A client library for executing notebooks.
NBClient, a client library for programmatic notebook execution, is a tool for running Jupyter Notebooks in different execution contexts. NBClient was spun out of nbconvert (formerly ExecutePreprocessor). NBClient lets you execute notebooks.
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IPython: Productive Interactive Computing
IPython provides a rich toolkit to help you make the most out of using Python interactively. Its main components are: * A powerful interactive Python shell * A `Jupyter <https://jupyter.org/>`_ kernel to work with Python code in Jupyter notebooks and other interactive frontends. The enhanced interactive Python shells have the following main features: * Comprehensive object introspection. * Input history, persistent across sessions. * Caching of output results during a session with automatically generated references. * Extensible tab completion, with support by default for completion of python variables and keywords, filenames and function keywords. * Extensible system of 'magic' commands for controlling the environment and performing many tasks related either to IPython or the operating system. * A rich configuration system with easy switching between different setups (simpler than changing $PYTHONSTARTUP environment variables every time). * Session logging and reloading. * Extensible syntax processing for special purpose situations. * Access to the system shell with user-extensible alias system. * Easily embeddable in other Python programs and GUIs. * Integrated access to the pdb debugger and the Python profiler. The latest development version is always available from IPython's `GitHub site <http://github.com/ipython>`_.
A collection of tools for working with Jupyter Notebooks in Sphinx.
importlib_metadata is a library which provides an API for accessing an installed package’s metadata (see PEP 566), such as its entry points or its top-level name.
YAML is a data serialization format designed for human readability and interaction with scripting languages. PyYAML is a YAML parser and emitter for Python. PyYAML features a complete YAML 1.1 parser, Unicode support, pickle support, capable extension API, and sensible error messages. PyYAML supports standard YAML tags and provides Python-specific tags that allow to represent an arbitrary Python object. PyYAML is applicable for a broad range of tasks from complex configuration files to object serialization and persistence.
A rich and extensible flavor of Markdown meant for technical documentation and publishing.
MyST is a flavor of markdown that is designed for simplicity, flexibility, and extensibility. This repository serves as the reference implementation of MyST Markdown, as well as a collection of tools to support working with MyST in Python and Sphinx. It contains an extended CommonMark-compliant parser using markdown-it-py, as well as a Sphinx extension that allows you to write MyST Markdown in Sphinx.
This package provides the IPython kernel for Jupyter.
This package contains the base implementation of the Jupyter Notebook format, and Python APIs for working with notebooks.
Sphinx is a tool that makes it easy to create intelligent and beautiful documentation for Python projects (or other documents consisting of multiple reStructuredText sources), written by Georg Brandl. It was originally created to translate the new Python documentation, but has now been cleaned up in the hope that it will be useful to many other projects. Sphinx uses reStructuredText as its markup language, and many of its strengths come from the power and straightforwardness of reStructuredText and its parsing and translating suite, the Docutils. Although it is still under constant development, the following features are already present, work fine and can be seen "in action" in the Python docs: * Output formats: HTML (including Windows HTML Help) and LaTeX, for printable PDF versions * Extensive cross-references: semantic markup and automatic links for functions, classes, glossary terms and similar pieces of information * Hierarchical structure: easy definition of a document tree, with automatic links to siblings, parents and children * Automatic indices: general index as well as a module index * Code handling: automatic highlighting using the Pygments highlighter * Various extensions are available, e.g. for automatic testing of snippets and inclusion of appropriately formatted docstrings.
Interpreter of the Python3 programming language
Python combines remarkable power with very clear syntax. It has modules, classes, exceptions, very high level dynamic data types, and dynamic typing. There are interfaces to many system calls and libraries, as well as to various windowing systems. New built-in modules are easily written in C or C++ (or other languages, depending on the chosen implementation). Python is also usable as an extension language for applications written in other languages that need easy-to-use scripting or automation interfaces. This package Provides python version 3.
Backported and Experimental Type Hints for Python 3.5+
Typing Extensions -Backported and Experimental Type Hints for Python.
Easily build and distribute Python 3 packages
Setuptools is a collection of enhancements to the Python 3 distutils that allow you to more easily build and distribute Python 3 packages, especially ones that have dependencies on other packages. This package also contains the runtime components of setuptools, necessary to execute the software that requires pkg_resources.py.
py.test plugin that allows you to add environment variables.