

"""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


_A							=  None
_A							=  """<""" 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							=  [
    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'''







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



  def __call__(self	):


        """simple docstring"""

        return self.pa_type



  def  _a      (self							,       _lowerCamelCase	):


        """simple docstring"""

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

        if isinstance(_lowerCamelCase							,       _lowerCamelCase	):
              UpperCAmelCase__			:							Optional[int]							=    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	):


        """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:
              UpperCAmelCase__			:							List[Any]							=    {}

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



  def  _a      (self	):


        """simple docstring"""

        from .features import Value

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



  def  _a      (self							,       _lowerCamelCase	):


        """simple docstring"""

        if pa.types.is_string(storage.type	):
              UpperCAmelCase__			:							Any							=    pa.array([None] * len(_lowerCamelCase	)							,       type=pa.binary()	)
              UpperCAmelCase__			:							Dict							=    pa.StructArray.from_arrays([bytes_array, storage]							,       ["""bytes""", """path"""]							,       mask=storage.is_null()	)
        elif pa.types.is_binary(storage.type	):
              UpperCAmelCase__			:							Optional[int]							=    pa.array([None] * len(_lowerCamelCase	)							,       type=pa.string()	)
              UpperCAmelCase__			:							Optional[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:
                    UpperCAmelCase__			:							int							=    storage.field("""bytes"""	)
              else:
                    UpperCAmelCase__			:							Optional[Any]							=    pa.array([None] * len(_lowerCamelCase	)							,       type=pa.binary()	)
              if storage.type.get_field_index("""path"""	) >= 0:
                    UpperCAmelCase__			:							Optional[Any]							=    storage.field("""path"""	)
              else:
                    UpperCAmelCase__			:							Optional[int]							=    pa.array([None] * len(_lowerCamelCase	)							,       type=pa.string()	)
              UpperCAmelCase__			:							Union[str, Any]							=    pa.StructArray.from_arrays([bytes_array, path_array]							,       ["""bytes""", """path"""]							,       mask=storage.is_null()	)
        elif pa.types.is_list(storage.type	):
              UpperCAmelCase__			:							int							=    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__			:							Union[str, Any]							=    pa.array([None] * len(_lowerCamelCase	)							,       type=pa.string()	)
              UpperCAmelCase__			:							Optional[Any]							=    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	):


        """simple docstring"""

        @no_op_if_value_is_null
        def path_to_bytes(_lowerCamelCase	):
              with xopen(_lowerCamelCase							,       """rb"""	) as f:
                    UpperCAmelCase__			:							List[str]							=    f.read()
              return bytes_

        UpperCAmelCase__			:							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()							,       )
        UpperCAmelCase__			:							Dict							=    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__			:							Tuple							=    pa.StructArray.from_arrays([bytes_array, path_array]							,       ["""bytes""", """path"""]							,       mask=bytes_array.is_null()	)
        return array_cast(_lowerCamelCase							,       self.pa_type	)




def 					a__						(						)	-> 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__			:							Union[str, Any]							=    list(set(PIL.Image.OPEN.keys()    ) & set(PIL.Image.SAVE.keys()    )    )
      return _IMAGE_COMPRESSION_FORMATS




def 					a__						(						lowerCAmelCase    )	-> bytes:
      UpperCAmelCase__			:							Dict							=    BytesIO()
      if image.format in list_image_compression_formats():
            UpperCAmelCase__			:							Any							=    image.format
      else:
            UpperCAmelCase__			:							Tuple							=    """PNG""" if image.mode in ["""1""", """L""", """LA""", """RGB""", """RGBA"""] else """TIFF"""
      image.save(lowerCAmelCase			,	format=lowerCAmelCase    )
      return buffer.getvalue()




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

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

      UpperCAmelCase__			:							List[Any]							=    None

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





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

      if objs:
            UpperCAmelCase__					,		UpperCAmelCase__			:							List[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    ):
                  UpperCAmelCase__			:							Optional[Any]							=    no_op_if_value_is_null(lowerCAmelCase    )
                  return [obj_to_image_dict_func(lowerCAmelCase    ) for obj in objs]
            elif isinstance(lowerCAmelCase			,	PIL.Image.Image    ):
                  UpperCAmelCase__			:							Union[str, Any]							=    no_op_if_value_is_null(lowerCAmelCase    )
                  return [obj_to_image_dict_func(lowerCAmelCase    ) for obj in objs]
            else:
                  return objs
      else:
            return objs




"""simple docstring"""
import math




def 					a__						(						lowerCAmelCase    )	-> list[int]:
      UpperCAmelCase__			:							Optional[int]							=    []
      UpperCAmelCase__			:							Union[str, Any]							=    2
      UpperCAmelCase__			:							List[Any]							=    int(math.sqrt(lowerCAmelCase    )    )  # Size of every segment
      UpperCAmelCase__			:							Dict							=    [True] * (end + 1)
      UpperCAmelCase__			:							str							=    []

      while start <= end:
            if temp[start] is True:
                  in_prime.append(lowerCAmelCase    )
                  for i in range(start * start			,	end + 1			,	lowerCAmelCase    ):
                        UpperCAmelCase__			:							Optional[Any]							=    False
            start += 1
      prime += in_prime

      UpperCAmelCase__			:							Optional[Any]							=    end + 1
      UpperCAmelCase__			:							Dict							=    min(2 * end			,	lowerCAmelCase    )

      while low <= n:
            UpperCAmelCase__			:							Optional[int]							=    [True] * (high - low + 1)
            for each in in_prime:
                  UpperCAmelCase__			:							Optional[int]							=    math.floor(low / each    ) * each
                  if t < low:
                        t += each

                  for j in range(lowerCAmelCase			,	high + 1			,	lowerCAmelCase    ):
                        UpperCAmelCase__			:							int							=    False

            for j in range(len(lowerCAmelCase    )    ):
                  if temp[j] is True:
                        prime.append(j + low    )

            UpperCAmelCase__			:							Dict							=    high + 1
            UpperCAmelCase__			:							int							=    min(high + end			,	lowerCAmelCase    )

      return prime





print(sieve(10**6))

