##// END OF EJS Templates
don't import numpy in pickleutil until it is used...
don't import numpy in pickleutil until it is used can affect startup time, memory usage, etc. as seen in #4199

File last commit:

r12474:e128d4eb
r12541:68af896f
Show More
release.py
148 lines | 5.3 KiB | text/x-python | PythonLexer
# -*- coding: utf-8 -*-
"""Release data for the IPython project."""
#-----------------------------------------------------------------------------
# Copyright (c) 2008, IPython Development Team.
# Copyright (c) 2001, Fernando Perez <fernando.perez@colorado.edu>
# Copyright (c) 2001, Janko Hauser <jhauser@zscout.de>
# Copyright (c) 2001, Nathaniel Gray <n8gray@caltech.edu>
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
#-----------------------------------------------------------------------------
# Name of the package for release purposes. This is the name which labels
# the tarballs and RPMs made by distutils, so it's best to lowercase it.
name = 'ipython'
# IPython version information. An empty _version_extra corresponds to a full
# release. 'dev' as a _version_extra string means this is a development
# version
_version_major = 2
_version_minor = 0
_version_patch = 0
_version_extra = 'dev'
# _version_extra = 'rc1'
# _version_extra = '' # Uncomment this for full releases
codename = 'An Afternoon Hack'
# Construct full version string from these.
_ver = [_version_major, _version_minor, _version_patch]
__version__ = '.'.join(map(str, _ver))
if _version_extra:
__version__ = __version__ + '-' + _version_extra
version = __version__ # backwards compatibility name
version_info = (_version_major, _version_minor, _version_patch, _version_extra)
# Change this when incrementing the kernel protocol version
kernel_protocol_version_info = (4, 0)
description = "IPython: Productive Interactive Computing"
long_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>`_.
"""
license = 'BSD'
authors = {'Fernando' : ('Fernando Perez','fperez.net@gmail.com'),
'Janko' : ('Janko Hauser','jhauser@zscout.de'),
'Nathan' : ('Nathaniel Gray','n8gray@caltech.edu'),
'Ville' : ('Ville Vainio','vivainio@gmail.com'),
'Brian' : ('Brian E Granger', 'ellisonbg@gmail.com'),
'Min' : ('Min Ragan-Kelley', 'benjaminrk@gmail.com'),
'Thomas' : ('Thomas A. Kluyver', 'takowl@gmail.com'),
'Jorgen' : ('Jorgen Stenarson', 'jorgen.stenarson@bostream.nu'),
'Matthias' : ('Matthias Bussonnier', 'bussonniermatthias@gmail.com'),
}
author = 'The IPython Development Team'
author_email = 'ipython-dev@scipy.org'
url = 'http://ipython.org'
download_url = 'https://github.com/ipython/ipython/downloads'
platforms = ['Linux','Mac OSX','Windows XP/Vista/7/8']
keywords = ['Interactive','Interpreter','Shell','Parallel','Distributed',
'Web-based computing', 'Qt console', 'Embedding']
classifiers = [
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: BSD License',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Topic :: System :: Distributed Computing',
'Topic :: System :: Shells'
]