old_contents: #!/usr/bin/env python
  from setuptools import setup, find_packages
  import os
  import minihmm
  
  with open("README.rst") as f:
      long_description = f.read()
  
  
  config_info = { "version"      : minihmm.__version__,
                  "packages"     : find_packages(),
                }
  
  
  setup(
      name = "minihmm",
      install_requires = [
      	                "numpy>=1.5",
                          "scipy>=0.12.0",
                          "matplotlib>=1.3.0",
                          ],
  
      zip_safe = True,
  
      # metadata for upload to PyPI
      author           = "Joshua Griffin Dunn",
      author_email     = "joshua.g.dunn@gmail.com",
      maintainer       = "Joshua Griffin Dunn",
      maintainer_email = "Joshua Griffin Dunn",
      
      description = "Lightweight extensible HMM engine, supporting univariate or multivariate, continuous or discrete emissions",
      long_description = long_description,
      license   = "BSD 3-Clause",
      keywords  = "HMM hidden Markov model machine learning modeling statistics",
      url       = "",
      platforms = "POSIX", # windows, 
      
      tests_require=["nose>=1.0"],
      #test_suite = "nose.collector",
      
      classifiers=[
           'Development Status :: 3 - Alpha',
  
           'Programming Language :: Python',
           'Programming Language :: Python :: 2.7',
           'Programming Language :: Python :: 3.3',
           'Programming Language :: Python :: 3.4',
  
           'Topic :: Scientific/Engineering',
           'License :: BSD 3-Clause',
           'Operating System :: POSIX',
          ]
      
      **config_info
  )
  
new_contents: #!/usr/bin/env python
  from setuptools import setup, find_packages
  import os
  import minihmm
  
  with open("README.rst") as f:
      long_description = f.read()
  
  
  config_info = { "version"      : minihmm.__version__,
                  "packages"     : find_packages(),
                }
  
  
  setup(
      name = "minihmm",
      install_requires = [
      	                "numpy>=1.5",
                          "scipy>=0.12.0",
                          "matplotlib>=1.3.0",
                          ],
  
      zip_safe = True,
  
      # metadata for upload to PyPI
      author           = "Joshua Griffin Dunn",
      author_email     = "joshua.g.dunn@gmail.com",
      maintainer       = "Joshua Griffin Dunn",
      maintainer_email = "Joshua Griffin Dunn",
      
      description = "Lightweight extensible HMM engine, supporting univariate or multivariate, continuous or discrete emissions",
      long_description = long_description,
      license   = "BSD 3-Clause",
      keywords  = "HMM hidden Markov model machine learning modeling statistics",
      url       = "",
      platforms = "POSIX", # windows, 
      
      tests_require=["nose>=1.0"],
      #test_suite = "nose.collector",
      
      classifiers=[
           'Development Status :: 3 - Alpha',
  
           'Programming Language :: Python',
           'Programming Language :: Python :: 2.7',
           'Programming Language :: Python :: 3.3',
           'Programming Language :: Python :: 3.4',
  
           'Topic :: Scientific/Engineering',
           'License :: BSD 3-Clause',
           'Operating System :: POSIX',
          ],
      
      **config_info
  )
  
subject: add lost comma