


"""simple docstring"""


A  :     List[str]    					=    8.3_144_598


def _lowerCamelCase			(	_UpperCamelCase					,				_UpperCamelCase   ):

			'''simple docstring'''




			if temperature < 0:
						raise Exception("Temperature cannot be less than 0 K"   )
			if molar_mass <= 0:
						raise Exception("Molar mass cannot be less than or equal to 0 kg/mol"   )
			else:
						return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
	import doctest

	# run doctest
	doctest.testmod()

	# example
	A  :     List[Any]    					=    3_0_0
	A  :     Dict    					=    2_8
	A  :     Optional[int]    					=    rms_speed_of_molecule(temperature, molar_mass)
	print(f'''Vrms of Nitrogen gas at 300 K is {vrms} m/s''')








"""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  :     Optional[List[str]]    					=    None
A  :     Optional[int]    					=    "<" 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  :     int    					=    [
    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 						_UpperCamelCase						:
							'''simple docstring'''







							__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=lowerCAmelCase__ ,repr=lowerCAmelCase__	)

							def __call__(  self			):
										return self.pa_type

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

										if isinstance(__a					,     __a			):
													__lowerCAmelCase       					=    np.array(__a			)

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

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

							def     snake_case       (  self			):
										from .features import Value

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

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



							def     snake_case       (  self					,     __a			):

										@no_op_if_value_is_null
										def path_to_bytes(__a			):
													with xopen(__a					,     "rb"			) as f:
																__lowerCAmelCase       					=    f.read()
													return bytes_

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


def _lowerCamelCase			(	):

			'''simple docstring'''




			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()
						__lowerCAmelCase       					=    list(set(PIL.Image.OPEN.keys()   ) & set(PIL.Image.SAVE.keys()   )   )
			return _IMAGE_COMPRESSION_FORMATS


def _lowerCamelCase			(	_UpperCamelCase   ):

			'''simple docstring'''




			__lowerCAmelCase       					=    BytesIO()
			if image.format in list_image_compression_formats():
						__lowerCAmelCase       					=    image.format
			else:
						__lowerCAmelCase       					=    "PNG" if image.mode in ["1", "L", "LA", "RGB", "RGBA"] else "TIFF"
			image.save(_UpperCamelCase					,				format=_UpperCamelCase   )
			return buffer.getvalue()


def _lowerCamelCase			(	_UpperCamelCase   ):

			'''simple docstring'''




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


def _lowerCamelCase			(	_UpperCamelCase   ):

			'''simple docstring'''




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

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

			__lowerCAmelCase       					=    None

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


def _lowerCamelCase			(	_UpperCamelCase   ):

			'''simple docstring'''




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

			if objs:
						__lowerCAmelCase					,			__lowerCAmelCase       					=    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   ):
									__lowerCAmelCase       					=    no_op_if_value_is_null(_UpperCamelCase   )
									return [obj_to_image_dict_func(_UpperCamelCase   ) for obj in objs]
						elif isinstance(_UpperCamelCase					,				PIL.Image.Image   ):
									__lowerCAmelCase       					=    no_op_if_value_is_null(_UpperCamelCase   )
									return [obj_to_image_dict_func(_UpperCamelCase   ) for obj in objs]
						else:
									return objs
			else:
						return objs




