





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





   def __call__(			self   )					->	Optional[int]:
      """simple docstring"""





      return self.pa_type





   def 						_snake_case			(			self       ,      snake_case   )					->	dict:
      """simple docstring"""





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

      if isinstance(snake_case       ,      snake_case   ):
         a__						:    List[str]   		=	np.array(snake_case   )

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

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





   def 						_snake_case			(			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 						_snake_case			(			self       ,      snake_case   )					->	pa.StructArray:
      """simple docstring"""





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





   def 						_snake_case			(			self       ,      snake_case   )					->	pa.StructArray:
      """simple docstring"""





      @no_op_if_value_is_null
      def path_to_bytes(snake_case   ):
         with xopen(snake_case       ,      "rb"   ) as f:
            a__						:    Optional[Any]   		=	f.read()
         return bytes_

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







def    _A	(   ):
   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__						:    Dict   		=	list(set(PIL.Image.OPEN.keys() ) & set(PIL.Image.SAVE.keys() ) )
   return _IMAGE_COMPRESSION_FORMATS






def    _A	(   lowerCamelCase ):
   a__						:    int   		=	BytesIO()
   if image.format in list_image_compression_formats():
      a__						:    Tuple   		=	image.format
   else:
      a__						:    int   		=	"PNG" if image.mode in ["1", "L", "LA", "RGB", "RGBA"] else "TIFF"
   image.save(lowerCamelCase				,			format=lowerCamelCase )
   return buffer.getvalue()






def    _A	(   lowerCamelCase ):
   if hasattr(lowerCamelCase				,			"filename" ) and image.filename != "":
      return {"path": image.filename, "bytes": None}
   else:
      return {"path": None, "bytes": image_to_bytes(lowerCamelCase )}






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

   a__						:    List[Any]   		=	array.dtype
   a__						:    Tuple   		=	dtype.byteorder if dtype.byteorder != "=" else _NATIVE_BYTEORDER
   a__						:    Any   		=	dtype.kind
   a__						:    List[str]   		=	dtype.itemsize

   a__						:    List[str]   		=	None

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






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

   if objs:
      a__		,  a__						:    int   		=	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 ):
         a__						:    Tuple   		=	no_op_if_value_is_null(lowerCamelCase )
         return [obj_to_image_dict_func(lowerCamelCase ) for obj in objs]
      elif isinstance(lowerCamelCase				,			PIL.Image.Image ):
         a__						:    Optional[int]   		=	no_op_if_value_is_null(lowerCamelCase )
         return [obj_to_image_dict_func(lowerCamelCase ) for obj in objs]
      else:
         return objs
   else:
      return objs








# Function to print upper half of diamond (pyramid)






def    _A	(   lowerCamelCase ):
   for i in range(0				,			lowerCamelCase ):
      for _ in range(0				,			n - i - 1 ):  # printing spaces
         print(" "				,			end="" )
      for _ in range(0				,			i + 1 ):  # printing stars
         print("* "				,			end="" )
      print()






def    _A	(   lowerCamelCase ):
   for i in range(lowerCamelCase				,			0				,			-1 ):
      for _ in range(lowerCamelCase				,			0				,			-1 ):  # printing stars
         print("* "				,			end="" )
      print()
      for _ in range(n - i + 1				,			0				,			-1 ):  # printing spaces
         print(" "				,			end="" )






def    _A	(   lowerCamelCase ):
   if n <= 0:
      print("       ...       ....        nothing printing :(" )
      return
   floyd(lowerCamelCase )  # upper half
   reverse_floyd(lowerCamelCase )  # lower half


if __name__ == "__main__":
  print(R"""| /\ | |- |  |-  |--| |\  /| |-""")
  print(R"""|/  \| |- |_ |_  |__| | \/ | |_""")
  SCREAMING_SNAKE_CASE__							:      Dict         =    1
  while K:
    SCREAMING_SNAKE_CASE__							:      str         =    int(input("""enter the number and , and see the magic : """))
    print()
    pretty_print(user_number)
    SCREAMING_SNAKE_CASE__							:      Tuple         =    int(input("""press 0 to exit... and 1 to continue..."""))

  print("""Good Bye...""")

