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.
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.
q is a Python module for "print" style of debugging Python code. It provides convenient short API for print out of values, tracebacks, and falling into the Python interpreter.
This package provides a replacement for Python's subprocess feature.
This package provides a replacement for Python's subprocess feature.
This package provides a tool for generating OIDC, OpenID Connect identities.
This package provides a Python bindings for H3, a hierarchical hexagonal geospatial indexing system
This package provides a Python bindings for H3, a hierarchical hexagonal geospatial indexing system
Py is a Python library for file name parsing, .ini file parsing, I/O, code introspection, and logging.
The ld package provides information about the GNU/Linux distribution it runs on, such as a reliable machine-readable ID, or version information.
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.
RQ (Redis Queue) is a simple Python library for queueing jobs and processing them in the background with workers. It is backed by Redis and it is designed to have a low barrier to entry.
This package provides yq and xq for processing YAML and XML respectively. The processing is done through jq, jq filters can be used to process the data as it passes through.
Hy is a dialect of Lisp that's embedded in Python. Since Hy transforms its Lisp code into the Python Abstract Syntax Tree, you have the whole world of Python at your fingertips, in Lisp form.
This package provides a structured, variable-resolution meshes, unstructured meshes, and discrete or sampled data such as particles. Focused on driving physically-meaningful inquiry, it has been applied in domains such as astrophysics, seismology, nuclear engineering, molecular dynamics, and oceanography.
PyFilesystem's FS object is a file system abstraction sharing similarities with Python's own file object for single files. It allows opening all the files under a given directory recursively, as a single FS object. This enables, for example, counting the combined number of lines in the contained files easily.
This module contains a pure-Python implementation of a HTTP/2 protocol stack. It does not provide a parsing layer, a network layer, or any rules about concurrency. Instead, it's a purely in-memory solution, defined in terms of data actions and HTTP/2 frames. This is one building block of a full Python HTTP implementation.
PyAV is a Python library that allows for direct and precise manipulation of media through containers, streams, packets, codecs, and frames. It provides access to the powerful FFmpeg libraries while managing the complex details as much as possible. PyAV also facilitates data transformation and integration with other packages such as Numpy and Pillow. However, working with media is a challenging task and PyAV cannot abstract it away or make all the best decisions for you. If you can accomplish your tasks with the ffmpeg command, PyAV may not be necessary. Nonetheless, PyAV is an essential tool when working with media that requires its specific capabilities.
Flexible test automation.