

import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links



def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE=7      ):
	UpperCAmelCase__:	List[str]									= None
	if token is not None:
		UpperCAmelCase__:	List[str]									= {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

	# The id of a workflow (not of a workflow run)
	UpperCAmelCase__:	Dict									= "636036"

	UpperCAmelCase__:	Optional[int]									= f"https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"
	# On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
	url += f"?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"

	UpperCAmelCase__:	List[Any]									= requests.get(SCREAMING_SNAKE_CASE	,headers=SCREAMING_SNAKE_CASE      ).json()

	return result["workflow_runs"]



def 			_A	(      SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	Dict									= get_daily_ci_runs(SCREAMING_SNAKE_CASE      )
	UpperCAmelCase__:	Tuple									= None
	for workflow_run in workflow_runs:
		if workflow_run["status"] == "completed":
			UpperCAmelCase__:	Optional[Any]									= workflow_run["id"]
			break

	return workflow_run_id



def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	Optional[int]									= get_last_daily_ci_runs(SCREAMING_SNAKE_CASE      )
	if workflow_run_id is not None:
		UpperCAmelCase__:	Tuple									= get_artifacts_links(worflow_run_id=SCREAMING_SNAKE_CASE	,token=SCREAMING_SNAKE_CASE      )
		for artifact_name in artifact_names:
			if artifact_name in artifacts_links:
				UpperCAmelCase__:	Union[str, Any]									= artifacts_links[artifact_name]
				download_artifact(
				    artifact_name=SCREAMING_SNAKE_CASE	,artifact_url=SCREAMING_SNAKE_CASE	,output_dir=SCREAMING_SNAKE_CASE	,token=SCREAMING_SNAKE_CASE      )



def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	get_last_daily_ci_artifacts(SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      )

	UpperCAmelCase__:	List[str]									= {}
	for artifact_name in artifact_names:
		UpperCAmelCase__:	str									= os.path.join(SCREAMING_SNAKE_CASE	,f"{artifact_name}.zip"      )
		if os.path.isfile(SCREAMING_SNAKE_CASE      ):
			UpperCAmelCase__:	Any									= {}
			with zipfile.ZipFile(SCREAMING_SNAKE_CASE      ) as z:
				for filename in z.namelist():
					if not os.path.isdir(SCREAMING_SNAKE_CASE      ):
						# read the file
						with z.open(SCREAMING_SNAKE_CASE      ) as f:
							UpperCAmelCase__:	Optional[int]									= f.read().decode("UTF-8"      )

	return results


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 __UpperCamelCase     (				_a		):






					'''simple docstring'''



					def    _UpperCAmelCase    (				self						):
						UpperCAmelCase__:	Optional[Any]									= pa.array(TypedSequence([1, 2, 3]						)						)
						self.assertEqual(arr.type				,      pa.intaa()						)





					def    _UpperCAmelCase    (				self						):
						with self.assertRaises(lowerCamelCase__						):
							UpperCAmelCase__:	Optional[Any]									= pa.array(TypedSequence([1, 2, 3]						)				,      type=pa.intaa()						)





					def    _UpperCAmelCase    (				self						):
						with self.assertRaises(lowerCamelCase__						):
							UpperCAmelCase__:	List[Any]									= pa.array(TypedSequence([1, 2, 3]				,      try_type=Value("bool"						)				,      type=Value("int64"						)						)						)





					def    _UpperCAmelCase    (				self						):
						UpperCAmelCase__:	Dict									= pa.array(TypedSequence([1, 2, 3]				,      type=Value("int32"						)						)						)
						self.assertEqual(arr.type				,      pa.intaa()						)





					def    _UpperCAmelCase    (				self						):
						with self.assertRaises((TypeError, pa.lib.ArrowInvalid)						):
							UpperCAmelCase__:	List[str]									= pa.array(TypedSequence(["foo", "bar"]				,      type=Value("int64"						)						)						)





					def    _UpperCAmelCase    (				self						):
						UpperCAmelCase__:	List[str]									= pa.array(TypedSequence([1, 2, 3]				,      try_type=Value("int32"						)						)						)
						self.assertEqual(arr.type				,      pa.intaa()						)





					def    _UpperCAmelCase    (				self						):
						UpperCAmelCase__:	str									= pa.array(TypedSequence(["foo", "bar"]				,      try_type=Value("int64"						)						)						)
						self.assertEqual(arr.type				,      pa.string()						)





					def    _UpperCAmelCase    (				self						):
						UpperCAmelCase__:	Optional[Any]									= pa.array(TypedSequence([[[1, 2, 3]]]				,      type=ArrayaD((1, 3)				,      "int64"						)						)						)
						self.assertEqual(arr.type				,      ArrayaDExtensionType((1, 3)				,      "int64"						)						)





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





					def    _UpperCAmelCase    (				self						):
						UpperCAmelCase__:	Any									= pa.array(TypedSequence([[[1, 2, 3]]]				,      try_type=ArrayaD((1, 3)				,      "int64"						)						)						)
						self.assertEqual(arr.type				,      ArrayaDExtensionType((1, 3)				,      "int64"						)						)





					def    _UpperCAmelCase    (				self						):
						UpperCAmelCase__:	int									= pa.array(TypedSequence(["foo", "bar"]				,      try_type=ArrayaD((1, 3)				,      "int64"						)						)						)
						self.assertEqual(arr.type				,      pa.string()						)





					@require_pil
					def    _UpperCAmelCase    (				self						):
						import PIL.Image

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



def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	Optional[Any]									= pa.BufferReader(SCREAMING_SNAKE_CASE      ) if isinstance(SCREAMING_SNAKE_CASE	,pa.Buffer      ) else pa.memory_map(SCREAMING_SNAKE_CASE      )
	UpperCAmelCase__:	str									= pa.ipc.open_stream(SCREAMING_SNAKE_CASE      )
	UpperCAmelCase__:	pa.Table									= 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, 1_0]      )
@pytest.mark.parametrize(
    "fields"	,[None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]      )
def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	List[str]									= pa.BufferOutputStream()
	UpperCAmelCase__:	Tuple									= pa.schema(SCREAMING_SNAKE_CASE      ) if fields else None
	with ArrowWriter(stream=SCREAMING_SNAKE_CASE	,schema=SCREAMING_SNAKE_CASE	,writer_batch_size=SCREAMING_SNAKE_CASE      ) as writer:
		writer.write({"col_1": "foo", "col_2": 1}      )
		writer.write({"col_1": "bar", "col_2": 2}      )
		UpperCAmelCase__							,						UpperCAmelCase__:	List[Any]									= writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	if not fields:
		UpperCAmelCase__:	Optional[int]									= {"col_1": pa.string(), "col_2": pa.intaa()}
	assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE	,metadata=writer._schema.metadata      )
	_check_output(output.getvalue()	,expected_num_chunks=num_examples if writer_batch_size == 1 else 1      )



def 			_A	(      ):
	UpperCAmelCase__:	Tuple									= pa.BufferOutputStream()
	UpperCAmelCase__:	Any									= Features({"labels": ClassLabel(names=["neg", "pos"]      )}      )
	with ArrowWriter(stream=SCREAMING_SNAKE_CASE	,features=SCREAMING_SNAKE_CASE      ) as writer:
		writer.write({"labels": 0}      )
		writer.write({"labels": 1}      )
		UpperCAmelCase__							,						UpperCAmelCase__:	List[Any]									= 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__:	Dict									= pa.BufferReader(output.getvalue()      )
	UpperCAmelCase__:	Any									= pa.ipc.open_stream(SCREAMING_SNAKE_CASE      )
	UpperCAmelCase__:	pa.Table									= f.read_all()
	UpperCAmelCase__:	Union[str, Any]									= 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(SCREAMING_SNAKE_CASE      )



@pytest.mark.parametrize("writer_batch_size"	,[None, 1, 1_0]      )
def 			_A	(      SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	List[str]									= pa.BufferOutputStream()
	with ArrowWriter(
	    stream=SCREAMING_SNAKE_CASE	,writer_batch_size=SCREAMING_SNAKE_CASE	,hash_salt="split_name"	,check_duplicates=SCREAMING_SNAKE_CASE	,) as writer:
		with pytest.raises(SCREAMING_SNAKE_CASE      ):
			writer.write({"col_1": "foo", "col_2": 1}	,key=[1, 2]      )
			UpperCAmelCase__							,						UpperCAmelCase__:	Any									= writer.finalize()



@pytest.mark.parametrize("writer_batch_size"	,[None, 2, 1_0]      )
def 			_A	(      SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	int									= pa.BufferOutputStream()
	with ArrowWriter(
	    stream=SCREAMING_SNAKE_CASE	,writer_batch_size=SCREAMING_SNAKE_CASE	,hash_salt="split_name"	,check_duplicates=SCREAMING_SNAKE_CASE	,) as writer:
		with pytest.raises(SCREAMING_SNAKE_CASE      ):
			writer.write({"col_1": "foo", "col_2": 1}	,key=1_0      )
			writer.write({"col_1": "bar", "col_2": 2}	,key=1_0      )
			UpperCAmelCase__							,						UpperCAmelCase__:	str									= writer.finalize()



@pytest.mark.parametrize("writer_batch_size"	,[None, 2, 1_0]      )
def 			_A	(      SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	Dict									= pa.BufferOutputStream()
	with ArrowWriter(
	    stream=SCREAMING_SNAKE_CASE	,writer_batch_size=SCREAMING_SNAKE_CASE	,hash_salt="split_name"	,check_duplicates=SCREAMING_SNAKE_CASE	,) as writer:
		writer.write({"col_1": "foo", "col_2": 1}	,key=1      )
		writer.write({"col_1": "bar", "col_2": 2}	,key=2      )
		UpperCAmelCase__							,						UpperCAmelCase__:	Union[str, Any]									= 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, 1_0]      )
@pytest.mark.parametrize(
    "fields"	,[None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]      )
def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	int									= pa.BufferOutputStream()
	UpperCAmelCase__:	Optional[Any]									= pa.schema(SCREAMING_SNAKE_CASE      ) if fields else None
	with ArrowWriter(stream=SCREAMING_SNAKE_CASE	,schema=SCREAMING_SNAKE_CASE	,writer_batch_size=SCREAMING_SNAKE_CASE      ) as writer:
		writer.write_batch({"col_1": ["foo", "bar"], "col_2": [1, 2]}      )
		writer.write_batch({"col_1": [], "col_2": []}      )
		UpperCAmelCase__							,						UpperCAmelCase__:	int									= writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	if not fields:
		UpperCAmelCase__:	Optional[Any]									= {"col_1": pa.string(), "col_2": pa.intaa()}
	assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE	,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, 1_0]      )
@pytest.mark.parametrize(
    "fields"	,[None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]      )
def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	Tuple									= pa.BufferOutputStream()
	UpperCAmelCase__:	List[str]									= pa.schema(SCREAMING_SNAKE_CASE      ) if fields else None
	with ArrowWriter(stream=SCREAMING_SNAKE_CASE	,schema=SCREAMING_SNAKE_CASE	,writer_batch_size=SCREAMING_SNAKE_CASE      ) as writer:
		writer.write_table(pa.Table.from_pydict({"col_1": ["foo", "bar"], "col_2": [1, 2]}      )      )
		UpperCAmelCase__							,						UpperCAmelCase__:	Any									= writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	if not fields:
		UpperCAmelCase__:	str									= {"col_1": pa.string(), "col_2": pa.intaa()}
	assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE	,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, 1_0]      )
@pytest.mark.parametrize(
    "fields"	,[None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]      )
def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	List[str]									= pa.BufferOutputStream()
	UpperCAmelCase__:	List[Any]									= pa.schema(SCREAMING_SNAKE_CASE      ) if fields else None
	with ArrowWriter(stream=SCREAMING_SNAKE_CASE	,schema=SCREAMING_SNAKE_CASE	,writer_batch_size=SCREAMING_SNAKE_CASE      ) 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__:	Any									= writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	if not fields:
		UpperCAmelCase__:	Dict									= {"col_1": pa.string(), "col_2": pa.intaa()}
	assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE	,metadata=writer._schema.metadata      )
	_check_output(output.getvalue()	,expected_num_chunks=num_examples if writer_batch_size == 1 else 1      )



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



def 			_A	(      SCREAMING_SNAKE_CASE      ):
	if pa.types.is_list(SCREAMING_SNAKE_CASE      ):
		return get_base_dtype(arr_type.value_type      )
	else:
		return arr_type



def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	if isinstance(lst[0]	,SCREAMING_SNAKE_CASE      ):
		change_first_primitive_element_in_list(lst[0]	,SCREAMING_SNAKE_CASE      )
	else:
		UpperCAmelCase__:	Dict									= 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	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	str									= pa.array(TypedSequence(SCREAMING_SNAKE_CASE	,optimized_int_type=SCREAMING_SNAKE_CASE      )      )
	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	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	# in range
	UpperCAmelCase__:	List[Any]									= pa.array(OptimizedTypedSequence(SCREAMING_SNAKE_CASE	,col=SCREAMING_SNAKE_CASE      )      )
	assert get_base_dtype(arr.type      ) == expected_dtype

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



@pytest.mark.parametrize("raise_exception"	,[False, True]      )
def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	List[Any]									= str(tmp_path / "dataset-train.arrow"      )
	try:
		with ArrowWriter(path=SCREAMING_SNAKE_CASE      ) 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	(      SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	List[Any]									= "mock://dataset-train.arrow"
	with ArrowWriter(path=SCREAMING_SNAKE_CASE	,storage_options=mockfs.storage_options      ) as writer:
		assert isinstance(writer._fs	,type(SCREAMING_SNAKE_CASE      )      )
		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__:	List[Any]									= writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	assert mockfs.exists(SCREAMING_SNAKE_CASE      )



def 			_A	(      ):
	UpperCAmelCase__:	Dict									= pa.BufferOutputStream()
	with ParquetWriter(stream=SCREAMING_SNAKE_CASE      ) as writer:
		writer.write({"col_1": "foo", "col_2": 1}      )
		writer.write({"col_1": "bar", "col_2": 2}      )
		UpperCAmelCase__							,						UpperCAmelCase__:	str									= writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	UpperCAmelCase__:	str									= pa.BufferReader(output.getvalue()      )
	UpperCAmelCase__:	pa.Table									= pq.read_table(SCREAMING_SNAKE_CASE      )
	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	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
	import PIL.Image

	UpperCAmelCase__:	List[str]									= str(tmp_path / "test_image_rgb.jpg"      )
	PIL.Image.fromarray(np.zeros((5, 5)	,dtype=np.uinta      )      ).save(SCREAMING_SNAKE_CASE	,format="png"      )
	UpperCAmelCase__:	List[Any]									= pa.BufferOutputStream()
	with ParquetWriter(
	    stream=SCREAMING_SNAKE_CASE	,features=Features({"image": Image()}      )	,embed_local_files=SCREAMING_SNAKE_CASE      ) as writer:
		writer.write({"image": image_path}      )
		writer.finalize()
	UpperCAmelCase__:	Optional[int]									= pa.BufferReader(output.getvalue()      )
	UpperCAmelCase__:	pa.Table									= pq.read_table(SCREAMING_SNAKE_CASE      )
	UpperCAmelCase__:	Dict									= pa_table.to_pydict()
	if embed_local_files:
		assert isinstance(out["image"][0]["path"]	,SCREAMING_SNAKE_CASE      )
		with open(SCREAMING_SNAKE_CASE	,"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	(      ):
	UpperCAmelCase__:	List[str]									= pa.schema([pa.field("col_1"	,pa.string()	,nullable=SCREAMING_SNAKE_CASE      )]      )
	UpperCAmelCase__:	Optional[Any]									= pa.BufferOutputStream()
	with ArrowWriter(stream=SCREAMING_SNAKE_CASE      ) as writer:
		writer._build_writer(inferred_schema=SCREAMING_SNAKE_CASE      )
		assert writer._schema == pa.schema([pa.field("col_1"	,pa.string()      )]      )