





'''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   : List[str]             =			'<' 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   : Union[str, 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       :
					_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=__UpperCAmelCase     ,							repr=__UpperCAmelCase  )


					def __call__(					self	:  Tuple       ):





											'''simple docstring'''





											return self.pa_type


					def    SCREAMING_SNAKE_CASE_		(					self	:  List[str]       ,     __snake_case	:  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(__snake_case       ,     __snake_case       ):
																	_snake_case:   Dict  					=		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    SCREAMING_SNAKE_CASE_		(					self	:  Optional[Any]       ,     __snake_case	:  dict       ,     __snake_case	:  List[str]=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:
																	_snake_case:   Tuple  					=		{}

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


					def    SCREAMING_SNAKE_CASE_		(					self	:  Dict       ):





											'''simple docstring'''





											from .features import Value

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


					def    SCREAMING_SNAKE_CASE_		(					self	:  Dict       ,     __snake_case	:  Union[pa.StringArray, pa.StructArray, pa.ListArray]       ):





											'''simple docstring'''





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




					def    SCREAMING_SNAKE_CASE_		(					self	:  str       ,     __snake_case	:  pa.StructArray       ):





											'''simple docstring'''





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

											_snake_case:   List[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()       ,     )
											_snake_case:   Union[str, Any]  					=		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()       ,     )
											_snake_case:   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       lowercase_      (		)   ->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()
												_snake_case:   str  					=		list(set(PIL.Image.OPEN.keys()						) & set(PIL.Image.SAVE.keys()						)						)
						return _IMAGE_COMPRESSION_FORMATS





def       lowercase_      (		lowercase__						)   ->bytes:
						_snake_case:   Any  					=		BytesIO()
						if image.format in list_image_compression_formats():
												_snake_case:   Dict  					=		image.format
						else:
												_snake_case:   Union[str, Any]  					=		'PNG' if image.mode in ['1', 'L', 'LA', 'RGB', 'RGBA'] else 'TIFF'
						image.save(lowercase__				,  format=lowercase__						)
						return buffer.getvalue()





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





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

						_snake_case:   List[str]  					=		array.dtype
						_snake_case:   Optional[Any]  					=		dtype.byteorder if dtype.byteorder != '=' else _NATIVE_BYTEORDER
						_snake_case:   Dict  					=		dtype.kind
						_snake_case:   Tuple  					=		dtype.itemsize

						_snake_case:   Optional[Any]  					=		None

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





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

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












'''simple docstring'''






import sys
import webbrowser

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
		print('Googling.....')
		A   : Optional[int]             =			'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
		A   : Dict             =			requests.get(url, headers={'UserAgent': UserAgent().random})
		# res.raise_for_status()
		with open('project1a.html', 'wb') as out_file:  # only for knowing the class
				for data in res.iter_content(10_000):
						out_file.write(data)
		A   : List[Any]             =			BeautifulSoup(res.text, 'html.parser')
		A   : List[Any]             =			list(soup.select('.eZt8xd'))[:5]

		print(len(links))
		for link in links:
				if link.text == "Maps":
						webbrowser.open(link.get('href'))
				else:
						webbrowser.open(F'https://google.com{link.get("href")}')





