

"""simple docstring"""



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


SCREAMING_SNAKE_CASE_    :		Optional[List[str]]							     =  None
SCREAMING_SNAKE_CASE_    :		Any							     =  "<" 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
SCREAMING_SNAKE_CASE_    :		Optional[Any]							     =  [
    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     a  :



    """simple docstring"""



    UpperCAmelCase         =    True
    UpperCAmelCase         =    None
    # Automatically constructed
    UpperCAmelCase         =    "PIL.Image.Image"
    UpperCAmelCase         =    pa.struct({"bytes": pa.binary(), "path": pa.string()} )
    UpperCAmelCase         =    field(default="Image",		init=_UpperCAmelCase,		repr=_UpperCAmelCase )

    def __call__(   self:       List[str]				):






         """simple docstring"""


         return self.pa_type

    def  UpperCamelCase		(   self:       Union[str, Any]			,  UpperCamelCase:       Union[str, bytes, dict, np.ndarray, "PIL.Image.Image"]				):






         """simple docstring"""


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

         if isinstance(lowercase_			,  lowercase_				):
              A__								=     np.array(lowercase_				)

         if isinstance(lowercase_			,  lowercase_				):
              return {"path": value, "bytes": None}
         elif isinstance(lowercase_			,  lowercase_				):
              return {"path": None, "bytes": value}
         elif isinstance(lowercase_			,  np.ndarray				):
              # convert the image array to PNG/TIFF bytes
              return encode_np_array(lowercase_				)
         elif isinstance(lowercase_			,  PIL.Image.Image				):
              # convert the PIL image to bytes (default format is PNG/TIFF)
              return encode_pil_image(lowercase_				)
         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  UpperCamelCase		(   self:       int			,  UpperCamelCase:       dict			,  UpperCamelCase:       int=None				):






         """simple docstring"""


         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:
              A__								=     {}

         A__								=     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(lowercase_				):
                        A__								=     PIL.Image.open(lowercase_				)
                   else:
                        A__								=     path.split("""::"""				)[-1]
                        try:
                             A__								=     string_to_dict(lowercase_			,  config.HUB_DATASETS_URL				)["""repo_id"""]
                             A__								=     token_per_repo_id.get(lowercase_				)
                        except ValueError:
                             A__								=     None
                        with xopen(lowercase_			,  """rb"""			,  use_auth_token=lowercase_				) as f:
                             A__								=     BytesIO(f.read()				)
                        A__								=     PIL.Image.open(bytes_				)
         else:
              A__								=     PIL.Image.open(BytesIO(bytes_				)				)
         image.load()  # to avoid "Too many open files" errors
         return image

    def  UpperCamelCase		(   self:       int				):






         """simple docstring"""


         from .features import Value

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

    def  UpperCamelCase		(   self:       List[str]			,  UpperCamelCase:       Union[pa.StringArray, pa.StructArray, pa.ListArray]				):






         """simple docstring"""


         if pa.types.is_string(storage.type				):
              A__								=     pa.array([None] * len(lowercase_				)			,  type=pa.binary()				)
              A__								=     pa.StructArray.from_arrays([bytes_array, storage]			,  ["""bytes""", """path"""]			,  mask=storage.is_null()				)
         elif pa.types.is_binary(storage.type				):
              A__								=     pa.array([None] * len(lowercase_				)			,  type=pa.string()				)
              A__								=     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:
                   A__								=     storage.field("""bytes"""				)
              else:
                   A__								=     pa.array([None] * len(lowercase_				)			,  type=pa.binary()				)
              if storage.type.get_field_index("""path"""				) >= 0:
                   A__								=     storage.field("""path"""				)
              else:
                   A__								=     pa.array([None] * len(lowercase_				)			,  type=pa.string()				)
              A__								=     pa.StructArray.from_arrays([bytes_array, path_array]			,  ["""bytes""", """path"""]			,  mask=storage.is_null()				)
         elif pa.types.is_list(storage.type				):
              A__								=     pa.array(
                  [encode_np_array(np.array(lowercase_				)				)["""bytes"""] if arr is not None else None for arr in storage.to_pylist()]			,  type=pa.binary()			,  )
              A__								=     pa.array([None] * len(lowercase_				)			,  type=pa.string()				)
              A__								=     pa.StructArray.from_arrays(
                  [bytes_array, path_array]			,  ["""bytes""", """path"""]			,  mask=bytes_array.is_null()				)
         return array_cast(lowercase_			,  self.pa_type				)





    def  UpperCamelCase		(   self:       Dict			,  UpperCamelCase:       pa.StructArray				):






         """simple docstring"""


         @no_op_if_value_is_null
         def path_to_bytes(UpperCamelCase:       List[Any]				):
              with xopen(lowercase_			,  """rb"""				) as f:
                   A__								=     f.read()
              return bytes_

         A__								=     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()			,  )
         A__								=     pa.array(
             [os.path.basename(lowercase_				) if path is not None else None for path in storage.field("""path"""				).to_pylist()]			,  type=pa.string()			,  )
         A__								=     pa.StructArray.from_arrays([bytes_array, path_array]			,  ["""bytes""", """path"""]			,  mask=bytes_array.is_null()				)
         return array_cast(lowercase_			,  self.pa_type				)





def        _snake_case   (			):
     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()
          A__								=     list(set(PIL.Image.OPEN.keys()	) & set(PIL.Image.SAVE.keys()	)	)
     return _IMAGE_COMPRESSION_FORMATS





def        _snake_case   (			UpperCAmelCase_     :    "PIL.Image.Image"	):
     A__								=     BytesIO()
     if image.format in list_image_compression_formats():
          A__								=     image.format
     else:
          A__								=     """PNG""" if image.mode in ["""1""", """L""", """LA""", """RGB""", """RGBA"""] else """TIFF"""
     image.save(UpperCAmelCase__    ,      format=UpperCAmelCase__	)
     return buffer.getvalue()





def        _snake_case   (			UpperCAmelCase_     :    "PIL.Image.Image"	):
     if hasattr(UpperCAmelCase__    ,      """filename"""	) and image.filename != "":
          return {"path": image.filename, "bytes": None}
     else:
          return {"path": None, "bytes": image_to_bytes(UpperCAmelCase__	)}





def        _snake_case   (			UpperCAmelCase_     :    np.ndarray	):
     if config.PIL_AVAILABLE:
          import PIL.Image
     else:
          raise ImportError("""To support encoding images, please install 'Pillow'."""	)

     A__								=     array.dtype
     A__								=     dtype.byteorder if dtype.byteorder != """=""" else _NATIVE_BYTEORDER
     A__								=     dtype.kind
     A__								=     dtype.itemsize

     A__								=     None

     # Multi-channel array case (only np.dtype("|u1") is allowed)
     if array.shape[2:]:
          A__								=     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:
          A__								=     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:
               A__								=     dtype_byteorder + dtype_kind + str(UpperCAmelCase__	)
               A__								=     np.dtype(UpperCAmelCase__	)
               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}"""	)
     A__								=     PIL.Image.fromarray(array.astype(UpperCAmelCase__	)	)
     return {"path": None, "bytes": image_to_bytes(UpperCAmelCase__	)}





def        _snake_case   (			UpperCAmelCase_     :    Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]]	):
     if config.PIL_AVAILABLE:
          import PIL.Image
     else:
          raise ImportError("""To support encoding images, please install 'Pillow'."""	)

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







'''simple docstring'''




from urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url




@pytest.mark.parametrize("""repo_id"""      ,      ["""canonical_dataset_name""", """org-name/dataset-name"""] )
@pytest.mark.parametrize("""path"""      ,      ["""filename.csv""", """filename with blanks.csv"""] )
@pytest.mark.parametrize("""revision"""      ,      [None, """v2"""] )
def 							lowerCamelCase	(      UpperCAmelCase__       :					int      ,      UpperCAmelCase__       :					Optional[int]      ,      UpperCAmelCase__       :					Optional[int] )			->      Optional[int]:
							lowercase_					:			Union[str, Any]										=       hf_hub_url(repo_id=UpperCAmelCase__      ,      path=UpperCAmelCase__      ,      revision=UpperCAmelCase__ )
							assert url == F'''https://huggingface.co/datasets/{repo_id}/resolve/{revision or 'main'}/{quote(UpperCAmelCase__ )}'''





