An interactive computing environment for Python
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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