new_contents: from setuptools import setup
  #import versioneer
  
  
  long_description = """
  pybroom
  =======
  
  Pybroom converts fitting results objects into
  `Pandas <http://pandas.pydata.org/`__
  `DataFrame <http://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe>`__
  in tidy format
  `(Wickham 2014) `<http://dx.doi.org/10.18637/jss.v059.i10>`__.
  
  The tidy format creates an uniform interface to fit results and allows to
  cleanly combine results from different fits (e.g. comparison of different
  models, comparison of different datasets, etc.). Moreover, tidy DataFrames
  can be easily and systematically plotted with
  `seaborn <https://web.stanford.edu/~mwaskom/software/seaborn/>`__
  (and, increasingly,
  `matplotlib <http://matplotlib.org/>`__).
  """
  
  setup(
      name='pybroom',
      version='0.1',
      #version=versioneer.get_version(),
      #cmdclass=versioneer.get_cmdclass(),
      author='Antonino Ingargiola',
      author_email='tritemio@gmail.com',
      url='https://github.com/tritemio/pybroom',
      download_url='https://github.com/tritemio/pybroom',
      install_requires=['lmfit', 'setuptools'],
      license='MIT',
      description=("Make tidy DataFrames from messy fit/model results."),
      long_description=long_description,
      platforms=('Windows', 'Linux', 'Mac OS X'),
      classifiers=['Intended Audience :: Science/Research',
                   'Operating System :: OS Independent',
                   'Programming Language :: Python',
                   'Programming Language :: Python :: 3.5',
                   'Topic :: Scientific/Engineering',
                   'License :: OSI Approved :: MIT License'],
      py_modules=['pybroom'],
      keywords=('dataframe tidy-data long-form model fitting'))
  
subject: Add setup.py