old_contents: #!/usr/bin/env python
  
  from setuptools import setup, find_packages
  from codecs import open
  from os import path
  here = path.abspath(path.dirname(__file__))
  
  # Get the long description from the relevant file
  with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
      long_description = f.read()
  
  # Get the version from the relevant file
  with open(path.join(here, 'pysparkling/version.txt'), encoding='utf-8') as f:
      version = f.read()
  
  setup(
      name = 'h2o_pysparkling_' + version[:version.rindex(".")],
  
      # Versions should comply with PEP440.  For a discussion on single-sourcing
      # the version across setup.py and the project code, see
      # https://packaging.python.org/en/latest/single_source_version.html
      version = version,
      description = 'Sparkling Water integrates H2O\'s Fast Scalable Machine Learning with Spark',
      long_description = long_description,
  
      url = 'https://github.com/h2oai/sparkling-water',
      download_url = 'https://github.com/h2oai/sparkling-water/',
      author = 'H2O.ai',
      author_email = 'support@h2o.ai',
      license = 'Apache v2',
      classifiers = [
          'Development Status :: 5 - Production/Stable',
          'Intended Audience :: Developers',
          'Topic :: Software Development :: Build Tools',
          'License :: OSI Approved :: Apache Software License',
          'Programming Language :: Python :: 2.7',
          'Programming Language :: Python :: 3',
          'Programming Language :: Python :: 3.2',
          'Programming Language :: Python :: 3.3',
          'Programming Language :: Python :: 3.4',
      ],
      keywords = 'machine learning, data mining, statistical analysis, modeling, big data, distributed, parallel',
  
  
      # find python packages starting in the current directory
      packages = find_packages(),
  
      # run-time dependencies
      install_requires=['requests', 'tabulate', 'future', 'colorama>=0.3.8', 'six', 'pyspark>=2.3.0,<=2.3.2'],
  
      # bundled binary packages
      package_data={'sparkling_water': ['*.jar'],
                    'h2o': ['version.txt', 'buildinfo.txt'],
                    'pysparkling': ['version.txt']},
  )
  
  
new_contents: #!/usr/bin/env python
  
  from setuptools import setup, find_packages
  from codecs import open
  from os import path
  here = path.abspath(path.dirname(__file__))
  
  # Get the long description from the relevant file
  with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
      long_description = f.read()
  
  # Get the version from the relevant file
  with open(path.join(here, 'pysparkling/version.txt'), encoding='utf-8') as f:
      version = f.read()
  
  setup(
      name = 'h2o_pysparkling_' + version[:version.rindex(".")],
  
      # Versions should comply with PEP440.  For a discussion on single-sourcing
      # the version across setup.py and the project code, see
      # https://packaging.python.org/en/latest/single_source_version.html
      version = version,
      description = 'Sparkling Water integrates H2O\'s Fast Scalable Machine Learning with Spark',
      long_description = long_description,
  
      url = 'https://github.com/h2oai/sparkling-water',
      download_url = 'https://github.com/h2oai/sparkling-water/',
      author = 'H2O.ai',
      author_email = 'support@h2o.ai',
      license = 'Apache v2',
      classifiers = [
          'Development Status :: 5 - Production/Stable',
          'Intended Audience :: Developers',
          'Topic :: Software Development :: Build Tools',
          'License :: OSI Approved :: Apache Software License',
          'Programming Language :: Python :: 2.7',
          'Programming Language :: Python :: 3',
          'Programming Language :: Python :: 3.2',
          'Programming Language :: Python :: 3.3',
          'Programming Language :: Python :: 3.4',
      ],
      keywords = 'machine learning, data mining, statistical analysis, modeling, big data, distributed, parallel',
  
  
      # find python packages starting in the current directory
      packages = find_packages(),
  
      # run-time dependencies
      install_requires=['requests', 'tabulate', 'future', 'colorama>=0.3.8', 'six', 'pyspark>=2.4.0,<=2.4.0'],
  
      # bundled binary packages
      package_data={'sparkling_water': ['*.jar'],
                    'h2o': ['version.txt', 'buildinfo.txt'],
                    'pysparkling': ['version.txt']},
  )
  
  
subject: Fix pyspark dependency for pysparkling for Spark 2.4 (#1004)