar package in that it uses relative package imports instead of absolute imports, which is necessary for the module to work under Python 3.3.

This package provides a utility to find Python versions on the current system.

phply is a parser for the PHP programming language written using PLY,a Lex/YACC-style parser generator toolkit for Python.

This package provides a library for accessing stubs in typeshed.

This package provides a Python library to parse, manipulate or create documents in LilyPond format. A command line program ly is also provided that can be used to do various manipulations with LilyPond files.

Python one-time password library for HMAC-based (HOTP) and time-based (TOTP) passwords.

This package provides a read-only implementation of fsspec for IPFS.

This package provides Python interface to the OpenJPEG library which allows one to read and write JPEG 2000 files

Babel is composed of two major parts: - tools to build and work with gettext message catalogs - a Python interface to the CLDR (Common Locale Data Repository), providing access to various locale display names, localized number and date formatting, etc.

This software allows you to verify wheel filenames and parse them into their component fields.

This package adheres strictly to the standard, with the following exceptions:

• Version components may be any sequence of the relevant set of characters; they are not verified for PEP 440 compliance.

• The .whl file extension is matched case-insensitively.

MicroPython is a lean and efficient implementation of the Python 3 programming language that includes a small subset of the Python standard library and is optimised to run on microcontrollers and in constrained environments. MicroPython is packed full of advanced features such as an interactive prompt, arbitrary precision integers, closures, list comprehension, generators, exception handling and more. Still it is compact enough to fit and run within just 256k of code space and 16k of RAM. MicroPython aims to be as compatible with normal Python as possible to allow you to transfer code with ease from the desktop to a microcontroller or embedded system.

This variant of Python provides an interpreter built with --with-pydebug to help develop and debug extensions. See https://pythonextensionpatterns.readthedocs.io/en/latest/debugging/debug.html, for more information.

Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.

Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.

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.

Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.

Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.

Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.

Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.

The pythoncapi-compat project can be used to write a C or C++ extension supporting a wide range of Python versions with a single code base, via the pythoncapi_compat.h header file.