






import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen
from ..table import array_cast
from ..utils.file_utils import is_local_path
from ..utils.py_utils import first_non_null_value, no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
   import PIL.Image

   from .features import FeatureType


A_		:		Union[str, Any]		     =			None
A_		:		str		     =			'<' if sys.byteorder == 'little' else '>'
# Origin: https://github.com/python-pillow/Pillow/blob/698951e19e19972aeed56df686868f1329981c12/src/PIL/Image.py#L3126 minus "|i1" which values are not preserved correctly when saving and loading an image
A_		:		str		     =			[
    np.dtype('|b1'),
    np.dtype('|u1'),
    np.dtype('<u2'),
    np.dtype('>u2'),
    np.dtype('<i2'),
    np.dtype('>i2'),
    np.dtype('<u4'),
    np.dtype('>u4'),
    np.dtype('<i4'),
    np.dtype('>i4'),
    np.dtype('<f4'),
    np.dtype('>f4'),
    np.dtype('<f8'),
    np.dtype('>f8'),
]





@dataclass
class     _lowerCAmelCase:





       """simple docstring"""







       a    :		bool									=True
       a    :		Optional[str]									=None
       # Automatically constructed
       a    :		ClassVar[str]									="PIL.Image.Image"
       a    :		ClassVar[Any]									=pa.struct({'''bytes''': pa.binary(), '''path''': pa.string()} )
       a    :		str									=field(default='''Image'''							,     init=__UpperCamelCase							,     repr=__UpperCamelCase )





       def __call__( self							):
         return self.pa_type





       def       _a   ( self  ,      _lowerCamelCase							):
         if config.PIL_AVAILABLE:
           import PIL.Image
         else:
           raise ImportError('To support encoding images, please install \'Pillow\'.'							)

         if isinstance(_lowerCAmelCase  ,      _lowerCAmelCase							):
           UpperCamelCase_: str   				=    np.array(_lowerCAmelCase							)

         if isinstance(_lowerCAmelCase  ,      _lowerCAmelCase							):
           return {"path": value, "bytes": None}
         elif isinstance(_lowerCAmelCase  ,      _lowerCAmelCase							):
           return {"path": None, "bytes": value}
         elif isinstance(_lowerCAmelCase  ,      np.ndarray							):
           # convert the image array to PNG/TIFF bytes
           return encode_np_array(_lowerCAmelCase							)
         elif isinstance(_lowerCAmelCase  ,      PIL.Image.Image							):
           # convert the PIL image to bytes (default format is PNG/TIFF)
           return encode_pil_image(_lowerCAmelCase							)
         elif value.get('path'							) is not None and os.path.isfile(value['path']							):
           # we set "bytes": None to not duplicate the data if they're already available locally
           return {"bytes": None, "path": value.get('path'							)}
         elif value.get('bytes'							) is not None or value.get('path'							) is not None:
           # store the image bytes, and path is used to infer the image format using the file extension
           return {"bytes": value.get('bytes'							), "path": value.get('path'							)}
         else:
           raise ValueError(
               f'''An image sample should have one of \'path\' or \'bytes\' but they are missing or None in {value}.'''							)





       def       _a   ( self  ,      _lowerCamelCase  ,      _lowerCamelCase=None							):
         if not self.decode:
           raise RuntimeError('Decoding is disabled for this feature. Please use Image(decode=True) instead.'							)

         if config.PIL_AVAILABLE:
           import PIL.Image
         else:
           raise ImportError('To support decoding images, please install \'Pillow\'.'							)

         if token_per_repo_id is None:
           UpperCamelCase_: Tuple   				=    {}

         UpperCamelCase_: str   				=    value["""path"""], value["""bytes"""]
         if bytes_ is None:
           if path is None:
             raise ValueError(f'''An image should have one of \'path\' or \'bytes\' but both are None in {value}.'''							)
           else:
             if is_local_path(_lowerCAmelCase							):
               UpperCamelCase_: str   				=    PIL.Image.open(_lowerCAmelCase							)
             else:
               UpperCamelCase_: List[str]   				=    path.split('::'							)[-1]
               try:
                 UpperCamelCase_: Dict   				=    string_to_dict(_lowerCAmelCase  ,      config.HUB_DATASETS_URL							)["""repo_id"""]
                 UpperCamelCase_: int   				=    token_per_repo_id.get(_lowerCAmelCase							)
               except ValueError:
                 UpperCamelCase_: List[Any]   				=    None
               with xopen(_lowerCAmelCase  ,      'rb'  ,      use_auth_token=_lowerCAmelCase							) as f:
                 UpperCamelCase_: Union[str, Any]   				=    BytesIO(f.read()							)
               UpperCamelCase_: Dict   				=    PIL.Image.open(bytes_							)
         else:
           UpperCamelCase_: Optional[Any]   				=    PIL.Image.open(BytesIO(bytes_							)							)
         image.load()  # to avoid "Too many open files" errors
         return image





       def       _a   ( self							):
         from .features import Value

         return (
             self
             if self.decode
             else {
                 "bytes": Value('binary'							),
                 "path": Value('string'							),
             }
         )





       def       _a   ( self  ,      _lowerCamelCase							):
         if pa.types.is_string(storage.type							):
           UpperCamelCase_: Optional[Any]   				=    pa.array([None] * len(_lowerCAmelCase							)  ,      type=pa.binary()							)
           UpperCamelCase_: Any   				=    pa.StructArray.from_arrays([bytes_array, storage]  ,      ['bytes', 'path']  ,      mask=storage.is_null()							)
         elif pa.types.is_binary(storage.type							):
           UpperCamelCase_: Optional[Any]   				=    pa.array([None] * len(_lowerCAmelCase							)  ,      type=pa.string()							)
           UpperCamelCase_: List[str]   				=    pa.StructArray.from_arrays([storage, path_array]  ,      ['bytes', 'path']  ,      mask=storage.is_null()							)
         elif pa.types.is_struct(storage.type							):
           if storage.type.get_field_index('bytes'							) >= 0:
             UpperCamelCase_: List[str]   				=    storage.field('bytes'							)
           else:
             UpperCamelCase_: List[Any]   				=    pa.array([None] * len(_lowerCAmelCase							)  ,      type=pa.binary()							)
           if storage.type.get_field_index('path'							) >= 0:
             UpperCamelCase_: Optional[int]   				=    storage.field('path'							)
           else:
             UpperCamelCase_: int   				=    pa.array([None] * len(_lowerCAmelCase							)  ,      type=pa.string()							)
           UpperCamelCase_: Tuple   				=    pa.StructArray.from_arrays([bytes_array, path_array]  ,      ['bytes', 'path']  ,      mask=storage.is_null()							)
         elif pa.types.is_list(storage.type							):
           UpperCamelCase_: Optional[Any]   				=    pa.array(
               [encode_np_array(np.array(_lowerCAmelCase							)							)['bytes'] if arr is not None else None for arr in storage.to_pylist()]  ,      type=pa.binary()  ,      )
           UpperCamelCase_: Optional[int]   				=    pa.array([None] * len(_lowerCAmelCase							)  ,      type=pa.string()							)
           UpperCamelCase_: List[str]   				=    pa.StructArray.from_arrays(
               [bytes_array, path_array]  ,      ['bytes', 'path']  ,      mask=bytes_array.is_null()							)
         return array_cast(_lowerCAmelCase  ,      self.pa_type							)





       def       _a   ( self  ,      _lowerCamelCase							):

         @no_op_if_value_is_null
         def path_to_bytes(_lowerCamelCase							):
           with xopen(_lowerCAmelCase  ,      'rb'							) as f:
             UpperCamelCase_: Optional[int]   				=    f.read()
           return bytes_

         UpperCamelCase_: Tuple   				=    pa.array(
             [
                 (path_to_bytes(x['path']							) if x['bytes'] is None else x['bytes']) if x is not None else None
                 for x in storage.to_pylist()
             ]  ,      type=pa.binary()  ,      )
         UpperCamelCase_: Optional[Any]   				=    pa.array(
             [os.path.basename(_lowerCAmelCase							) if path is not None else None for path in storage.field('path'							).to_pylist()]  ,      type=pa.string()  ,      )
         UpperCamelCase_: Any   				=    pa.StructArray.from_arrays([bytes_array, path_array]  ,      ['bytes', 'path']  ,      mask=bytes_array.is_null()							)
         return array_cast(_lowerCAmelCase  ,      self.pa_type							)







def   snake_case ()	->    List[str]:
  if config.PIL_AVAILABLE:
    import PIL.Image
  else:
    raise ImportError('To support encoding images, please install \'Pillow\'.'  )

  global _IMAGE_COMPRESSION_FORMATS
  if _IMAGE_COMPRESSION_FORMATS is None:
    PIL.Image.init()
    UpperCamelCase_: Optional[Any]   				=    list(set(PIL.Image.OPEN.keys()  ) & set(PIL.Image.SAVE.keys()  )  )
  return _IMAGE_COMPRESSION_FORMATS

def   snake_case (UpperCAmelCase__  )	->    List[Any]:
  UpperCamelCase_: List[Any]   				=    BytesIO()
  if image.format in list_image_compression_formats():
    UpperCamelCase_: Union[str, Any]   				=    image.format
  else:
    UpperCamelCase_: List[Any]   				=    """PNG""" if image.mode in ["""1""", """L""", """LA""", """RGB""", """RGBA"""] else """TIFF"""
  image.save(__SCREAMING_SNAKE_CASE     ,   format=__SCREAMING_SNAKE_CASE  )
  return buffer.getvalue()

def   snake_case (UpperCAmelCase__  )	->    Dict:
  if hasattr(__SCREAMING_SNAKE_CASE     ,   'filename'  ) and image.filename != "":
    return {"path": image.filename, "bytes": None}
  else:
    return {"path": None, "bytes": image_to_bytes(__SCREAMING_SNAKE_CASE  )}

def   snake_case (UpperCAmelCase__  )	->    Union[str, Any]:
  if config.PIL_AVAILABLE:
    import PIL.Image
  else:
    raise ImportError('To support encoding images, please install \'Pillow\'.'  )

  UpperCamelCase_: List[Any]   				=    array.dtype
  UpperCamelCase_: List[Any]   				=    dtype.byteorder if dtype.byteorder != """=""" else _NATIVE_BYTEORDER
  UpperCamelCase_: Dict   				=    dtype.kind
  UpperCamelCase_: Union[str, Any]   				=    dtype.itemsize

  UpperCamelCase_: Tuple   				=    None

  # Multi-channel array case (only np.dtype("|u1") is allowed)
  if array.shape[2:]:
    UpperCamelCase_: int   				=    np.dtype('|u1'  )
    if dtype_kind not in ["u", "i"]:
      raise TypeError(
          F'''Unsupported array dtype {dtype} for image encoding. Only {dest_dtype} is supported for multi-channel arrays.'''  )
    if dtype is not dest_dtype:
      warnings.warn(F'''Downcasting array dtype {dtype} to {dest_dtype} to be compatible with \'Pillow\''''  )
    # Exact match
  elif dtype in _VALID_IMAGE_ARRAY_DTPYES:
    UpperCamelCase_: List[str]   				=    dtype
  else:  # Downcast the type within the kind (np.can_cast(from_type, to_type, casting="same_kind") doesn't behave as expected, so do it manually)
    while dtype_itemsize >= 1:
      UpperCamelCase_: int   				=    dtype_byteorder + dtype_kind + str(__SCREAMING_SNAKE_CASE  )
      UpperCamelCase_: Any   				=    np.dtype(__SCREAMING_SNAKE_CASE  )
      if dest_dtype in _VALID_IMAGE_ARRAY_DTPYES:
        warnings.warn(F'''Downcasting array dtype {dtype} to {dest_dtype} to be compatible with \'Pillow\''''  )
        break
      else:
        dtype_itemsize //= 2

  if dest_dtype is None:
    raise TypeError(
        F'''Cannot convert dtype {dtype} to a valid image dtype. Valid image dtypes: {_VALID_IMAGE_ARRAY_DTPYES}'''  )
  UpperCamelCase_: Optional[int]   				=    PIL.Image.fromarray(array.astype(__SCREAMING_SNAKE_CASE  )  )
  return {"path": None, "bytes": image_to_bytes(__SCREAMING_SNAKE_CASE  )}

def   snake_case (UpperCAmelCase__  )	->    List[Any]:
  if config.PIL_AVAILABLE:
    import PIL.Image
  else:
    raise ImportError('To support encoding images, please install \'Pillow\'.'  )

  if objs:
    UpperCamelCase_: Any   				=    first_non_null_value(__SCREAMING_SNAKE_CASE  )
    if isinstance(__SCREAMING_SNAKE_CASE     ,   __SCREAMING_SNAKE_CASE  ):
      return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
    if isinstance(__SCREAMING_SNAKE_CASE     ,   np.ndarray  ):
      UpperCamelCase_: int   				=    no_op_if_value_is_null(__SCREAMING_SNAKE_CASE  )
      return [obj_to_image_dict_func(__SCREAMING_SNAKE_CASE  ) for obj in objs]
    elif isinstance(__SCREAMING_SNAKE_CASE     ,   PIL.Image.Image  ):
      UpperCamelCase_: List[str]   				=    no_op_if_value_is_null(__SCREAMING_SNAKE_CASE  )
      return [obj_to_image_dict_func(__SCREAMING_SNAKE_CASE  ) for obj in objs]
    else:
      return objs
  else:
    return objs







import os


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
A_		:		List[str]		     =			'.'


if __name__ == "__main__":
   A_		:		Dict		     =			os.path.join(REPO_PATH, 'utils/documentation_tests.txt')
   A_		:		Dict		     =			[]
   A_		:		Optional[Any]		     =			[]
   with open(doctest_file_path) as fp:
      for line in fp:
         A_		:		Tuple		     =			line.strip()
         A_		:		Any		     =			os.path.join(REPO_PATH, line)
         if not (os.path.isfile(path) or os.path.isdir(path)):
            non_existent_paths.append(line)
         all_paths.append(path)
   if len(non_existent_paths) > 0:
      A_		:		str		     =			'\n'.join(non_existent_paths)
      raise ValueError(F'''`utils/documentation_tests.txt` contains non-existent paths:\n{non_existent_paths}''')
   if all_paths != sorted(all_paths):
      raise ValueError('Files in `utils/documentation_tests.txt` are not in alphabetical order.')