
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil


class 				lowercase					(		_SCREAMING_SNAKE_CASE   ):



		def __UpperCamelCase ( self       )  ->					int:
				"""simple docstring"""
				UpperCamelCase		=     pa.array(TypedSequence([1, 2, 3]       )       )
				self.assertEqual(arr.type				,      pa.intaa()       )



		def __UpperCamelCase ( self       )  ->					Optional[Any]:
				"""simple docstring"""
				with self.assertRaises(A_       ):
						UpperCamelCase		=     pa.array(TypedSequence([1, 2, 3]       )				,      type=pa.intaa()       )



		def __UpperCamelCase ( self       )  ->					Dict:
				"""simple docstring"""
				with self.assertRaises(A_       ):
						UpperCamelCase		=     pa.array(TypedSequence([1, 2, 3]				,      try_type=Value('bool'       )				,      type=Value('int64'       )       )       )



		def __UpperCamelCase ( self       )  ->					Tuple:
				"""simple docstring"""
				UpperCamelCase		=     pa.array(TypedSequence([1, 2, 3]				,      type=Value('int32'       )       )       )
				self.assertEqual(arr.type				,      pa.intaa()       )



		def __UpperCamelCase ( self       )  ->					Any:
				"""simple docstring"""
				with self.assertRaises((TypeError, pa.lib.ArrowInvalid)       ):
						UpperCamelCase		=     pa.array(TypedSequence(['foo', 'bar']				,      type=Value('int64'       )       )       )



		def __UpperCamelCase ( self       )  ->					List[str]:
				"""simple docstring"""
				UpperCamelCase		=     pa.array(TypedSequence([1, 2, 3]				,      try_type=Value('int32'       )       )       )
				self.assertEqual(arr.type				,      pa.intaa()       )



		def __UpperCamelCase ( self       )  ->					Optional[int]:
				"""simple docstring"""
				UpperCamelCase		=     pa.array(TypedSequence(['foo', 'bar']				,      try_type=Value('int64'       )       )       )
				self.assertEqual(arr.type				,      pa.string()       )



		def __UpperCamelCase ( self       )  ->					Union[str, Any]:
				"""simple docstring"""
				UpperCamelCase		=     pa.array(TypedSequence([[[1, 2, 3]]]				,      type=ArrayaD((1, 3)				,      'int64'       )       )       )
				self.assertEqual(arr.type				,      ArrayaDExtensionType((1, 3)				,      'int64'       )       )



		def __UpperCamelCase ( self       )  ->					List[Any]:
				"""simple docstring"""
				with self.assertRaises((TypeError, pa.lib.ArrowInvalid)       ):
						UpperCamelCase		=     pa.array(TypedSequence(['foo', 'bar']				,      type=ArrayaD((1, 3)				,      'int64'       )       )       )



		def __UpperCamelCase ( self       )  ->					str:
				"""simple docstring"""
				UpperCamelCase		=     pa.array(TypedSequence([[[1, 2, 3]]]				,      try_type=ArrayaD((1, 3)				,      'int64'       )       )       )
				self.assertEqual(arr.type				,      ArrayaDExtensionType((1, 3)				,      'int64'       )       )



		def __UpperCamelCase ( self       )  ->					Optional[Any]:
				"""simple docstring"""
				UpperCamelCase		=     pa.array(TypedSequence(['foo', 'bar']				,      try_type=ArrayaD((1, 3)				,      'int64'       )       )       )
				self.assertEqual(arr.type				,      pa.string()       )



		@require_pil
		def __UpperCamelCase ( self       )  ->					List[Any]:
				"""simple docstring"""
				import PIL.Image

				UpperCamelCase		=     PIL.Image.fromarray(np.arange(10				,      dtype=np.uinta       ).reshape(2				,      5       )       )
				with patch(
				    'datasets.arrow_writer.cast_to_python_objects'				,      side_effect=A_       ) as mock_cast_to_python_objects:
						UpperCamelCase		=     pa.array(TypedSequence([{'path': None, 'bytes': b'image_bytes'}, pil_image]				,      type=Image()       )       )
						UpperCamelCase	,  UpperCamelCase		=     mock_cast_to_python_objects.call_args_list[-1]
						self.assertIn('optimize_list_casting'				,      A_       )
						self.assertFalse(kwargs['optimize_list_casting']       )






def       A       (					lowercase    ,       lowercase )   ->  int:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferReader(lowercase ) if isinstance(lowercase    ,       pa.Buffer ) else pa.memory_map(lowercase )
		UpperCamelCase		=     pa.ipc.open_stream(lowercase )
		UpperCamelCase		=     f.read_all()
		assert len(pa_table.to_batches() ) == expected_num_chunks
		assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
		del pa_table


@pytest.mark.parametrize('writer_batch_size'    ,       [None, 1, 10] )
@pytest.mark.parametrize(
    'fields'    ,       [None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}] )
def       A       (					lowercase    ,       lowercase )   ->  Optional[int]:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		UpperCamelCase		=     pa.schema(lowercase ) if fields else None
		with ArrowWriter(stream=lowercase    ,       schema=lowercase    ,       writer_batch_size=lowercase ) as writer:
				writer.write({'col_1': 'foo', 'col_2': 1} )
				writer.write({'col_1': 'bar', 'col_2': 2} )
				UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				UpperCamelCase		=     {'col_1': pa.string(), 'col_2': pa.intaa()}
		assert writer._schema == pa.schema(lowercase    ,       metadata=writer._schema.metadata )
		_check_output(output.getvalue()    ,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )


def       A       (					)   ->  Any:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		UpperCamelCase		=     Features({'labels': ClassLabel(names=['neg', 'pos'] )} )
		with ArrowWriter(stream=lowercase    ,       features=lowercase ) as writer:
				writer.write({'labels': 0} )
				writer.write({'labels': 1} )
				UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		assert writer._schema == features.arrow_schema
		assert writer._schema.metadata == features.arrow_schema.metadata
		UpperCamelCase		=     pa.BufferReader(output.getvalue() )
		UpperCamelCase		=     pa.ipc.open_stream(lowercase )
		UpperCamelCase		=     f.read_all()
		UpperCamelCase		=     pa_table.schema
		assert pa_table.num_rows == 2
		assert schema == features.arrow_schema
		assert schema.metadata == features.arrow_schema.metadata
		assert features == Features.from_arrow_schema(lowercase )


@pytest.mark.parametrize('writer_batch_size'    ,       [None, 1, 10] )
def       A       (					lowercase )   ->  Any:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		with ArrowWriter(
		    stream=lowercase    ,       writer_batch_size=lowercase    ,       hash_salt='split_name'    ,       check_duplicates=lowercase    ,       ) as writer:
				with pytest.raises(lowercase ):
						writer.write({'col_1': 'foo', 'col_2': 1}    ,       key=[1, 2] )
						UpperCamelCase	,  UpperCamelCase		=     writer.finalize()


@pytest.mark.parametrize('writer_batch_size'    ,       [None, 2, 10] )
def       A       (					lowercase )   ->  Dict:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		with ArrowWriter(
		    stream=lowercase    ,       writer_batch_size=lowercase    ,       hash_salt='split_name'    ,       check_duplicates=lowercase    ,       ) as writer:
				with pytest.raises(lowercase ):
						writer.write({'col_1': 'foo', 'col_2': 1}    ,       key=10 )
						writer.write({'col_1': 'bar', 'col_2': 2}    ,       key=10 )
						UpperCamelCase	,  UpperCamelCase		=     writer.finalize()


@pytest.mark.parametrize('writer_batch_size'    ,       [None, 2, 10] )
def       A       (					lowercase )   ->  Tuple:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		with ArrowWriter(
		    stream=lowercase    ,       writer_batch_size=lowercase    ,       hash_salt='split_name'    ,       check_duplicates=lowercase    ,       ) as writer:
				writer.write({'col_1': 'foo', 'col_2': 1}    ,       key=1 )
				writer.write({'col_1': 'bar', 'col_2': 2}    ,       key=2 )
				UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		_check_output(output.getvalue()    ,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )


@pytest.mark.parametrize('writer_batch_size'    ,       [None, 1, 10] )
@pytest.mark.parametrize(
    'fields'    ,       [None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}] )
def       A       (					lowercase    ,       lowercase )   ->  Optional[int]:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		UpperCamelCase		=     pa.schema(lowercase ) if fields else None
		with ArrowWriter(stream=lowercase    ,       schema=lowercase    ,       writer_batch_size=lowercase ) as writer:
				writer.write_batch({'col_1': ['foo', 'bar'], 'col_2': [1, 2]} )
				writer.write_batch({'col_1': [], 'col_2': []} )
				UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				UpperCamelCase		=     {'col_1': pa.string(), 'col_2': pa.intaa()}
		assert writer._schema == pa.schema(lowercase    ,       metadata=writer._schema.metadata )
		_check_output(output.getvalue()    ,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )


@pytest.mark.parametrize('writer_batch_size'    ,       [None, 1, 10] )
@pytest.mark.parametrize(
    'fields'    ,       [None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}] )
def       A       (					lowercase    ,       lowercase )   ->  Dict:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		UpperCamelCase		=     pa.schema(lowercase ) if fields else None
		with ArrowWriter(stream=lowercase    ,       schema=lowercase    ,       writer_batch_size=lowercase ) as writer:
				writer.write_table(pa.Table.from_pydict({'col_1': ['foo', 'bar'], 'col_2': [1, 2]} ) )
				UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				UpperCamelCase		=     {'col_1': pa.string(), 'col_2': pa.intaa()}
		assert writer._schema == pa.schema(lowercase    ,       metadata=writer._schema.metadata )
		_check_output(output.getvalue()    ,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )


@pytest.mark.parametrize('writer_batch_size'    ,       [None, 1, 10] )
@pytest.mark.parametrize(
    'fields'    ,       [None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}] )
def       A       (					lowercase    ,       lowercase )   ->  Dict:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		UpperCamelCase		=     pa.schema(lowercase ) if fields else None
		with ArrowWriter(stream=lowercase    ,       schema=lowercase    ,       writer_batch_size=lowercase ) as writer:
				writer.write_row(pa.Table.from_pydict({'col_1': ['foo'], 'col_2': [1]} ) )
				writer.write_row(pa.Table.from_pydict({'col_1': ['bar'], 'col_2': [2]} ) )
				UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				UpperCamelCase		=     {'col_1': pa.string(), 'col_2': pa.intaa()}
		assert writer._schema == pa.schema(lowercase    ,       metadata=writer._schema.metadata )
		_check_output(output.getvalue()    ,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )


def       A       (					)   ->  Union[str, Any]:
		'''simple docstring'''

		with tempfile.TemporaryDirectory() as tmp_dir:
				UpperCamelCase		=     {'col_1': pa.string(), 'col_2': pa.intaa()}
				UpperCamelCase		=     os.path.join(lowercase    ,       'test.arrow' )
				with ArrowWriter(path=lowercase    ,       schema=pa.schema(lowercase ) ) as writer:
						writer.write_batch({'col_1': ['foo', 'bar'], 'col_2': [1, 2]} )
						UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				assert writer._schema == pa.schema(lowercase    ,       metadata=writer._schema.metadata )
				_check_output(lowercase    ,       1 )


def       A       (					lowercase )   ->  str:
		'''simple docstring'''

		if pa.types.is_list(lowercase ):
				return get_base_dtype(arr_type.value_type )
		else:
				return arr_type


def       A       (					lowercase    ,       lowercase )   ->  Optional[Any]:
		'''simple docstring'''

		if isinstance(lst[0]    ,       lowercase ):
				change_first_primitive_element_in_list(lst[0]    ,       lowercase )
		else:
				UpperCamelCase		=     value


@pytest.mark.parametrize('optimized_int_type, expected_dtype'    ,       [(None, pa.intaa()), (Value('int32' ), pa.intaa())] )
@pytest.mark.parametrize('sequence'    ,       [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]] )
def       A       (					lowercase    ,       lowercase    ,       lowercase )   ->  Any:
		'''simple docstring'''

		UpperCamelCase		=     pa.array(TypedSequence(lowercase    ,       optimized_int_type=lowercase ) )
		assert get_base_dtype(arr.type ) == expected_dtype


@pytest.mark.parametrize(
    'col, expected_dtype'    ,       [
        ('attention_mask', pa.inta()),
        ('special_tokens_mask', pa.inta()),
        ('token_type_ids', pa.inta()),
        ('input_ids', pa.intaa()),
        ('other', pa.intaa()),
    ]    ,       )
@pytest.mark.parametrize('sequence'    ,       [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]] )
def       A       (					lowercase    ,       lowercase    ,       lowercase )   ->  Optional[Any]:
		'''simple docstring'''

		UpperCamelCase		=     pa.array(OptimizedTypedSequence(lowercase    ,       col=lowercase ) )
		assert get_base_dtype(arr.type ) == expected_dtype

		# not in range
		if col != "other":
				# avoids errors due to in-place modifications
				UpperCamelCase		=     copy.deepcopy(lowercase )
				UpperCamelCase		=     np.iinfo(expected_dtype.to_pandas_dtype() ).max + 1
				change_first_primitive_element_in_list(lowercase    ,       lowercase )
				UpperCamelCase		=     pa.array(OptimizedTypedSequence(lowercase    ,       col=lowercase ) )
				assert get_base_dtype(arr.type ) == pa.intaa()


@pytest.mark.parametrize('raise_exception'    ,       [False, True] )
def       A       (					lowercase    ,       lowercase )   ->  Dict:
		'''simple docstring'''

		UpperCamelCase		=     str(tmp_path / 'dataset-train.arrow' )
		try:
				with ArrowWriter(path=lowercase ) as writer:
						if raise_exception:
								raise pa.lib.ArrowInvalid()
						else:
								writer.stream.close()
		except pa.lib.ArrowInvalid:
				pass
		finally:
				assert writer.stream.closed


def       A       (					lowercase )   ->  int:
		'''simple docstring'''

		UpperCamelCase		=     'mock://dataset-train.arrow'
		with ArrowWriter(path=lowercase    ,       storage_options=mockfs.storage_options ) as writer:
				assert isinstance(writer._fs    ,       type(lowercase ) )
				assert writer._fs.storage_options == mockfs.storage_options
				writer.write({'col_1': 'foo', 'col_2': 1} )
				writer.write({'col_1': 'bar', 'col_2': 2} )
				UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		assert mockfs.exists(lowercase )


def       A       (					)   ->  List[Any]:
		'''simple docstring'''

		UpperCamelCase		=     pa.BufferOutputStream()
		with ParquetWriter(stream=lowercase ) as writer:
				writer.write({'col_1': 'foo', 'col_2': 1} )
				writer.write({'col_1': 'bar', 'col_2': 2} )
				UpperCamelCase	,  UpperCamelCase		=     writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		UpperCamelCase		=     pa.BufferReader(output.getvalue() )
		UpperCamelCase		=     pq.read_table(lowercase )
		assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}


@require_pil
@pytest.mark.parametrize('embed_local_files'    ,       [False, True] )
def       A       (					lowercase    ,       lowercase )   ->  Dict:
		'''simple docstring'''

		import PIL.Image

		UpperCamelCase		=     str(tmp_path / 'test_image_rgb.jpg' )
		PIL.Image.fromarray(np.zeros((5, 5)    ,       dtype=np.uinta ) ).save(lowercase    ,       format='png' )
		UpperCamelCase		=     pa.BufferOutputStream()
		with ParquetWriter(
		    stream=lowercase    ,       features=Features({'image': Image()} )    ,       embed_local_files=lowercase ) as writer:
				writer.write({'image': image_path} )
				writer.finalize()
		UpperCamelCase		=     pa.BufferReader(output.getvalue() )
		UpperCamelCase		=     pq.read_table(lowercase )
		UpperCamelCase		=     pa_table.to_pydict()
		if embed_local_files:
				assert isinstance(out['image'][0]['path']    ,       lowercase )
				with open(lowercase    ,       'rb' ) as f:
						assert out["image"][0]["bytes"] == f.read()
		else:
				assert out["image"][0]["path"] == image_path
				assert out["image"][0]["bytes"] is None


def       A       (					)   ->  Any:
		'''simple docstring'''

		UpperCamelCase		=     pa.schema([pa.field('col_1'    ,       pa.string()    ,       nullable=lowercase )] )
		UpperCamelCase		=     pa.BufferOutputStream()
		with ArrowWriter(stream=lowercase ) as writer:
				writer._build_writer(inferred_schema=lowercase )
				assert writer._schema == pa.schema([pa.field('col_1'    ,       pa.string() )] )


from __future__ import annotations

import os
from collections.abc import Mapping

_UpperCAmelCase					: Tuple      =       tuple[int, int]


class 				lowercase					:



		def __init__( self				,      A_				,      A_       )  ->					None:
				"""simple docstring"""
				UpperCamelCase		=     vertices
				UpperCamelCase		=     {
				    (min(A_       ), max(A_       )): weight for edge, weight in edges.items()
				}



		def __UpperCamelCase ( self				,      A_				,      A_       )  ->					None:
				"""simple docstring"""
				self.vertices.add(edge[0]       )
				self.vertices.add(edge[1]       )
				UpperCamelCase		=     weight



		def __UpperCamelCase ( self       )  ->					Graph:
				"""simple docstring"""
				UpperCamelCase		=     Graph({min(self.vertices       )}				,      {}       )
				UpperCamelCase		=     42
				UpperCamelCase		=     42
				UpperCamelCase		=     42
				UpperCamelCase		=     42

				while len(subgraph.vertices       ) < len(self.vertices       ):
						UpperCamelCase		=     max(self.edges.values()       ) + 1
						for edge, weight in self.edges.items():
								if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
										if weight < min_weight:
												UpperCamelCase		=     edge
												UpperCamelCase		=     weight

						subgraph.add_edge(A_				,      A_       )

				return subgraph






def       A       (					lowercase = "p107_network.txt" )   ->  int:
		'''simple docstring'''

		UpperCamelCase		=     os.path.abspath(os.path.dirname(lowercase ) )
		UpperCamelCase		=     os.path.join(lowercase    ,       lowercase )
		UpperCamelCase		=     {}
		UpperCamelCase		=     42
		UpperCamelCase		=     42
		UpperCamelCase		=     42

		with open(lowercase ) as f:
				UpperCamelCase		=     f.read().strip().split('\n' )

		UpperCamelCase		=     [line.split(',' ) for line in data]

		for edgea in range(1    ,       len(lowercase ) ):
				for edgea in range(lowercase ):
						if adjaceny_matrix[edgea][edgea] != "-":
								UpperCamelCase		=     int(adjaceny_matrix[edgea][edgea] )

		UpperCamelCase		=     Graph(set(range(len(lowercase ) ) )    ,       lowercase )

		UpperCamelCase		=     graph.prims_algorithm()

		UpperCamelCase		=     sum(graph.edges.values() )
		UpperCamelCase		=     sum(subgraph.edges.values() )

		return initial_total - optimal_total


if __name__ == "__main__":
					print(F'''{solution() = }''')
