text: # coding: utf-8
  # Copyright (c) Pymatgen Development Team.
  # Distributed under the terms of the MIT License.
  
  """Setup.py for pymatgen."""
  
  import sys
  import platform
  
  from setuptools import setup, find_packages, Extension
  from setuptools.command.build_ext import build_ext as _build_ext
  
  
  class build_ext(_build_ext):
      """Extension builder that checks for numpy before install."""
      def finalize_options(self):
          """Override finalize_options."""
          _build_ext.finalize_options(self)
          # Prevent numpy from thinking it is still in its setup process:
          import builtins
          if hasattr(builtins, '__NUMPY_SETUP__'):
              del builtins.__NUMPY_SETUP__
          import importlib
          import numpy
          importlib.reload(numpy)
          self.include_dirs.append(numpy.get_include())
  
  
  extra_link_args = []
  if sys.platform.startswith('win') and platform.machine().endswith('64'):
      extra_link_args.append('-Wl,--allow-multiple-definition')
  
  cpp_extra_link_args = extra_link_args
  cpp_extra_compile_args = ["-Wno-cpp", "-Wno-unused-function", "-O2", "-march=native", '-std=c++11']
  if sys.platform.startswith('darwin'):
      cpp_extra_compile_args.append("-stdlib=libc++")
      cpp_extra_link_args = ["-O2", "-march=native", '-stdlib=libc++']
  
  # https://docs.microsoft.com/en-us/cpp/build/reference/compiler-options-listed-alphabetically?view=vs-2017
  if sys.platform.startswith('win'):
      cpp_extra_compile_args = ['/w', '/O2', '/std:c++14']
      cpp_extra_link_args = extra_link_args
  
  long_desc = """
  Official docs: [http://pymatgen.org](http://pymatgen.org/)
  
  Pymatgen (Python Materials Genomics) is a robust, open-source Python library
  for materials analysis. These are some of the main features:
  
  1. Highly flexible classes for the representation of Element, Site, Molecule,
     Structure objects.
  2. Extensive input/output support, including support for
     [VASP](http://cms.mpi.univie.ac.at/vasp/), [ABINIT](http://www.abinit.org/),
     CIF, Gaussian, XYZ, and many other file formats.
  3. Powerful analysis tools, including generation of phase diagrams, Pourbaix
     diagrams, diffusion analyses, reactions, etc.
  4. Electronic structure analyses, such as density of states and band structure.
  5. Integration with the Materials Project REST API.
  
  Pymatgen is free to use. However, we also welcome your help to improve this
  library by making your own contributions.  These contributions can be in the
  form of additional tools or modules you develop, or feature requests and bug
  reports. Please report any bugs and issues at pymatgen's [Github page]
  (https://github.com/materialsproject/pymatgen). For help with any pymatgen
  issues, please use the [Discourse page](https://discuss.matsci.org/c/pymatgen).
  
  Why use pymatgen?
  =================
  
  There are many materials analysis codes out there, both commerical and free,
  but pymatgen offer several advantages:
  
  1. **It is (fairly) robust.** Pymatgen is used by thousands of researchers,
     and is the analysis code powering the [Materials Project](https://www.materialsproject.org).
     The analysis it produces survives rigorous scrutiny every single day. Bugs
     tend to be found and corrected quickly. Pymatgen also uses
     [CircleCI](https://circleci.com) and [Appveyor](https://www.appveyor.com/)
     for continuous integration on the Linux and Windows platforms,
     respectively, which ensures that every commit passes a comprehensive suite
     of unittests.
  2. **It is well documented.** A fairly comprehensive documentation has been
     written to help you get to grips with it quickly.
  3. **It is open.** You are free to use and contribute to pymatgen. It also means
     that pymatgen is continuously being improved. We will attribute any code you
     contribute to any publication you specify. Contributing to pymatgen means
     your research becomes more visible, which translates to greater impact.
  4. **It is fast.** Many of the core numerical methods in pymatgen have been
     optimized by vectorizing in numpy/scipy. This means that coordinate
     manipulations are extremely fast and are in fact comparable to codes
     written in other languages. Pymatgen also comes with a complete system for
     handling periodic boundary conditions.
  5. **It will be around.** Pymatgen is not a pet research project. It is used in
     the well-established Materials Project. It is also actively being developed
     and maintained by the [Materials Virtual Lab](https://www.materialsvirtuallab.org),
     the ABINIT group and many other research groups.
  
  With effect from version 2019.1.1, pymatgen only supports Python 3.x. Users
  who require Python 2.7 should install pymatgen v2018.x.
  """
  
  setup(
      name="pymatgen",
      packages=find_packages(),
      version="2019.11.11",
      cmdclass={'build_ext': build_ext},
      setup_requires=['numpy>=1.14.3', 'setuptools>=18.0'],
      python_requires='>=3.6',
      install_requires=["numpy>=1.14.3", "requests", "ruamel.yaml>=0.15.6",
                        "monty>=3.0.2", "scipy>=1.0.1", "pydispatcher>=2.0.5",
                        "tabulate", "spglib>=1.9.9.44", "networkx>=2.2",
                        "matplotlib>=1.5", "palettable>=3.1.1", "sympy", "pandas"],
      extras_require={
          "provenance": ["pybtex"],
          "ase": ["ase>=3.3"],
          "vis": ["vtk>=6.0.0"],
          "abinit": ["netcdf4"],
          ':python_version < "3.7"': [
              "dataclasses>=0.6",
          ]},
      package_data={
          "pymatgen.core": ["*.json"],
          "pymatgen.analysis": ["*.yaml", "*.json"],
          "pymatgen.analysis.cost": ["*.csv"],
          "pymatgen.analysis.chemenv.coordination_environments.coordination_geometries_files": ["*.txt", "*.json"],
          "pymatgen.analysis.chemenv.coordination_environments.strategy_files": ["*.json"],
          "pymatgen.analysis.hhi": ["*.csv"],
          "pymatgen.analysis.magnetism": ["*.json", "*.yaml"],
          "pymatgen.analysis.structure_prediction": ["data/*.json", "*.yaml"],
          "pymatgen.io": ["*.yaml"],
          "pymatgen.io.vasp": ["*.yaml", "*.json"],
          "pymatgen.io.lammps": ["templates/*.*"],
          "pymatgen.io.feff": ["*.yaml"],
          "pymatgen.symmetry": ["*.yaml", "*.json", "*.sqlite"],
          "pymatgen.entries": ["*.yaml"],
          "pymatgen.vis": ["ElementColorSchemes.yaml"],
          "pymatgen.command_line": ["OxideTersoffPotentials"],
          "pymatgen.analysis.defects": ["*.json"],
          "pymatgen.analysis.diffraction": ["*.json"],
          "pymatgen.util": ["structures/*.json"]},
      author="Pymatgen Development Team",
      author_email="ongsp@eng.ucsd.edu",
      maintainer="Shyue Ping Ong, Matthew Horton",
      maintainer_email="ongsp@eng.ucsd.edu, mkhorton@lbl.gov",
      url="http://www.pymatgen.org",
      license="MIT",
      description="Python Materials Genomics is a robust materials "
                  "analysis code that defines core object representations for "
                  "structures and molecules with support for many electronic "
                  "structure codes. It is currently the core analysis code "
                  "powering the Materials Project "
                  "(https://www.materialsproject.org).",
      long_description=long_desc,
      long_description_content_type='text/markdown',
      keywords=["VASP", "gaussian", "ABINIT", "nwchem", "qchem", "materials", "science",
                "project", "electronic", "structure", "analysis", "phase", "diagrams",
                "crystal"],
      classifiers=[
          "Programming Language :: Python :: 3",
          "Programming Language :: Python :: 3.5",
          "Programming Language :: Python :: 3.6",
          "Programming Language :: Python :: 3.7",
          "Development Status :: 4 - Beta",
          "Intended Audience :: Science/Research",
          "License :: OSI Approved :: MIT License",
          "Operating System :: OS Independent",
          "Topic :: Scientific/Engineering :: Information Analysis",
          "Topic :: Scientific/Engineering :: Physics",
          "Topic :: Scientific/Engineering :: Chemistry",
          "Topic :: Software Development :: Libraries :: Python Modules"
      ],
      ext_modules=[Extension("pymatgen.optimization.linear_assignment",
                             ["pymatgen/optimization/linear_assignment.c"],
                             extra_link_args=extra_link_args),
                   Extension("pymatgen.util.coord_cython",
                             ["pymatgen/util/coord_cython.c"],
                             extra_link_args=extra_link_args),
                   Extension("pymatgen.optimization.neighbors",
                             ["pymatgen/optimization/neighbors.cpp"],
                             extra_compile_args=cpp_extra_compile_args,
                             extra_link_args=cpp_extra_link_args,
                             language='c++')],
      entry_points={
            'console_scripts': [
                'pmg = pymatgen.cli.pmg:main',
                'feff_input_generation = pymatgen.cli.feff_input_generation:main',
                'feff_plot_cross_section = pymatgen.cli.feff_plot_cross_section:main',
                'feff_plot_dos = pymatgen.cli.feff_plot_dos:main',
                'gaussian_analyzer = pymatgen.cli.gaussian_analyzer:main',
                'get_environment = pymatgen.cli.get_environment:main',
            ]
      }
  )