


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       :      Union[str, 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 _lowerCamelCase:
       lowercase_ :	bool     =			True
       lowercase_ :	Optional[str]     =			None
       # Automatically constructed
       lowercase_ :	ClassVar[str]     =			"PIL.Image.Image"
       lowercase_ :	ClassVar[Any]     =			pa.struct({"""bytes""": pa.binary(), """path""": pa.string()}   )
       lowercase_ :	str     =			field(default="""Image""", init=_a, repr=_a   )
       def __call__(					self)       ->   Optional[int]:




           """simple docstring"""

           return self.pa_type
       def 			UpperCamelCase     (					self,      lowerCamelCase)       ->   dict:




           """simple docstring"""

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

           if isinstance(lowerCamelCase,      lowerCamelCase):
               _lowercase       :							List[Any]      		=		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 			UpperCamelCase     (					self,      lowerCamelCase,      lowerCamelCase=None)       ->   "PIL.Image.Image":




           """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:
               _lowercase       :							List[str]      		=		{}

           _lowercase		,				_lowercase       :							Optional[Any]      		=		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):
                       _lowercase       :							Optional[int]      		=		PIL.Image.open(lowerCamelCase)
                   else:
                       _lowercase       :							List[Any]      		=		path.split('::')[-1]
                       try:
                           _lowercase       :							Union[str, Any]      		=		string_to_dict(lowerCamelCase,      config.HUB_DATASETS_URL)['repo_id']
                           _lowercase       :							Any      		=		token_per_repo_id.get(lowerCamelCase)
                       except ValueError:
                           _lowercase       :							Optional[Any]      		=		None
                       with xopen(lowerCamelCase,      'rb',      use_auth_token=lowerCamelCase) as f:
                           _lowercase       :							Optional[Any]      		=		BytesIO(f.read())
                       _lowercase       :							Tuple      		=		PIL.Image.open(bytes_)
           else:
               _lowercase       :							Optional[Any]      		=		PIL.Image.open(BytesIO(bytes_))
           image.load()  # to avoid "Too many open files" errors
           return image
       def 			UpperCamelCase     (					self)       ->   Union["FeatureType", Dict[str, "FeatureType"]]:




           """simple docstring"""

           from .features import Value

           return (
               self
               if self.decode
               else {
                   "bytes": Value('binary'),
                   "path": Value('string'),
               }
           )
       def 			UpperCamelCase     (					self,      lowerCamelCase)       ->   pa.StructArray:




           """simple docstring"""

           if pa.types.is_string(storage.type):
               _lowercase       :							Optional[int]      		=		pa.array([None] * len(lowerCamelCase),      type=pa.binary())
               _lowercase       :							Dict      		=		pa.StructArray.from_arrays([bytes_array, storage],      ['bytes', 'path'],      mask=storage.is_null())
           elif pa.types.is_binary(storage.type):
               _lowercase       :							str      		=		pa.array([None] * len(lowerCamelCase),      type=pa.string())
               _lowercase       :							Any      		=		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:
                   _lowercase       :							List[str]      		=		storage.field('bytes')
               else:
                   _lowercase       :							Any      		=		pa.array([None] * len(lowerCamelCase),      type=pa.binary())
               if storage.type.get_field_index('path') >= 0:
                   _lowercase       :							Optional[int]      		=		storage.field('path')
               else:
                   _lowercase       :							List[Any]      		=		pa.array([None] * len(lowerCamelCase),      type=pa.string())
               _lowercase       :							List[Any]      		=		pa.StructArray.from_arrays([bytes_array, path_array],      ['bytes', 'path'],      mask=storage.is_null())
           elif pa.types.is_list(storage.type):
               _lowercase       :							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(),      )
               _lowercase       :							List[Any]      		=		pa.array([None] * len(lowerCamelCase),      type=pa.string())
               _lowercase       :							str      		=		pa.StructArray.from_arrays(
                   [bytes_array, path_array],      ['bytes', 'path'],      mask=bytes_array.is_null())
           return array_cast(lowerCamelCase,      self.pa_type)




       def 			UpperCamelCase     (					self,      lowerCamelCase)       ->   pa.StructArray:




           """simple docstring"""

           @no_op_if_value_is_null
           def path_to_bytes(lowerCamelCase):
               with xopen(lowerCamelCase,      'rb') as f:
                   _lowercase       :							int      		=		f.read()
               return bytes_

           _lowercase       :							int      		=		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(),      )
           _lowercase       :							List[str]      		=		pa.array(
               [os.path.basename(lowerCamelCase) if path is not None else None for path in storage.field('path').to_pylist()],      type=pa.string(),      )
           _lowercase       :							Union[str, Any]      		=		pa.StructArray.from_arrays([bytes_array, path_array],      ['bytes', 'path'],      mask=bytes_array.is_null())
           return array_cast(lowerCamelCase,      self.pa_type)



def 				UpperCamelCase_(      )    ->						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()
        _lowercase       :							Any      		=		list(set(PIL.Image.OPEN.keys() ) & set(PIL.Image.SAVE.keys() ) )
    return _IMAGE_COMPRESSION_FORMATS



def 				UpperCamelCase_(      lowerCamelCase_ )    ->						bytes:
    _lowercase       :							str      		=		BytesIO()
    if image.format in list_image_compression_formats():
        _lowercase       :							Dict      		=		image.format
    else:
        _lowercase       :							int      		=		'PNG' if image.mode in ['1', 'L', 'LA', 'RGB', 'RGBA'] else 'TIFF'
    image.save(lowerCamelCase_							, format=lowerCamelCase_ )
    return buffer.getvalue()



def 				UpperCamelCase_(      lowerCamelCase_ )    ->						dict:
    if hasattr(lowerCamelCase_							, 'filename' ) and image.filename != "":
        return {"path": image.filename, "bytes": None}
    else:
        return {"path": None, "bytes": image_to_bytes(lowerCamelCase_ )}



def 				UpperCamelCase_(      lowerCamelCase_ )    ->						dict:
    if config.PIL_AVAILABLE:
        import PIL.Image
    else:
        raise ImportError('To support encoding images, please install \'Pillow\'.' )

    _lowercase       :							str      		=		array.dtype
    _lowercase       :							Optional[int]      		=		dtype.byteorder if dtype.byteorder != '=' else _NATIVE_BYTEORDER
    _lowercase       :							Union[str, Any]      		=		dtype.kind
    _lowercase       :							Union[str, Any]      		=		dtype.itemsize

    _lowercase       :							Tuple      		=		None

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



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

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






import random
from typing import Any



def 				UpperCamelCase_(      lowerCamelCase_ )    ->						list[Any]:
    for _ in range(len(lowerCamelCase_ ) ):
        _lowercase       :							Optional[int]      		=		random.randint(0							, len(lowerCamelCase_ ) - 1 )
        _lowercase       :							str      		=		random.randint(0							, len(lowerCamelCase_ ) - 1 )
        _lowercase		,				_lowercase       :							Optional[int]      		=		data[b], data[a]
    return data


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE       :      str												= [0, 1, 2, 3, 4, 5, 6, 7]
 SCREAMING_SNAKE_CASE       :      int												= ["python", "says", "hello", "!"]
 print("Fisher-Yates Shuffle:")
 print("List", integers, strings)
 print("FY Shuffle", fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))


