Metadata-Version: 1.1
Name: ipython
Version: 2.3.1
Summary: IPython: Productive Interactive Computing
Home-page: http://ipython.org
Author: The IPython Development Team
Author-email: ipython-dev@scipy.org
License: BSD
Download-URL: https://github.com/ipython/ipython/downloads
Description: 
        IPython provides a rich toolkit to help you make the most out of using Python
        interactively.  Its main components are:
        
        * Powerful interactive Python shells (terminal- and Qt-based).
        * A web-based interactive notebook environment with all shell features plus
          support for embedded figures, animations and rich media.
        * Support for interactive data visualization and use of GUI toolkits.
        * Flexible, embeddable interpreters to load into your own projects.
        * A high-performance library for high level and interactive parallel computing
          that works in multicore systems, clusters, supercomputing and cloud scenarios.
        
        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 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 <http://github.com/ipython>`_.
        
Keywords: Interactive,Interpreter,Shell,Parallel,Distributed,Web-based computing,Qt console,Embedding
Platform: Linux
Platform: Mac OSX
Platform: Windows XP/Vista/7/8
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: System :: Distributed Computing
Classifier: Topic :: System :: Shells
