


'''simple docstring'''



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 						_snake_case   (       a__		):




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




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




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




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




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




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




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




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




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




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




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




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

								UpperCAmelCase__					:   List[str]       				=       PIL.Image.fromarray(np.arange(10							,							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__					:   Union[str, Any]       				=       pa.array(TypedSequence([{"""path""": None, """bytes""": B"""image_bytes"""}, pil_image]							,							type=Image()))
											UpperCAmelCase__					:   Tuple       				=       mock_cast_to_python_objects.call_args_list[-1]
											self.assertIn("""optimize_list_casting"""							,							_lowerCamelCase)
											self.assertFalse(kwargs["""optimize_list_casting"""])







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







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







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







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







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







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







def       _UpperCamelCase (						UpperCamelCase__   ):
			if pa.types.is_list(UpperCamelCase__   ):
						return get_base_dtype(arr_type.value_type   )
			else:
						return arr_type







def       _UpperCamelCase (						UpperCamelCase__	, UpperCamelCase__   ):
			if isinstance(lst[0]	, UpperCamelCase__   ):
						change_first_primitive_element_in_list(lst[0]	, UpperCamelCase__   )
			else:
						UpperCAmelCase__					:   int       				=       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       _UpperCamelCase (						UpperCamelCase__	, UpperCamelCase__	, UpperCamelCase__   ):
			UpperCAmelCase__					:   Union[str, Any]       				=       pa.array(TypedSequence(UpperCamelCase__	, optimized_int_type=UpperCamelCase__   )   )
			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       _UpperCamelCase (						UpperCamelCase__	, UpperCamelCase__	, UpperCamelCase__   ):
			# in range
			UpperCAmelCase__					:   Tuple       				=       pa.array(OptimizedTypedSequence(UpperCamelCase__	, col=UpperCamelCase__   )   )
			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(UpperCamelCase__   )
						UpperCAmelCase__					:   Optional[int]       				=       np.iinfo(expected_dtype.to_pandas_dtype()   ).max + 1
						change_first_primitive_element_in_list(UpperCamelCase__	, UpperCamelCase__   )
						UpperCAmelCase__					:   List[str]       				=       pa.array(OptimizedTypedSequence(UpperCamelCase__	, col=UpperCamelCase__   )   )
						assert get_base_dtype(arr.type   ) == pa.intaa()







@pytest.mark.parametrize("""raise_exception"""	, [False, True]   )
def       _UpperCamelCase (						UpperCamelCase__	, UpperCamelCase__   ):
			UpperCAmelCase__					:   Dict       				=       str(tmp_path / """dataset-train.arrow"""   )
			try:
						with ArrowWriter(path=UpperCamelCase__   ) as writer:
									if raise_exception:
												raise pa.lib.ArrowInvalid()
									else:
												writer.stream.close()
			except pa.lib.ArrowInvalid:
						pass
			finally:
						assert writer.stream.closed







def       _UpperCamelCase (						UpperCamelCase__   ):
			UpperCAmelCase__					:   Optional[int]       				=       """mock://dataset-train.arrow"""
			with ArrowWriter(path=UpperCamelCase__	, storage_options=mockfs.storage_options   ) as writer:
						assert isinstance(writer._fs	, type(UpperCamelCase__   )   )
						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__					:   Dict       				=       writer.finalize()
			assert num_examples == 2
			assert num_bytes > 0
			assert mockfs.exists(UpperCamelCase__   )







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







@require_pil
@pytest.mark.parametrize("""embed_local_files"""	, [False, True]   )
def       _UpperCamelCase (						UpperCamelCase__	, UpperCamelCase__   ):
			import PIL.Image

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



'''simple docstring'''



def       _UpperCamelCase (						UpperCamelCase__ = 1_0	, UpperCamelCase__ = 2_2   ):
			UpperCAmelCase__					:   List[str]       				=       range(1	, UpperCamelCase__   )
			UpperCAmelCase__					:   int       				=       range(1	, UpperCamelCase__   )
			return sum(
			    1 for power in powers for base in bases if len(str(base**power   )   ) == power   )


if __name__ == "__main__":
		print(f"""{solution(10, 22) = }""")