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>`_.
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Interactive HTML widgets for Jupyter notebooks and the IPython kernel.
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.
The nbconvert tool, jupyter nbconvert, converts notebooks to various other formats via Jinja templates. The nbconvert tool allows you to convert an .ipynb notebook file into various static formats including HTML, LaTeX, PDF, Reveal JS, Markdown (md), ReStructured Text (rst) and executable script.