<commit_before> #!/usr/bin/env python
import os
import re
import sys
import warnings

from setuptools import setup, find_packages

MAJOR = 0
MINOR = 5
MICRO = 1
ISRELEASED = False
VERSION = '%d.%d.%d' % (MAJOR, MINOR, MICRO)
QUALIFIER = ''


DISTNAME = 'xray'
LICENSE = 'Apache'
AUTHOR = '<NAME>'
AUTHOR_EMAIL = '<EMAIL>'
URL = 'https://github.com/xray/xray'
CLASSIFIERS = [
    'Development Status :: 4 - Beta',
    'License :: OSI Approved :: Apache Software License',
    'Operating System :: OS Independent',
    'Intended Audience :: Science/Research',
    'Programming Language :: Python',
    'Programming Language :: Python :: 2',
    'Programming Language :: Python :: 2.6',
    'Programming Language :: Python :: 2.7',
    'Programming Language :: Python :: 3',
    'Programming Language :: Python :: 3.3',
    'Programming Language :: Python :: 3.4',
    'Topic :: Scientific/Engineering',
]

INSTALL_REQUIRES = ['numpy >= 1.7', 'pandas >= 0.15.0']
TESTS_REQUIRE = ['nose >= 1.0']

if sys.version_info[:2] < (2, 7):
    TESTS_REQUIRE += ["unittest2 == 0.5.1"]

DESCRIPTION = "N-D labeled arrays and datasets in Python"
LONG_DESCRIPTION = """
**xray** is an open source project and Python package that aims to bring the
labeled data power of pandas_ to the physical sciences, by providing
N-dimensional variants of the core pandas data structures.

Our goal is to provide a pandas-like and pandas-compatible toolkit for
analytics on multi-dimensional arrays, rather than the tabular data for which
pandas excels. Our approach adopts the `Common Data Model`_ for self-
describing scientific data in widespread use in the Earth sciences:
``xray.Dataset`` is an in-memory representation of a netCDF file.

.. _pandas: http://pandas.pydata.org
.. _Common Data Model: http://www.unidata.ucar.edu/software/thredds/current/netcdf-java/CDM
.. _netCDF: http://www.unidata.ucar.edu/software/netcdf
.. _OPeNDAP: http://www.opendap.org/

Important links
---------------

- HTML documentation: http://xray.readthedocs.org
- Issue tracker: http://github.com/xray/xray/issues
- Source code: http://github.com/xray/xray
- PyData talk: https://www.youtube.com/watch?v=T5CZyNwBa9c
"""

# code to extract and write the version copied from pandas
FULLVERSION = VERSION
write_version = True

if not ISRELEASED:
    import subprocess
    FULLVERSION += '.dev'

    pipe = None
    for cmd in ['git', 'git.cmd']:
        try:
            pipe = subprocess.Popen(
                [cmd, "describe", "--always", "--match", "v[0-9]*"],
                stdout=subprocess.PIPE)
            (so, serr) = pipe.communicate()
            if pipe.returncode == 0:
                break
        except:
            pass
<commit_msg>update setup.py youtube link to scipy2015<commit_after> #!/usr/bin/env python
import os
import re
import sys
import warnings

from setuptools import setup, find_packages

MAJOR = 0
MINOR = 5
MICRO = 1
ISRELEASED = False
VERSION = '%d.%d.%d' % (MAJOR, MINOR, MICRO)
QUALIFIER = ''


DISTNAME = 'xray'
LICENSE = 'Apache'
AUTHOR = 'xray Developers'
AUTHOR_EMAIL = '<EMAIL>'
URL = 'https://github.com/xray/xray'
CLASSIFIERS = [
    'Development Status :: 4 - Beta',
    'License :: OSI Approved :: Apache Software License',
    'Operating System :: OS Independent',
    'Intended Audience :: Science/Research',
    'Programming Language :: Python',
    'Programming Language :: Python :: 2',
    'Programming Language :: Python :: 2.6',
    'Programming Language :: Python :: 2.7',
    'Programming Language :: Python :: 3',
    'Programming Language :: Python :: 3.3',
    'Programming Language :: Python :: 3.4',
    'Topic :: Scientific/Engineering',
]

INSTALL_REQUIRES = ['numpy >= 1.7', 'pandas >= 0.15.0']
TESTS_REQUIRE = ['nose >= 1.0']

if sys.version_info[:2] < (2, 7):
    TESTS_REQUIRE += ["unittest2 == 0.5.1"]

DESCRIPTION = "N-D labeled arrays and datasets in Python"
LONG_DESCRIPTION = """
**xray** is an open source project and Python package that aims to bring the
labeled data power of pandas_ to the physical sciences, by providing
N-dimensional variants of the core pandas data structures.

Our goal is to provide a pandas-like and pandas-compatible toolkit for
analytics on multi-dimensional arrays, rather than the tabular data for which
pandas excels. Our approach adopts the `Common Data Model`_ for self-
describing scientific data in widespread use in the Earth sciences:
``xray.Dataset`` is an in-memory representation of a netCDF file.

.. _pandas: http://pandas.pydata.org
.. _Common Data Model: http://www.unidata.ucar.edu/software/thredds/current/netcdf-java/CDM
.. _netCDF: http://www.unidata.ucar.edu/software/netcdf
.. _OPeNDAP: http://www.opendap.org/

Important links
---------------

- HTML documentation: http://xray.readthedocs.org
- Issue tracker: http://github.com/xray/xray/issues
- Source code: http://github.com/xray/xray
- SciPy2015 talk: https://www.youtube.com/watch?v=X0pAhJgySxk
"""

# code to extract and write the version copied from pandas
FULLVERSION = VERSION
write_version = True

if not ISRELEASED:
    import subprocess
    FULLVERSION += '.dev'

    pipe = None
    for cmd in ['git', 'git.cmd']:
        try:
            pipe = subprocess.Popen(
                [cmd, "describe", "--always", "--match", "v[0-9]*"],
                stdout=subprocess.PIPE)
            (so, serr) = pipe.communicate()
            if pipe.returncode == 0:
                break
        except:
            pass

{'fraction_non_alphanumeric': 0.1343967730106344, 'fraction_numerical': 0.013751375137513752, 'mean_word_length': 3.2026194144838214, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 12, 'https://': 4, 'lorem ipsum': 0, 'www.': 8, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 3, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '5538438', 'n_tokens_mistral': 1829, 'n_tokens_neox': 1735, 'n_words': 538}