






import heapq as hq
import math
from collections.abc import Iterator







class   lowerCamelCase	:





     def __init__(self   :					Union[str, Any]       ,					_A   :					Dict     )		->		int:
         snake_case				  =      str(id_     )
         snake_case				  =      None
         snake_case				  =      None
         snake_case				  =      []
         snake_case				  =      {}  # {vertex:distance}





     def __lt__(self   :					List[Any]       ,					_A   :					List[str]     )		->		List[Any]:
         return self.key < other.key





     def __repr__(self   :					Optional[Any]     )		->		List[str]:
         return self.id





     def 	UpperCAmelCase(self   :					Dict       ,					_A   :					List[str]     )		->		List[Any]:
         self.neighbors.append(UpperCamelCase_     )





     def 	UpperCAmelCase(self   :					int       ,					_A   :					Any       ,					_A   :					Union[str, Any]     )		->		Optional[int]:
         snake_case				  =      weight



def 		lowercase_    (     A__				,	A__				,	A__				,	A__	)							->							Union[str, Any]:
    """simple docstring"""

    graph[a - 1].add_neighbor(graph[b - 1]	)
    graph[b - 1].add_neighbor(graph[a - 1]	)
    # add the edges:
    graph[a - 1].add_edge(graph[b - 1]				,	lowerCamelCase__	)
    graph[b - 1].add_edge(graph[a - 1]				,	lowerCamelCase__	)



def 		lowercase_    (     A__				,	A__	)							->							list:
    """simple docstring"""

    snake_case				  =      []
    for u in graph:
        snake_case				  =      math.inf
        snake_case				  =      None
    snake_case				  =      0
    snake_case				  =      graph[:]
    while q:
        snake_case				  =      min(lowerCamelCase__	)
        q.remove(lowerCamelCase__	)
        for v in u.neighbors:
            if (v in q) and (u.edges[v.id] < v.key):
                snake_case				  =      u
                snake_case				  =      u.edges[v.id]
    for i in range(1				,	len(lowerCamelCase__	)	):
        a.append((int(graph[i].id	) + 1, int(graph[i].pi.id	) + 1)	)
    return a



def 		lowercase_    (     A__				,	A__	)							->							Iterator[tuple]:
    """simple docstring"""

    for u in graph:
        snake_case				  =      math.inf
        snake_case				  =      None
    snake_case				  =      0

    snake_case				  =      list(lowerCamelCase__	)
    hq.heapify(lowerCamelCase__	)

    while h:
        snake_case				  =      hq.heappop(lowerCamelCase__	)
        for v in u.neighbors:
            if (v in h) and (u.edges[v.id] < v.key):
                snake_case				  =      u
                snake_case				  =      u.edges[v.id]
                hq.heapify(lowerCamelCase__	)

    for i in range(1				,	len(lowerCamelCase__	)	):
        yield (int(graph[i].id	) + 1, int(graph[i].pi.id	) + 1)



def 		lowercase_    (     )							->							None:
    """simple docstring"""





if __name__ == "__main__":
   import doctest

   doctest.testmod()



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   lowerCamelCase	(						A_						):





     def 	UpperCAmelCase(self   :					str     )		->		Dict:
         snake_case				  =      pa.array(TypedSequence([1, 2, 3]     )     )
         self.assertEqual(arr.type       ,					pa.intaa()     )





     def 	UpperCAmelCase(self   :					Optional[int]     )		->		Optional[int]:
         with self.assertRaises(_A     ):
             snake_case				  =      pa.array(TypedSequence([1, 2, 3]     )       ,					type=pa.intaa()     )





     def 	UpperCAmelCase(self   :					Dict     )		->		str:
         with self.assertRaises(_A     ):
             snake_case				  =      pa.array(TypedSequence([1, 2, 3]       ,					try_type=Value("bool"     )       ,					type=Value("int64"     )     )     )





     def 	UpperCAmelCase(self   :					List[Any]     )		->		List[str]:
         snake_case				  =      pa.array(TypedSequence([1, 2, 3]       ,					type=Value("int32"     )     )     )
         self.assertEqual(arr.type       ,					pa.intaa()     )





     def 	UpperCAmelCase(self   :					Tuple     )		->		List[Any]:
         with self.assertRaises((TypeError, pa.lib.ArrowInvalid)     ):
             snake_case				  =      pa.array(TypedSequence(["foo", "bar"]       ,					type=Value("int64"     )     )     )





     def 	UpperCAmelCase(self   :					List[Any]     )		->		Dict:
         snake_case				  =      pa.array(TypedSequence([1, 2, 3]       ,					try_type=Value("int32"     )     )     )
         self.assertEqual(arr.type       ,					pa.intaa()     )





     def 	UpperCAmelCase(self   :					Optional[int]     )		->		Optional[int]:
         snake_case				  =      pa.array(TypedSequence(["foo", "bar"]       ,					try_type=Value("int64"     )     )     )
         self.assertEqual(arr.type       ,					pa.string()     )





     def 	UpperCAmelCase(self   :					Any     )		->		Tuple:
         snake_case				  =      pa.array(TypedSequence([[[1, 2, 3]]]       ,					type=ArrayaD((1, 3)       ,					"int64"     )     )     )
         self.assertEqual(arr.type       ,					ArrayaDExtensionType((1, 3)       ,					"int64"     )     )





     def 	UpperCAmelCase(self   :					str     )		->		Union[str, Any]:
         with self.assertRaises((TypeError, pa.lib.ArrowInvalid)     ):
             snake_case				  =      pa.array(TypedSequence(["foo", "bar"]       ,					type=ArrayaD((1, 3)       ,					"int64"     )     )     )





     def 	UpperCAmelCase(self   :					Optional[int]     )		->		Tuple:
         snake_case				  =      pa.array(TypedSequence([[[1, 2, 3]]]       ,					try_type=ArrayaD((1, 3)       ,					"int64"     )     )     )
         self.assertEqual(arr.type       ,					ArrayaDExtensionType((1, 3)       ,					"int64"     )     )





     def 	UpperCAmelCase(self   :					str     )		->		Dict:
         snake_case				  =      pa.array(TypedSequence(["foo", "bar"]       ,					try_type=ArrayaD((1, 3)       ,					"int64"     )     )     )
         self.assertEqual(arr.type       ,					pa.string()     )





     @require_pil
     def 	UpperCAmelCase(self   :					Optional[int]     )		->		Any:
         import PIL.Image

         snake_case				  =      PIL.Image.fromarray(np.arange(1_0       ,					dtype=np.uinta     ).reshape(2       ,					5     )     )
         with patch(
             "datasets.arrow_writer.cast_to_python_objects"       ,					side_effect=_A     ) as mock_cast_to_python_objects:
             snake_case				  =      pa.array(TypedSequence([{"path": None, "bytes": b"image_bytes"}, pil_image]       ,					type=Image()     )     )
             snake_case  ,							snake_case				  =      mock_cast_to_python_objects.call_args_list[-1]
             self.assertIn("optimize_list_casting"       ,					_A     )
             self.assertFalse(kwargs["optimize_list_casting"]     )



def 		lowercase_    (     A__				,	A__	)							->							Tuple:
    """simple docstring"""

    snake_case				  =      pa.BufferReader(A__	) if isinstance(A__				,	pa.Buffer	) else pa.memory_map(A__	)
    snake_case				  =      pa.ipc.open_stream(A__	)
    snake_case				  =      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 		lowercase_    (     A__				,	A__	)							->							Optional[int]:
    """simple docstring"""

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



def 		lowercase_    (     )							->							str:
    """simple docstring"""

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



@pytest.mark.parametrize("writer_batch_size"				,	[None, 1, 10]	)
def 		lowercase_    (     A__	)							->							int:
    """simple docstring"""

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



@pytest.mark.parametrize("writer_batch_size"				,	[None, 2, 10]	)
def 		lowercase_    (     A__	)							->							str:
    """simple docstring"""

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



@pytest.mark.parametrize("writer_batch_size"				,	[None, 2, 10]	)
def 		lowercase_    (     A__	)							->							Optional[int]:
    """simple docstring"""

    snake_case				  =      pa.BufferOutputStream()
    with ArrowWriter(
        stream=A__				,	writer_batch_size=A__				,	hash_salt="split_name"				,	check_duplicates=A__				,	) as writer:
        writer.write({"col_1": "foo", "col_2": 1}				,	key=1	)
        writer.write({"col_1": "bar", "col_2": 2}				,	key=2	)
        snake_case  ,							snake_case				  =      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 		lowercase_    (     A__				,	A__	)							->							Dict:
    """simple docstring"""

    snake_case				  =      pa.BufferOutputStream()
    snake_case				  =      pa.schema(A__	) if fields else None
    with ArrowWriter(stream=A__				,	schema=A__				,	writer_batch_size=A__	) as writer:
        writer.write_batch({"col_1": ["foo", "bar"], "col_2": [1, 2]}	)
        writer.write_batch({"col_1": [], "col_2": []}	)
        snake_case  ,							snake_case				  =      writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        snake_case				  =      {"col_1": pa.string(), "col_2": pa.intaa()}
    assert writer._schema == pa.schema(A__				,	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 		lowercase_    (     A__				,	A__	)							->							Union[str, Any]:
    """simple docstring"""

    snake_case				  =      pa.BufferOutputStream()
    snake_case				  =      pa.schema(A__	) if fields else None
    with ArrowWriter(stream=A__				,	schema=A__				,	writer_batch_size=A__	) as writer:
        writer.write_table(pa.Table.from_pydict({"col_1": ["foo", "bar"], "col_2": [1, 2]}	)	)
        snake_case  ,							snake_case				  =      writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        snake_case				  =      {"col_1": pa.string(), "col_2": pa.intaa()}
    assert writer._schema == pa.schema(A__				,	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 		lowercase_    (     A__				,	A__	)							->							List[Any]:
    """simple docstring"""

    snake_case				  =      pa.BufferOutputStream()
    snake_case				  =      pa.schema(A__	) if fields else None
    with ArrowWriter(stream=A__				,	schema=A__				,	writer_batch_size=A__	) 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]}	)	)
        snake_case  ,							snake_case				  =      writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        snake_case				  =      {"col_1": pa.string(), "col_2": pa.intaa()}
    assert writer._schema == pa.schema(A__				,	metadata=writer._schema.metadata	)
    _check_output(output.getvalue()				,	expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)



def 		lowercase_    (     )							->							Dict:
    """simple docstring"""

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



def 		lowercase_    (     A__	)							->							int:
    """simple docstring"""

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



def 		lowercase_    (     A__				,	A__	)							->							Any:
    """simple docstring"""

    if isinstance(lst[0]				,	A__	):
        change_first_primitive_element_in_list(lst[0]				,	A__	)
    else:
        snake_case				  =      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 		lowercase_    (     A__				,	A__				,	A__	)							->							Tuple:
    """simple docstring"""

    snake_case				  =      pa.array(TypedSequence(A__				,	optimized_int_type=A__	)	)
    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 		lowercase_    (     A__				,	A__				,	A__	)							->							List[str]:
    """simple docstring"""

    snake_case				  =      pa.array(OptimizedTypedSequence(A__				,	col=A__	)	)
    assert get_base_dtype(arr.type	) == expected_dtype

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



@pytest.mark.parametrize("raise_exception"				,	[False, True]	)
def 		lowercase_    (     A__				,	A__	)							->							Optional[Any]:
    """simple docstring"""

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



def 		lowercase_    (     A__	)							->							Optional[int]:
    """simple docstring"""

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



def 		lowercase_    (     )							->							Tuple:
    """simple docstring"""

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



@require_pil
@pytest.mark.parametrize("embed_local_files"				,	[False, True]	)
def 		lowercase_    (     A__				,	A__	)							->							Dict:
    """simple docstring"""

    import PIL.Image

    snake_case				  =      str(tmp_path / "test_image_rgb.jpg"	)
    PIL.Image.fromarray(np.zeros((5, 5)				,	dtype=np.uinta	)	).save(A__				,	format="png"	)
    snake_case				  =      pa.BufferOutputStream()
    with ParquetWriter(
        stream=A__				,	features=Features({"image": Image()}	)				,	embed_local_files=A__	) as writer:
        writer.write({"image": image_path}	)
        writer.finalize()
    snake_case				  =      pa.BufferReader(output.getvalue()	)
    snake_case				  =      pq.read_table(A__	)
    snake_case				  =      pa_table.to_pydict()
    if embed_local_files:
        assert isinstance(out["image"][0]["path"]				,	A__	)
        with open(A__				,	"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 		lowercase_    (     )							->							List[Any]:
    """simple docstring"""

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

