text: #!/usr/bin/env python
  
  """
  Parts of this file were taken from the pyzmq project
  (https://github.com/zeromq/pyzmq) which have been permitted for use under the
  BSD license. Parts are from lxml (https://github.com/lxml/lxml)
  """
  
  import os
  from os.path import join as pjoin
  
  import pkg_resources
  import platform
  from distutils.sysconfig import get_config_vars
  import sys
  import shutil
  from distutils.version import LooseVersion
  from setuptools import setup, Command, find_packages
  
  # versioning
  import versioneer
  
  cmdclass = versioneer.get_cmdclass()
  
  
  def is_platform_windows():
      return sys.platform == "win32" or sys.platform == "cygwin"
  
  
  def is_platform_mac():
      return sys.platform == "darwin"
  
  
  min_numpy_ver = "1.13.3"
  setuptools_kwargs = {
      "install_requires": [
          "python-dateutil >= 2.6.1",
          "pytz >= 2017.2",
          "numpy >= {numpy_ver}".format(numpy_ver=min_numpy_ver),
      ],
      "setup_requires": ["numpy >= {numpy_ver}".format(numpy_ver=min_numpy_ver)],
      "zip_safe": False,
  }
  
  
  min_cython_ver = "0.28.2"
  try:
      import Cython
  
      ver = Cython.__version__
      from Cython.Build import cythonize
  
      _CYTHON_INSTALLED = ver >= LooseVersion(min_cython_ver)
  except ImportError:
      _CYTHON_INSTALLED = False
      cythonize = lambda x, *args, **kwargs: x  # dummy func
  
  # The import of Extension must be after the import of Cython, otherwise
  # we do not get the appropriately patched class.
  # See https://cython.readthedocs.io/en/latest/src/reference/compilation.html
  from distutils.extension import Extension  # noqa:E402
  from distutils.command.build import build  # noqa:E402
  
  try:
      if not _CYTHON_INSTALLED:
          raise ImportError("No supported version of Cython installed.")
      from Cython.Distutils.old_build_ext import old_build_ext as _build_ext
  
      cython = True
  except ImportError:
      from distutils.command.build_ext import build_ext as _build_ext
  
      cython = False
  else:
      try:
          try:
              from Cython import Tempita as tempita
          except ImportError:
              import tempita
      except ImportError:
          raise ImportError("Building pandas requires Tempita: " "pip install Tempita")
  
  
  _pxi_dep_template = {
      "algos": [
          "_libs/algos_common_helper.pxi.in",
          "_libs/algos_take_helper.pxi.in",
          "_libs/algos_rank_helper.pxi.in",
      ],
      "groupby": ["_libs/groupby_helper.pxi.in"],
      "hashtable": [
          "_libs/hashtable_class_helper.pxi.in",
          "_libs/hashtable_func_helper.pxi.in",
      ],
      "index": ["_libs/index_class_helper.pxi.in"],
      "sparse": ["_libs/sparse_op_helper.pxi.in"],
      "interval": ["_libs/intervaltree.pxi.in"],
  }
  
  _pxifiles = []
  _pxi_dep = {}
  for module, files in _pxi_dep_template.items():
      pxi_files = [pjoin("pandas", x) for x in files]
      _pxifiles.extend(pxi_files)
      _pxi_dep[module] = pxi_files
  
  
  class build_ext(_build_ext):
      @classmethod
      def render_templates(cls, pxifiles):
          for pxifile in pxifiles:
              # build pxifiles first, template extension must be .pxi.in
              assert pxifile.endswith(".pxi.in")
              outfile = pxifile[:-3]
  
              if (
                  os.path.exists(outfile)
                  and os.stat(pxifile).st_mtime < os.stat(outfile).st_mtime
              ):
                  # if .pxi.in is not updated, no need to output .pxi
                  continue
  
              with open(pxifile, "r") as f:
                  tmpl = f.read()
              pyxcontent = tempita.sub(tmpl)
  
              with open(outfile, "w") as f:
                  f.write(pyxcontent)
  
      def build_extensions(self):
          # if building from c files, don't need to
          # generate template output
          if cython:
              self.render_templates(_pxifiles)
  
          numpy_incl = pkg_resources.resource_filename("numpy", "core/include")
  
          for ext in self.extensions:
              if hasattr(ext, "include_dirs") and numpy_incl not in ext.include_dirs:
                  ext.include_dirs.append(numpy_incl)
          _build_ext.build_extensions(self)
  
  
  DESCRIPTION = (
      "Powerful data structures for data analysis, time series, " "and statistics"
  )
  LONG_DESCRIPTION = """
  **pandas** is a Python package providing fast, flexible, and expressive data
  structures designed to make working with structured (tabular, multidimensional,
  potentially heterogeneous) and time series data both easy and intuitive. It
  aims to be the fundamental high-level building block for doing practical,
  **real world** data analysis in Python. Additionally, it has the broader goal
  of becoming **the most powerful and flexible open source data analysis /
  manipulation tool available in any language**. It is already well on its way
  toward this goal.
  
  pandas is well suited for many different kinds of data:
  
    - Tabular data with heterogeneously-typed columns, as in an SQL table or
      Excel spreadsheet
    - Ordered and unordered (not necessarily fixed-frequency) time series data.
    - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and
      column labels
    - Any other form of observational / statistical data sets. The data actually
      need not be labeled at all to be placed into a pandas data structure
  
  The two primary data structures of pandas, Series (1-dimensional) and DataFrame
  (2-dimensional), handle the vast majority of typical use cases in finance,
  statistics, social science, and many areas of engineering. For R users,
  DataFrame provides everything that R's ``data.frame`` provides and much
  more. pandas is built on top of `NumPy <http://www.numpy.org>`__ and is
  intended to integrate well within a scientific computing environment with many
  other 3rd party libraries.
  
  Here are just a few of the things that pandas does well:
  
    - Easy handling of **missing data** (represented as NaN) in floating point as
      well as non-floating point data
    - Size mutability: columns can be **inserted and deleted** from DataFrame and
      higher dimensional objects
    - Automatic and explicit **data alignment**: objects can be explicitly
      aligned to a set of labels, or the user can simply ignore the labels and
      let `Series`, `DataFrame`, etc. automatically align the data for you in
      computations
    - Powerful, flexible **group by** functionality to perform
      split-apply-combine operations on data sets, for both aggregating and
      transforming data
    - Make it **easy to convert** ragged, differently-indexed data in other
      Python and NumPy data structures into DataFrame objects
    - Intelligent label-based **slicing**, **fancy indexing**, and **subsetting**
      of large data sets
    - Intuitive **merging** and **joining** data sets
    - Flexible **reshaping** and pivoting of data sets
    - **Hierarchical** labeling of axes (possible to have multiple labels per
      tick)
    - Robust IO tools for loading data from **flat files** (CSV and delimited),
      Excel files, databases, and saving / loading data from the ultrafast **HDF5
      format**
    - **Time series**-specific functionality: date range generation and frequency
      conversion, moving window statistics, moving window linear regressions,
      date shifting and lagging, etc.
  
  Many of these principles are here to address the shortcomings frequently
  experienced using other languages / scientific research environments. For data
  scientists, working with data is typically divided into multiple stages:
  munging and cleaning data, analyzing / modeling it, then organizing the results
  of the analysis into a form suitable for plotting or tabular display. pandas is
  the ideal tool for all of these tasks.
  """
  
  DISTNAME = "pandas"
  LICENSE = "BSD"
  AUTHOR = "The PyData Development Team"
  EMAIL = "pydata@googlegroups.com"
  URL = "http://pandas.pydata.org"
  DOWNLOAD_URL = ""
  PROJECT_URLS = {
      "Bug Tracker": "https://github.com/pandas-dev/pandas/issues",
      "Documentation": "http://pandas.pydata.org/pandas-docs/stable/",
      "Source Code": "https://github.com/pandas-dev/pandas",
  }
  CLASSIFIERS = [
      "Development Status :: 5 - Production/Stable",
      "Environment :: Console",
      "Operating System :: OS Independent",
      "Intended Audience :: Science/Research",
      "Programming Language :: Python",
      "Programming Language :: Python :: 3",
      "Programming Language :: Python :: 3.5",
      "Programming Language :: Python :: 3.6",
      "Programming Language :: Python :: 3.7",
      "Programming Language :: Cython",
      "Topic :: Scientific/Engineering",
  ]
  
  
  class CleanCommand(Command):
      """Custom distutils command to clean the .so and .pyc files."""
  
      user_options = [("all", "a", "")]
  
      def initialize_options(self):
          self.all = True
          self._clean_me = []
          self._clean_trees = []
  
          base = pjoin("pandas", "_libs", "src")
          tsbase = pjoin("pandas", "_libs", "tslibs", "src")
          dt = pjoin(tsbase, "datetime")
          util = pjoin("pandas", "util")
          parser = pjoin(base, "parser")
          ujson_python = pjoin(base, "ujson", "python")
          ujson_lib = pjoin(base, "ujson", "lib")
          self._clean_exclude = [
              pjoin(dt, "np_datetime.c"),
              pjoin(dt, "np_datetime_strings.c"),
              pjoin(parser, "tokenizer.c"),
              pjoin(parser, "io.c"),
              pjoin(ujson_python, "ujson.c"),
              pjoin(ujson_python, "objToJSON.c"),
              pjoin(ujson_python, "JSONtoObj.c"),
              pjoin(ujson_lib, "ultrajsonenc.c"),
              pjoin(ujson_lib, "ultrajsondec.c"),
              pjoin(util, "move.c"),
          ]
  
          for root, dirs, files in os.walk("pandas"):
              for f in files:
                  filepath = pjoin(root, f)
                  if filepath in self._clean_exclude:
                      continue
  
                  if os.path.splitext(f)[-1] in (
                      ".pyc",
                      ".so",
                      ".o",
                      ".pyo",
                      ".pyd",
                      ".c",
                      ".orig",
                  ):
                      self._clean_me.append(filepath)
              for d in dirs:
                  if d == "__pycache__":
                      self._clean_trees.append(pjoin(root, d))
  
          # clean the generated pxi files
          for pxifile in _pxifiles:
              pxifile = pxifile.replace(".pxi.in", ".pxi")
              self._clean_me.append(pxifile)
  
          for d in ("build", "dist"):
              if os.path.exists(d):
                  self._clean_trees.append(d)
  
      def finalize_options(self):
          pass
  
      def run(self):
          for clean_me in self._clean_me:
              try:
                  os.unlink(clean_me)
              except Exception:
                  pass
          for clean_tree in self._clean_trees:
              try:
                  shutil.rmtree(clean_tree)
              except Exception:
                  pass
  
  
  # we need to inherit from the versioneer
  # class as it encodes the version info
  sdist_class = cmdclass["sdist"]
  
  
  class CheckSDist(sdist_class):
      """Custom sdist that ensures Cython has compiled all pyx files to c."""
  
      _pyxfiles = [
          "pandas/_libs/lib.pyx",
          "pandas/_libs/hashtable.pyx",
          "pandas/_libs/tslib.pyx",
          "pandas/_libs/index.pyx",
          "pandas/_libs/internals.pyx",
          "pandas/_libs/algos.pyx",
          "pandas/_libs/join.pyx",
          "pandas/_libs/indexing.pyx",
          "pandas/_libs/interval.pyx",
          "pandas/_libs/hashing.pyx",
          "pandas/_libs/missing.pyx",
          "pandas/_libs/reduction.pyx",
          "pandas/_libs/testing.pyx",
          "pandas/_libs/skiplist.pyx",
          "pandas/_libs/sparse.pyx",
          "pandas/_libs/ops.pyx",
          "pandas/_libs/parsers.pyx",
          "pandas/_libs/tslibs/c_timestamp.pyx",
          "pandas/_libs/tslibs/ccalendar.pyx",
          "pandas/_libs/tslibs/period.pyx",
          "pandas/_libs/tslibs/strptime.pyx",
          "pandas/_libs/tslibs/np_datetime.pyx",
          "pandas/_libs/tslibs/timedeltas.pyx",
          "pandas/_libs/tslibs/timestamps.pyx",
          "pandas/_libs/tslibs/timezones.pyx",
          "pandas/_libs/tslibs/conversion.pyx",
          "pandas/_libs/tslibs/fields.pyx",
          "pandas/_libs/tslibs/offsets.pyx",
          "pandas/_libs/tslibs/frequencies.pyx",
          "pandas/_libs/tslibs/resolution.pyx",
          "pandas/_libs/tslibs/parsing.pyx",
          "pandas/_libs/tslibs/tzconversion.pyx",
          "pandas/_libs/writers.pyx",
          "pandas/io/sas/sas.pyx",
      ]
  
      _cpp_pyxfiles = [
          "pandas/_libs/window.pyx",
          "pandas/io/msgpack/_packer.pyx",
          "pandas/io/msgpack/_unpacker.pyx",
      ]
  
      def initialize_options(self):
          sdist_class.initialize_options(self)
  
      def run(self):
          if "cython" in cmdclass:
              self.run_command("cython")
          else:
              # If we are not running cython then
              # compile the extensions correctly
              pyx_files = [(self._pyxfiles, "c"), (self._cpp_pyxfiles, "cpp")]
  
              for pyxfiles, extension in pyx_files:
                  for pyxfile in pyxfiles:
                      sourcefile = pyxfile[:-3] + extension
                      msg = (
                          "{extension}-source file '{source}' not found.\n"
                          "Run 'setup.py cython' before sdist.".format(
                              source=sourcefile, extension=extension
                          )
                      )
                      assert os.path.isfile(sourcefile), msg
          sdist_class.run(self)
  
  
  class CheckingBuildExt(build_ext):
      """
      Subclass build_ext to get clearer report if Cython is necessary.
      """
  
      def check_cython_extensions(self, extensions):
          for ext in extensions:
              for src in ext.sources:
                  if not os.path.exists(src):
                      print("{}: -> [{}]".format(ext.name, ext.sources))
                      raise Exception(
                          """Cython-generated file '{src}' not found.
                  Cython is required to compile pandas from a development branch.
                  Please install Cython or download a release package of pandas.
                  """.format(
                              src=src
                          )
                      )
  
      def build_extensions(self):
          self.check_cython_extensions(self.extensions)
          build_ext.build_extensions(self)
  
  
  class CythonCommand(build_ext):
      """
      Custom distutils command subclassed from Cython.Distutils.build_ext
      to compile pyx->c, and stop there. All this does is override the
      C-compile method build_extension() with a no-op.
      """
  
      def build_extension(self, ext):
          pass
  
  
  class DummyBuildSrc(Command):
      """ numpy's build_src command interferes with Cython's build_ext.
      """
  
      user_options = []
  
      def initialize_options(self):
          self.py_modules_dict = {}
  
      def finalize_options(self):
          pass
  
      def run(self):
          pass
  
  
  cmdclass.update({"clean": CleanCommand, "build": build})
  
  if cython:
      suffix = ".pyx"
      cmdclass["build_ext"] = CheckingBuildExt
      cmdclass["cython"] = CythonCommand
  else:
      suffix = ".c"
      cmdclass["build_src"] = DummyBuildSrc
      cmdclass["build_ext"] = CheckingBuildExt
  
  # ----------------------------------------------------------------------
  # Preparation of compiler arguments
  
  debugging_symbols_requested = "--with-debugging-symbols" in sys.argv
  if debugging_symbols_requested:
      sys.argv.remove("--with-debugging-symbols")
  
  
  if sys.byteorder == "big":
      endian_macro = [("__BIG_ENDIAN__", "1")]
  else:
      endian_macro = [("__LITTLE_ENDIAN__", "1")]
  
  
  if is_platform_windows():
      extra_compile_args = []
      extra_link_args = []
      if debugging_symbols_requested:
          extra_compile_args.append("/Z7")
          extra_link_args.append("/DEBUG")
  else:
      # args to ignore warnings
      extra_compile_args = ["-Wno-unused-function"]
      extra_link_args = []
      if debugging_symbols_requested:
          extra_compile_args.append("-g")
  
  # Build for at least macOS 10.9 when compiling on a 10.9 system or above,
  # overriding CPython distuitls behaviour which is to target the version that
  # python was built for. This may be overridden by setting
  # MACOSX_DEPLOYMENT_TARGET before calling setup.py
  if is_platform_mac():
      if "MACOSX_DEPLOYMENT_TARGET" not in os.environ:
          current_system = platform.mac_ver()[0]
          python_target = get_config_vars().get(
              "MACOSX_DEPLOYMENT_TARGET", current_system
          )
          if (
              LooseVersion(python_target) < "10.9"
              and LooseVersion(current_system) >= "10.9"
          ):
              os.environ["MACOSX_DEPLOYMENT_TARGET"] = "10.9"
  
  # enable coverage by building cython files by setting the environment variable
  # "PANDAS_CYTHON_COVERAGE" (with a Truthy value) or by running build_ext
  # with `--with-cython-coverage`enabled
  linetrace = os.environ.get("PANDAS_CYTHON_COVERAGE", False)
  if "--with-cython-coverage" in sys.argv:
      linetrace = True
      sys.argv.remove("--with-cython-coverage")
  
  # Note: if not using `cythonize`, coverage can be enabled by
  # pinning `ext.cython_directives = directives` to each ext in extensions.
  # github.com/cython/cython/wiki/enhancements-compilerdirectives#in-setuppy
  directives = {"linetrace": False, "language_level": 3}
  macros = []
  if linetrace:
      # https://pypkg.com/pypi/pytest-cython/f/tests/example-project/setup.py
      directives["linetrace"] = True
      macros = [("CYTHON_TRACE", "1"), ("CYTHON_TRACE_NOGIL", "1")]
  
  # in numpy>=1.16.0, silence build warnings about deprecated API usage
  #  we can't do anything about these warnings because they stem from
  #  cython+numpy version mismatches.
  macros.append(("NPY_NO_DEPRECATED_API", "0"))
  
  
  # ----------------------------------------------------------------------
  # Specification of Dependencies
  
  # TODO: Need to check to see if e.g. `linetrace` has changed and possibly
  # re-compile.
  def maybe_cythonize(extensions, *args, **kwargs):
      """
      Render tempita templates before calling cythonize
      """
      if len(sys.argv) > 1 and "clean" in sys.argv:
          # Avoid running cythonize on `python setup.py clean`
          # See https://github.com/cython/cython/issues/1495
          return extensions
      if not cython:
          # Avoid trying to look up numpy when installing from sdist
          # https://github.com/pandas-dev/pandas/issues/25193
          # TODO: See if this can be removed after pyproject.toml added.
          return extensions
  
      numpy_incl = pkg_resources.resource_filename("numpy", "core/include")
      # TODO: Is this really necessary here?
      for ext in extensions:
          if hasattr(ext, "include_dirs") and numpy_incl not in ext.include_dirs:
              ext.include_dirs.append(numpy_incl)
  
      build_ext.render_templates(_pxifiles)
      return cythonize(extensions, *args, **kwargs)
  
  
  def srcpath(name=None, suffix=".pyx", subdir="src"):
      return pjoin("pandas", subdir, name + suffix)
  
  
  common_include = ["pandas/_libs/src/klib", "pandas/_libs/src"]
  ts_include = ["pandas/_libs/tslibs/src", "pandas/_libs/tslibs"]
  
  
  lib_depends = ["pandas/_libs/src/parse_helper.h", "pandas/_libs/src/compat_helper.h"]
  
  np_datetime_headers = [
      "pandas/_libs/tslibs/src/datetime/np_datetime.h",
      "pandas/_libs/tslibs/src/datetime/np_datetime_strings.h",
  ]
  np_datetime_sources = [
      "pandas/_libs/tslibs/src/datetime/np_datetime.c",
      "pandas/_libs/tslibs/src/datetime/np_datetime_strings.c",
  ]
  
  tseries_depends = np_datetime_headers
  
  
  ext_data = {
      "_libs.algos": {"pyxfile": "_libs/algos", "depends": _pxi_dep["algos"]},
      "_libs.groupby": {"pyxfile": "_libs/groupby", "depends": _pxi_dep["groupby"]},
      "_libs.hashing": {"pyxfile": "_libs/hashing", "include": [], "depends": []},
      "_libs.hashtable": {
          "pyxfile": "_libs/hashtable",
          "depends": (["pandas/_libs/src/klib/khash_python.h"] + _pxi_dep["hashtable"]),
      },
      "_libs.index": {
          "pyxfile": "_libs/index",
          "include": common_include + ts_include,
          "depends": _pxi_dep["index"],
          "sources": np_datetime_sources,
      },
      "_libs.indexing": {"pyxfile": "_libs/indexing"},
      "_libs.internals": {"pyxfile": "_libs/internals"},
      "_libs.interval": {"pyxfile": "_libs/interval", "depends": _pxi_dep["interval"]},
      "_libs.join": {"pyxfile": "_libs/join"},
      "_libs.lib": {
          "pyxfile": "_libs/lib",
          "include": common_include + ts_include,
          "depends": lib_depends + tseries_depends,
          "sources": ["pandas/_libs/src/parser/tokenizer.c"],
      },
      "_libs.missing": {
          "pyxfile": "_libs/missing",
          "include": common_include + ts_include,
          "depends": tseries_depends,
      },
      "_libs.parsers": {
          "pyxfile": "_libs/parsers",
          "depends": [
              "pandas/_libs/src/parser/tokenizer.h",
              "pandas/_libs/src/parser/io.h",
          ],
          "sources": [
              "pandas/_libs/src/parser/tokenizer.c",
              "pandas/_libs/src/parser/io.c",
          ],
      },
      "_libs.reduction": {"pyxfile": "_libs/reduction"},
      "_libs.ops": {"pyxfile": "_libs/ops"},
      "_libs.properties": {"pyxfile": "_libs/properties", "include": []},
      "_libs.reshape": {"pyxfile": "_libs/reshape", "depends": []},
      "_libs.skiplist": {
          "pyxfile": "_libs/skiplist",
          "depends": ["pandas/_libs/src/skiplist.h"],
      },
      "_libs.sparse": {"pyxfile": "_libs/sparse", "depends": _pxi_dep["sparse"]},
      "_libs.tslib": {
          "pyxfile": "_libs/tslib",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.c_timestamp": {
          "pyxfile": "_libs/tslibs/c_timestamp",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.ccalendar": {"pyxfile": "_libs/tslibs/ccalendar", "include": []},
      "_libs.tslibs.conversion": {
          "pyxfile": "_libs/tslibs/conversion",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.fields": {
          "pyxfile": "_libs/tslibs/fields",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.frequencies": {"pyxfile": "_libs/tslibs/frequencies", "include": []},
      "_libs.tslibs.nattype": {"pyxfile": "_libs/tslibs/nattype", "include": []},
      "_libs.tslibs.np_datetime": {
          "pyxfile": "_libs/tslibs/np_datetime",
          "include": ts_include,
          "depends": np_datetime_headers,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.offsets": {
          "pyxfile": "_libs/tslibs/offsets",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.parsing": {
          "pyxfile": "_libs/tslibs/parsing",
          "depends": ["pandas/_libs/src/parser/tokenizer.h"],
          "sources": ["pandas/_libs/src/parser/tokenizer.c"],
      },
      "_libs.tslibs.period": {
          "pyxfile": "_libs/tslibs/period",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.resolution": {
          "pyxfile": "_libs/tslibs/resolution",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.strptime": {
          "pyxfile": "_libs/tslibs/strptime",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.timedeltas": {
          "pyxfile": "_libs/tslibs/timedeltas",
          "include": ts_include,
          "depends": np_datetime_headers,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.timestamps": {
          "pyxfile": "_libs/tslibs/timestamps",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.tslibs.timezones": {"pyxfile": "_libs/tslibs/timezones", "include": []},
      "_libs.tslibs.tzconversion": {
          "pyxfile": "_libs/tslibs/tzconversion",
          "include": ts_include,
          "depends": tseries_depends,
          "sources": np_datetime_sources,
      },
      "_libs.testing": {"pyxfile": "_libs/testing"},
      "_libs.window": {"pyxfile": "_libs/window", "language": "c++", "suffix": ".cpp"},
      "_libs.writers": {"pyxfile": "_libs/writers"},
      "io.sas._sas": {"pyxfile": "io/sas/sas"},
      "io.msgpack._packer": {
          "macros": endian_macro + macros,
          "depends": [
              "pandas/_libs/src/msgpack/pack.h",
              "pandas/_libs/src/msgpack/pack_template.h",
          ],
          "include": ["pandas/_libs/src/msgpack"] + common_include,
          "language": "c++",
          "suffix": ".cpp",
          "pyxfile": "io/msgpack/_packer",
          "subdir": "io/msgpack",
      },
      "io.msgpack._unpacker": {
          "depends": [
              "pandas/_libs/src/msgpack/unpack.h",
              "pandas/_libs/src/msgpack/unpack_define.h",
              "pandas/_libs/src/msgpack/unpack_template.h",
          ],
          "macros": endian_macro + macros,
          "include": ["pandas/_libs/src/msgpack"] + common_include,
          "language": "c++",
          "suffix": ".cpp",
          "pyxfile": "io/msgpack/_unpacker",
          "subdir": "io/msgpack",
      },
  }
  
  extensions = []
  
  for name, data in ext_data.items():
      source_suffix = suffix if suffix == ".pyx" else data.get("suffix", ".c")
  
      sources = [srcpath(data["pyxfile"], suffix=source_suffix, subdir="")]
  
      sources.extend(data.get("sources", []))
  
      include = data.get("include", common_include)
  
      obj = Extension(
          "pandas.{name}".format(name=name),
          sources=sources,
          depends=data.get("depends", []),
          include_dirs=include,
          language=data.get("language", "c"),
          define_macros=data.get("macros", macros),
          extra_compile_args=extra_compile_args,
          extra_link_args=extra_link_args,
      )
  
      extensions.append(obj)
  
  # ----------------------------------------------------------------------
  # ujson
  
  if suffix == ".pyx":
      # undo dumb setuptools bug clobbering .pyx sources back to .c
      for ext in extensions:
          if ext.sources[0].endswith((".c", ".cpp")):
              root, _ = os.path.splitext(ext.sources[0])
              ext.sources[0] = root + suffix
  
  ujson_ext = Extension(
      "pandas._libs.json",
      depends=["pandas/_libs/src/ujson/lib/ultrajson.h"],
      sources=(
          [
              "pandas/_libs/src/ujson/python/ujson.c",
              "pandas/_libs/src/ujson/python/objToJSON.c",
              "pandas/_libs/src/ujson/python/JSONtoObj.c",
              "pandas/_libs/src/ujson/lib/ultrajsonenc.c",
              "pandas/_libs/src/ujson/lib/ultrajsondec.c",
          ]
          + np_datetime_sources
      ),
      include_dirs=[
          "pandas/_libs/src/ujson/python",
          "pandas/_libs/src/ujson/lib",
          "pandas/_libs/src/datetime",
      ],
      extra_compile_args=(["-D_GNU_SOURCE"] + extra_compile_args),
      extra_link_args=extra_link_args,
      define_macros=macros,
  )
  
  
  extensions.append(ujson_ext)
  
  # ----------------------------------------------------------------------
  # util
  # extension for pseudo-safely moving bytes into mutable buffers
  _move_ext = Extension(
      "pandas.util._move",
      depends=[],
      sources=["pandas/util/move.c"],
      define_macros=macros,
      extra_compile_args=extra_compile_args,
      extra_link_args=extra_link_args,
  )
  extensions.append(_move_ext)
  
  # ----------------------------------------------------------------------
  
  
  # The build cache system does string matching below this point.
  # if you change something, be careful.
  
  setup(
      name=DISTNAME,
      maintainer=AUTHOR,
      version=versioneer.get_version(),
      packages=find_packages(include=["pandas", "pandas.*"]),
      package_data={"": ["templates/*", "_libs/*.dll"]},
      ext_modules=maybe_cythonize(extensions, compiler_directives=directives),
      maintainer_email=EMAIL,
      description=DESCRIPTION,
      license=LICENSE,
      cmdclass=cmdclass,
      url=URL,
      download_url=DOWNLOAD_URL,
      project_urls=PROJECT_URLS,
      long_description=LONG_DESCRIPTION,
      classifiers=CLASSIFIERS,
      platforms="any",
      python_requires=">=3.5.3",
      extras_require={
          "test": [
              # sync with setup.cfg minversion & install.rst
              "pytest>=4.0.2",
              "pytest-xdist",
              "hypothesis>=3.58",
          ]
      },
      entry_points={
          "pandas_plotting_backends": [
              "matplotlib = pandas:plotting._matplotlib",
          ],
      },
      **setuptools_kwargs
  )
  