text: # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
  #
  # This source code is licensed under the MIT license found in the
  # LICENSE file in the root directory of this source tree.
  
  import os
  import sys
  import shutil
  import tempfile
  import subprocess
  from typing import List, Any, Iterable, Tuple, Union, Optional, Dict, Generic, TypeVar
  from pathlib import Path
  import numpy as np
  from ..common.typetools import ArrayLike
  
  
  X = TypeVar("X")
  
  
  class Variable(Generic[X]):
  
      @property
      def dimension(self) -> int:
          raise NotImplementedError
  
      @property
      def continuous(self) -> bool:
          return True
  
      @property
      def noisy(self) -> bool:
          return False
  
      def argument_to_data(self, arg: X) -> ArrayLike:
          raise NotImplementedError
  
      def data_to_argument(self, data: ArrayLike, random: Union[bool, np.random.RandomState] = True) -> X:
          """Converts data into arguments
  
          Parameters
          ----------
          data: np.ndarray
              data to convert
          random: bool or np.random.RandomState
              either a RandomState to pull values from, or True for pulling values on the default random state,
              or False to get a deterministic behavior
          """
          raise NotImplementedError
  
      def get_summary(self, data: ArrayLike) -> str:
          output = self.data_to_argument(data, random=False)
          d = data if len(data) > 1 else data[0]
          return f"Value {output}, from data: {d}"
  
      def __eq__(self, other: Any) -> bool:
          return bool(self.__class__ == other.__class__ and self.__dict__ == other.__dict__)
  
      def __repr__(self) -> str:
          args = ", ".join(f"{x}={y}" for x, y in sorted(self.__dict__.items()) if not x.startswith("_"))
          return f"{self.__class__.__name__}({args})"
  
      def _short_repr(self) -> str:
          raise NotImplementedError
  
      def __format__(self, format_spec: str) -> str:
          if format_spec == "short":
              return self._short_repr()
          elif format_spec == "display":
              # ugly hack below, but simplifies code a lot
              return self._short_repr() if self.__class__.__name__ == "_Constant" else repr(self)
          return repr(self)
  
  
  def split_data(data: ArrayLike, variables: Iterable[Variable[Any]]) -> List[np.ndarray]:
      """Splits data according to the data requirements of the variables
      """
      # this functions should be tested
      data = np.array(data).ravel()
      variables = list(variables)  # make sure it is not an iterator
      total = sum(t.dimension for t in variables)
      assert len(data) == total, f"Expected {total} values but got {len(data)}"
      splitted_data: List[np.ndarray] = []
      variables = list(variables)  # make sure it is not an iterator
      start, end = 0, 0
      for variable in variables:
          end = start + variable.dimension
          splitted_data.append(data[start: end])
          start = end
      assert end == len(data), f"Finished at {end} but expected {len(data)}"
      return splitted_data
  
  
  def process_variables(variables: Iterable[Variable[Any]], data: ArrayLike,
                        random: Union[bool, np.random.RandomState] = True) -> Tuple[Any, ...]:
      # this function should be removed (but tests of split_data are currently
      # made through this function)
      variables = list(variables)
      splitted_data = split_data(data, variables)
      return tuple([variable.data_to_argument(d, random=random) for variable, d in zip(variables, splitted_data)])
  
  
  class TemporaryDirectoryCopy(tempfile.TemporaryDirectory):  # type: ignore
      """Creates a full copy of a directory inside a temporary directory
      This class can be used as TemporaryDirectory but:
      - the created copy path is available through the copyname attribute
      - the contextmanager returns the clean copy path
      - the directory where the temporary directory will be created
        can be controlled through the CLEAN_COPY_DIRECTORY environment
        variable
      """
  
      key = "CLEAN_COPY_DIRECTORY"
  
      @classmethod
      def set_clean_copy_environment_variable(cls, directory: Union[Path, str]) -> None:
          """Sets the CLEAN_COPY_DIRECTORY environment variable in
          order for subsequent calls to use this directory as base for the
          copies.
          """
          assert Path(directory).exists(), "Directory does not exist"
          os.environ[cls.key] = str(directory)
  
      # pylint: disable=redefined-builtin
      def __init__(self, source: Union[Path, str], dir: Optional[Union[Path, str]] = None) -> None:
          if dir is None:
              dir = os.environ.get(self.key, None)
          super().__init__(prefix="tmp_clean_copy_", dir=dir)
          self.copyname = Path(self.name) / Path(source).name
          shutil.copytree(str(source), str(self.copyname))
  
      def __enter__(self) -> Path:
          super().__enter__()
          return self.copyname
  
  
  class FailedJobError(RuntimeError):
      """Job failed during processing
      """
  
  
  class CommandFunction:
      """Wraps a command as a function in order to make sure it goes through the
      pipeline and notify when it is finished.
      The output is a string containing everything that has been sent to stdout
  
      Parameters
      ----------
      command: list
          command to run, as a list
      verbose: bool
          prints the command and stdout at runtime
      cwd: Path/str
          path to the location where the command must run from
  
      Returns
      -------
      str
         Everything that has been sent to stdout
      """
  
      def __init__(self, command: List[str], verbose: bool = False, cwd: Optional[Union[str, Path]] = None,
                   env: Optional[Dict[str, str]] = None) -> None:
          if not isinstance(command, list):
              raise TypeError("The command must be provided as a list")
          self.command = command
          self.verbose = verbose
          self.cwd = None if cwd is None else str(cwd)
          self.env = env
  
      def __call__(self, *args: Any, **kwargs: Any) -> str:
          """Call the cammand line with addidional arguments
          The keyword arguments will be sent as --{key}={val}
          The logs are bufferized. They will be printed if the job fails, or sent as output of the function
          Errors are provided with the internal stderr
          """
          # TODO make the following command more robust (probably fails in multiple cases)
          full_command = self.command + [str(x) for x in args] + ["--{}={}".format(x, y) for x, y in kwargs.items()]
          if self.verbose:
              print(f"The following command is sent: {full_command}")
          outlines: List[str] = []
          with subprocess.Popen(full_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
                                shell=False, cwd=self.cwd, env=self.env) as process:
              try:
                  for line in iter(process.stdout.readline, ''):
                      if not line:
                          break
                      outlines.append(line.decode().strip())  # type: ignore
                      if self.verbose:
                          print(outlines[-1], flush=True)
              except Exception:  # pylint: disable=broad-except
                  process.kill()
                  process.wait()
                  raise FailedJobError("Job got killed for an unknown reason.")
              stderr = process.communicate()[1]  # we already got stdout
              stdout = "\n".join(outlines)
              retcode = process.poll()
              if stderr and (retcode or self.verbose):
                  print(stderr.decode(), file=sys.stderr)
              if retcode:
                  subprocess_error = subprocess.CalledProcessError(retcode, process.args, output=stdout, stderr=stderr)
                  raise FailedJobError(stderr.decode()) from subprocess_error
          return stdout
  