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An interactive computing environment for Python

Project description

The goal of IPython is to create a comprehensive environment for interactive and exploratory computing. To support this goal, IPython has two main components:

  • An enhanced interactive Python shell.
  • An architecture for interactive parallel computing.

The enhanced interactive Python shell has the following main features:

  • Comprehensive object introspection.
  • Input history, persistent across sessions.
  • Caching of output results during a session with automatically generated references.
  • Readline based name completion.
  • Extensible system of ‘magic’ commands for controlling the environment and performing many tasks related either to IPython or the operating system.
  • 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 wxPython GUIs.
  • Integrated access to the pdb debugger and the Python profiler.

The parallel computing architecture has the following main features:

  • Quickly parallelize Python code from an interactive Python/IPython session.
  • A flexible and dynamic process model that be deployed on anything from multicore workstations to supercomputers.
  • An architecture that supports many different styles of parallelism, from message passing to task farming.
  • Both blocking and fully asynchronous interfaces.
  • High level APIs that enable many things to be parallelized in a few lines of code.
  • Share live parallel jobs with other users securely.
  • Dynamically load balanced task farming system.
  • Robust error handling in parallel code.

The latest development version is always available from IPython’s GitHub site.

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