setup.py

#!/usr/bin/env python
# vim: set fileencoding=utf-8 :
# Andre Anjos <andre.anjos@idiap.ch>
# Mon 16 Apr 08:18:08 2012 CEST
#
# Copyright (C) Idiap Research Institute, Martigny, Switzerland
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, version 3 of the License.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.

# This file contains the python (distutils/setuptools) instructions so your
# package can be installed on **any** host system. It defines some basic
# information like the package name for instance, or its homepage.
#
# It also defines which other packages this python package depends on and that
# are required for this package's operation. The python subsystem will make
# sure all dependent packages are installed or will install them for you upon
# the installation of this package.
#
# The 'buildout' system we use here will go further and wrap this package in
# such a way to create an isolated python working environment. Buildout will
# make sure that dependencies which are not yet installed do get installed, but
# **without** requiring administrative privileges on the host system. This
# allows you to test your package with new python dependencies w/o requiring
# administrative interventions.

from setuptools import setup

# The only thing we do in this file is to call the setup() function with all
# parameters that define our package.
setup(

    # This is the basic information about your project. Modify all this
    # information before releasing code publicly.
    name = 'tensorflow.examples',
    version = open("version.txt").read().rstrip(),
    description = 'Hands on with tensor flow',

    url = 'https://www.github.com/tiagofrepereira2012/tensorflow.examples',
    license = 'BSD',
    author = 'Tiago de Freitas Pereira',
    author_email = 'tiago.pereira@idiap.ch',
    keywords = 'tensorflow',

    # If you have a better, long description of your package, place it on the
    # 'doc' directory and then hook it here
    long_description = open('README.rst').read(),

    # This line is required for any distutils based packaging.
    include_package_data = True,

    # This line defines which packages should be installed when you "install"
    # this package. All packages that are mentioned here, but are not installed
    # on the current system will be installed locally and only visible to the
    # scripts of this package. Don't worry - You won't need administrative
    # privileges when using buildout.
    install_requires = [
        'setuptools',
        'docopt',
        'ipython',
        'bob.db.mnist',
        'tfdebugger'
    ],

    entry_points = {

      # scripts should be declared using this entry:
      'console_scripts': [
        'train_mnist.py        = examples.tensorflow.script.train_mnist:main',
        'train_mnist_siamese.py = examples.tensorflow.script.train_mnist_siamese:main',
        'train_mnist_triplet.py = examples.tensorflow.script.train_mnist_triplet:main',
      ],


   },

    # Classifiers are important if you plan to distribute this package through
    # PyPI. You can find the complete list of classifiers that are valid and
    # useful here (http://pypi.python.org/pypi?%3Aaction=list_classifiers).
    classifiers = [
      'Framework :: Tensorflow',
      'Development Status :: 3 - Alpha',
      'Intended Audience :: Developers',
      'License :: OSI Approved ::  BSD License',
      'Natural Language :: English',
      'Programming Language :: Python',
      'Topic :: Scientific/Engineering :: Artificial Intelligence',
    ],
)