old_contents: """
  OSMnx setup script.
  
  See license in LICENSE.txt.
  """
  
  import os
  
  from setuptools import setup
  
  # provide a long description using reStructuredText
  LONG_DESCRIPTION = r"""
  **OSMnx** is a package to easily download, model, project, visualize, and
  analyze complex street networks from OpenStreetMap in Python with NetworkX.
  
  You can get a city's or neighborhood's walking, driving, or biking network
  with a single line of Python code. Then you can easily visualize cul-de-sacs
  or one-way streets, plot shortest-path routes, or calculate stats like
  intersection density, average node connectivity, betweenness centrality, etc.
  
  Citation info: Boeing, G. 2017. "`OSMnx: New Methods for Acquiring,
  Constructing, Analyzing, and Visualizing Complex Street Networks`_."
  *Computers, Environment and Urban Systems* 65, 126-139.
  doi:10.1016/j.compenvurbsys.2017.05.004
  
  See the examples and demos on `GitHub`_ or read more about `OSMnx`_.
  
  .. _GitHub: https://github.com/gboeing/osmnx
  .. _OSMnx: http://geoffboeing.com/2016/11/osmnx-python-street-networks/
  .. _OSMnx\: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks: http://geoffboeing.com/publications/osmnx-complex-street-networks/
  """
  
  # list of classifiers from the PyPI classifiers trove
  CLASSIFIERS = [
      "Development Status :: 5 - Production/Stable",
      "License :: OSI Approved :: MIT License",
      "Operating System :: OS Independent",
      "Intended Audience :: Science/Research",
      "Topic :: Scientific/Engineering :: GIS",
      "Topic :: Scientific/Engineering :: Visualization",
      "Topic :: Scientific/Engineering :: Physics",
      "Topic :: Scientific/Engineering :: Mathematics",
      "Topic :: Scientific/Engineering :: Information Analysis",
      "Programming Language :: Python",
      "Programming Language :: Python :: 3",
      "Programming Language :: Python :: 3.6",
      "Programming Language :: Python :: 3.7",
      "Programming Language :: Python :: 3.8",
  ]
  
  DESC = (
      "Retrieve, model, analyze, and visualize OpenStreetMap street networks and other spatial data"
  )
  
  # only specify install_requires if not in RTD environment
  if os.getenv("READTHEDOCS") == "True":
      INSTALL_REQUIRES = []
  else:
      with open("requirements.txt") as f:
          INSTALL_REQUIRES = [line.strip() for line in f.readlines()]
  
  # now call setup
  setup(
      name="osmnx",
      version="0.14.0",
      description=DESC,
      long_description=LONG_DESCRIPTION,
      classifiers=CLASSIFIERS,
      url="https://github.com/gboeing/osmnx",
      author="Geoff Boeing",
      author_email="boeing@usc.edu",
      license="MIT",
      platforms="any",
      packages=["osmnx"],
      python_requires=">=3.6",
      install_requires=INSTALL_REQUIRES,
      extras_require={
          "folium": ["folium>=0.11"],
          "kdtree": ["scipy>=1.4"],
          "balltree": ["scikit-learn>=0.23"],
      },
  )
  
new_contents: """
  OSMnx setup script.
  
  See license in LICENSE.txt.
  """
  
  import os
  
  from setuptools import setup
  
  # provide a long description using reStructuredText
  LONG_DESCRIPTION = r"""
  **OSMnx** is a Python package that lets you download spatial geometries and
  model, project, visualize, and analyze real-world street networks from
  OpenStreetMap's APIs. Users can download and model walkable, drivable, or
  bikeable urban networks with a single line of Python code, and then easily
  analyze and visualize them. You can just as easily download and work with
  amenities/points of interest, building footprints, elevation data, street
  bearings/orientations, speed/travel time, and network routing.
  
  Citation info: Boeing, G. 2017. "`OSMnx: New Methods for Acquiring,
  Constructing, Analyzing, and Visualizing Complex Street Networks`_."
  *Computers, Environment and Urban Systems* 65, 126-139.
  doi:10.1016/j.compenvurbsys.2017.05.004
  
  See the examples and demos on `GitHub`_ or read more about `OSMnx`_.
  
  .. _GitHub: https://github.com/gboeing/osmnx
  .. _OSMnx: http://geoffboeing.com/2016/11/osmnx-python-street-networks/
  .. _OSMnx\: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks: http://geoffboeing.com/publications/osmnx-complex-street-networks/
  """
  
  # list of classifiers from the PyPI classifiers trove
  CLASSIFIERS = [
      "Development Status :: 5 - Production/Stable",
      "License :: OSI Approved :: MIT License",
      "Operating System :: OS Independent",
      "Intended Audience :: Science/Research",
      "Topic :: Scientific/Engineering :: GIS",
      "Topic :: Scientific/Engineering :: Visualization",
      "Topic :: Scientific/Engineering :: Physics",
      "Topic :: Scientific/Engineering :: Mathematics",
      "Topic :: Scientific/Engineering :: Information Analysis",
      "Programming Language :: Python",
      "Programming Language :: Python :: 3",
      "Programming Language :: Python :: 3.6",
      "Programming Language :: Python :: 3.7",
      "Programming Language :: Python :: 3.8",
  ]
  
  DESC = (
      "Retrieve, model, analyze, and visualize OpenStreetMap street networks and other spatial data"
  )
  
  # only specify install_requires if not in RTD environment
  if os.getenv("READTHEDOCS") == "True":
      INSTALL_REQUIRES = []
  else:
      with open("requirements.txt") as f:
          INSTALL_REQUIRES = [line.strip() for line in f.readlines()]
  
  # now call setup
  setup(
      name="osmnx",
      version="0.14.0",
      description=DESC,
      long_description=LONG_DESCRIPTION,
      classifiers=CLASSIFIERS,
      url="https://github.com/gboeing/osmnx",
      author="Geoff Boeing",
      author_email="boeing@usc.edu",
      license="MIT",
      platforms="any",
      packages=["osmnx"],
      python_requires=">=3.6",
      install_requires=INSTALL_REQUIRES,
      extras_require={
          "folium": ["folium>=0.11"],
          "kdtree": ["scipy>=1.4"],
          "balltree": ["scikit-learn>=0.23"],
      },
  )
  
subject: update long desc