


def        UpperCamelCase_(				_A   :Optional[Any]  )->		List[str]:
			UpperCamelCase__					=       0
			UpperCamelCase__					=       len(_A  )

			for i in range(n - 1  ):
						for j in range(i + 1				,     _A  ):
									if arr[i] > arr[j]:
												num_inversions += 1

			return num_inversions
def        UpperCamelCase_(				_A   :int  )->		Optional[Any]:
			if len(_A  ) <= 1:
						return arr, 0
			UpperCamelCase__					=       len(_A  ) // 2
			UpperCamelCase__					=       arr[0:mid]
			UpperCamelCase__					=       arr[mid:]

			UpperCamelCase__,      UpperCamelCase__					=       count_inversions_recursive(_A  )
			UpperCamelCase__,      UpperCamelCase__					=       count_inversions_recursive(_A  )
			UpperCamelCase__,      UpperCamelCase__					=       _count_cross_inversions(_A				,     _A  )

			UpperCamelCase__					=       inversion_p + inversions_q + cross_inversions
			return c, num_inversions
def        UpperCamelCase_(				_A   :Optional[Any]				,     _A   :str  )->		Dict:
			UpperCamelCase__					=       []
			UpperCamelCase__					=       UpperCamelCase__					=       UpperCamelCase__					=       0
			while i < len(_A  ) and j < len(_A  ):
						if p[i] > q[j]:
									# if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
									# These are all inversions. The claim emerges from the
									# property that P is sorted.
									num_inversion += len(_A  ) - i
									r.append(q[j]  )
									j += 1
						else:
									r.append(p[i]  )
									i += 1

			if i < len(_A  ):
						r.extend(p[i:]  )
			else:
						r.extend(q[j:]  )

			return r, num_inversion
def        UpperCamelCase_(				)->		Optional[int]:
			UpperCamelCase__					=       [10, 2, 1, 5, 5, 2, 11]

			# this arr has 8 inversions:
			# (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

			UpperCamelCase__					=       count_inversions_bf(_A  )
			UpperCamelCase__,      UpperCamelCase__					=       count_inversions_recursive(_A  )

			assert num_inversions_bf == num_inversions_recursive == 8

			print("number of inversions = "				,     _A  )

			# testing an array with zero inversion (a sorted arr_1)

			arr_a.sort()
			UpperCamelCase__					=       count_inversions_bf(_A  )
			UpperCamelCase__,      UpperCamelCase__					=       count_inversions_recursive(_A  )

			assert num_inversions_bf == num_inversions_recursive == 0
			print("number of inversions = "				,     _A  )

			# an empty list should also have zero inversions
			UpperCamelCase__					=       []
			UpperCamelCase__					=       count_inversions_bf(_A  )
			UpperCamelCase__,      UpperCamelCase__					=       count_inversions_recursive(_A  )

			assert num_inversions_bf == num_inversions_recursive == 0
			print("number of inversions = "				,     _A  )


if __name__ == "__main__":
						main()






import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil
@pytest.fixture
def        UpperCamelCase_(				_A   :Union[str, Any]  )->		int:
			UpperCamelCase__					=       tmp_path / "file.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    "\\n        header1,header2\n        1,2\n        10,20\n        "  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
@pytest.fixture
def        UpperCamelCase_(				_A   :int  )->		Union[str, Any]:
			UpperCamelCase__					=       tmp_path / "malformed_file.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    "\\n        header1,header2\n        1,2\n        10,20,\n        "  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
@pytest.fixture
def        UpperCamelCase_(				_A   :List[Any]				,     _A   :Dict  )->		Optional[Any]:
			UpperCamelCase__					=       tmp_path / "csv_with_image.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    F'''\
        image
        {image_file}
        '''  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
@pytest.fixture
def        UpperCamelCase_(				_A   :List[Any]  )->		Any:
			UpperCamelCase__					=       tmp_path / "csv_with_label.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    "\\n        label\n        good\n        bad\n        good\n        "  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
@pytest.fixture
def        UpperCamelCase_(				_A   :Any  )->		int:
			UpperCamelCase__					=       tmp_path / "csv_with_int_list.csv"
			UpperCamelCase__					=       textwrap.dedent(
			    "\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        "  )
			with open(_A				,     "w"  ) as f:
						f.write(_A  )
			return str(_A  )
def        UpperCamelCase_(				_A   :Optional[Any]				,     _A   :Optional[Any]				,     _A   :List[str]  )->		Union[str, Any]:
			UpperCamelCase__					=       Csv()
			UpperCamelCase__					=       csv._generate_tables([[csv_file, malformed_csv_file]]  )
			with pytest.raises(_A				,     match="Error tokenizing data"  ):
						for _ in generator:
									pass
			assert any(
			    record.levelname == "ERROR"
			    and "Failed to read file" in record.message
			    and os.path.basename(_A  ) in record.message
			    for record in caplog.records  )
@require_pil
def        UpperCamelCase_(				_A   :Any  )->		int:
			with open(_A				,     encoding="utf-8"  ) as f:
						UpperCamelCase__					=       f.read().splitlines()[1]
			UpperCamelCase__					=       Csv(encoding="utf-8"				,     features=Features({"image": Image()}  )  )
			UpperCamelCase__					=       csv._generate_tables([[csv_file_with_image]]  )
			UpperCamelCase__					=       pa.concat_tables([table for _, table in generator]  )
			assert pa_table.schema.field("image"  ).type == Image()()
			UpperCamelCase__					=       pa_table.to_pydict()["image"]
			assert generated_content == [{"path": image_file, "bytes": None}]
def        UpperCamelCase_(				_A   :Any  )->		Dict:
			with open(_A				,     encoding="utf-8"  ) as f:
						UpperCamelCase__					=       f.read().splitlines()[1:]
			UpperCamelCase__					=       Csv(encoding="utf-8"				,     features=Features({"label": ClassLabel(names=["good", "bad"]  )}  )  )
			UpperCamelCase__					=       csv._generate_tables([[csv_file_with_label]]  )
			UpperCamelCase__					=       pa.concat_tables([table for _, table in generator]  )
			assert pa_table.schema.field("label"  ).type == ClassLabel(names=["good", "bad"]  )()
			UpperCamelCase__					=       pa_table.to_pydict()["label"]
			assert generated_content == [ClassLabel(names=["good", "bad"]  ).straint(_A  ) for label in labels]







def        UpperCamelCase_(				_A   :Dict  )->		Optional[Any]:
			UpperCamelCase__					=       Csv(encoding="utf-8"				,     sep=","				,     converters={"int_list": lambda _A  : [int(_A  ) for i in x.split()]}  )
			UpperCamelCase__					=       csv._generate_tables([[csv_file_with_int_list]]  )
			UpperCamelCase__					=       pa.concat_tables([table for _, table in generator]  )
			assert pa.types.is_list(pa_table.schema.field("int_list"  ).type  )
			UpperCamelCase__					=       pa_table.to_pydict()["int_list"]
			assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]


