




'''simple docstring'''





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      __a     (       _UpperCamelCase:   Tuple   )						->			Optional[int]:

     """simple docstring"""




     _snake_case							=				tmp_path / "file.csv"
     _snake_case							=				textwrap.dedent(
         "\\n        header1,header2\n        1,2\n        10,20\n        "   )
     with open(_UpperCamelCase ,						"w"   ) as f:
          f.write(_UpperCamelCase   )
     return str(_UpperCamelCase   )





@pytest.fixture
def      __a     (       _UpperCamelCase:   Optional[int]   )						->			Dict:

     """simple docstring"""




     _snake_case							=				tmp_path / "malformed_file.csv"
     _snake_case							=				textwrap.dedent(
         "\\n        header1,header2\n        1,2\n        10,20,\n        "   )
     with open(_UpperCamelCase ,						"w"   ) as f:
          f.write(_UpperCamelCase   )
     return str(_UpperCamelCase   )





@pytest.fixture
def      __a     (       _UpperCamelCase:   Dict ,						_UpperCamelCase:   List[Any]   )						->			Tuple:

     """simple docstring"""




     _snake_case							=				tmp_path / "csv_with_image.csv"
     _snake_case							=				textwrap.dedent(
         F"""\
        image
        {image_file}
        """   )
     with open(_UpperCamelCase ,						"w"   ) as f:
          f.write(_UpperCamelCase   )
     return str(_UpperCamelCase   )





@pytest.fixture
def      __a     (       _UpperCamelCase:   List[str]   )						->			Any:

     """simple docstring"""




     _snake_case							=				tmp_path / "csv_with_label.csv"
     _snake_case							=				textwrap.dedent(
         "\\n        label\n        good\n        bad\n        good\n        "   )
     with open(_UpperCamelCase ,						"w"   ) as f:
          f.write(_UpperCamelCase   )
     return str(_UpperCamelCase   )





@pytest.fixture
def      __a     (       _UpperCamelCase:   Optional[Any]   )						->			List[Any]:

     """simple docstring"""




     _snake_case							=				tmp_path / "csv_with_int_list.csv"
     _snake_case							=				textwrap.dedent(
         "\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        "   )
     with open(_UpperCamelCase ,						"w"   ) as f:
          f.write(_UpperCamelCase   )
     return str(_UpperCamelCase   )





def      __a     (       _UpperCamelCase:   Dict ,						_UpperCamelCase:   Any ,						_UpperCamelCase:   Optional[int]   )						->			Optional[int]:

     """simple docstring"""




     _snake_case							=				Csv()
     _snake_case							=				csv._generate_tables([[csv_file, malformed_csv_file]]   )
     with pytest.raises(_UpperCamelCase ,						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(_UpperCamelCase   ) in record.message
         for record in caplog.records   )





@require_pil
def      __a     (       _UpperCamelCase:   Optional[Any]   )						->			Optional[Any]:

     """simple docstring"""




     with open(_UpperCamelCase ,						encoding="utf-8"   ) as f:
          _snake_case							=				f.read().splitlines()[1]
     _snake_case							=				Csv(encoding="utf-8" ,						features=Features({"image": Image()}   )   )
     _snake_case							=				csv._generate_tables([[csv_file_with_image]]   )
     _snake_case							=				pa.concat_tables([table for _, table in generator]   )
     assert pa_table.schema.field("image"   ).type == Image()()
     _snake_case							=				pa_table.to_pydict()["image"]
     assert generated_content == [{"path": image_file, "bytes": None}]





def      __a     (       _UpperCamelCase:   List[str]   )						->			List[str]:

     """simple docstring"""




     with open(_UpperCamelCase ,						encoding="utf-8"   ) as f:
          _snake_case							=				f.read().splitlines()[1:]
     _snake_case							=				Csv(encoding="utf-8" ,						features=Features({"label": ClassLabel(names=["good", "bad"]   )}   )   )
     _snake_case							=				csv._generate_tables([[csv_file_with_label]]   )
     _snake_case							=				pa.concat_tables([table for _, table in generator]   )
     assert pa_table.schema.field("label"   ).type == ClassLabel(names=["good", "bad"]   )()
     _snake_case							=				pa_table.to_pydict()["label"]
     assert generated_content == [ClassLabel(names=["good", "bad"]   ).straint(_UpperCamelCase   ) for label in labels]





def      __a     (       _UpperCamelCase:   Optional[int]   )						->			Optional[int]:

     """simple docstring"""




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








'''simple docstring'''





def      __a     (       _UpperCamelCase:   int   )						->			None:

     """simple docstring"""




     _snake_case							=				generate_pascal_triangle(_UpperCamelCase   )
     for row_idx in range(_UpperCamelCase   ):
          # Print left spaces
          for _ in range(num_rows - row_idx - 1   ):
               print(end=" "   )
          # Print row values
          for col_idx in range(row_idx + 1   ):
               if col_idx != row_idx:
                    print(triangle[row_idx][col_idx] ,						end=" "   )
               else:
                    print(triangle[row_idx][col_idx] ,						end=""   )
          print()





def      __a     (       _UpperCamelCase:   int   )						->			list[list[int]]:

     """simple docstring"""




     if not isinstance(_UpperCamelCase ,						_UpperCamelCase   ):
          raise TypeError("The input value of 'num_rows' should be 'int'"   )

     if num_rows == 0:
          return []
     elif num_rows < 0:
          raise ValueError(
              "The input value of 'num_rows' should be greater than or equal to 0"   )

     _snake_case							=				[]
     for current_row_idx in range(_UpperCamelCase   ):
          _snake_case							=				populate_current_row(_UpperCamelCase ,						_UpperCamelCase   )
          triangle.append(_UpperCamelCase   )
     return triangle





def      __a     (       _UpperCamelCase:   list[list[int]] ,						_UpperCamelCase:   int   )						->			list[int]:

     """simple docstring"""




     _snake_case							=				[-1] * (current_row_idx + 1)
     # first and last elements of current row are equal to 1
     _snake_case							, _snake_case							=				1, 1
     for current_col_idx in range(1 ,						_UpperCamelCase   ):
          calculate_current_element(
              _UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase   )
     return current_row





def      __a     (       _UpperCamelCase:   list[list[int]] ,						_UpperCamelCase:   list[int] ,						_UpperCamelCase:   int ,						_UpperCamelCase:   int ,						)						->			None:

     """simple docstring"""




     _snake_case							=				triangle[current_row_idx - 1][current_col_idx - 1]
     _snake_case							=				triangle[current_row_idx - 1][current_col_idx]
     _snake_case							=				above_to_left_elt + above_to_right_elt





def      __a     (       _UpperCamelCase:   int   )						->			list[list[int]]:

     """simple docstring"""




     if not isinstance(_UpperCamelCase ,						_UpperCamelCase   ):
          raise TypeError("The input value of 'num_rows' should be 'int'"   )

     if num_rows == 0:
          return []
     elif num_rows < 0:
          raise ValueError(
              "The input value of 'num_rows' should be greater than or equal to 0"   )

     _snake_case							=				[[1]]

     for row_index in range(1 ,						_UpperCamelCase   ):
          _snake_case							=				[0] + result[-1] + [0]
          _snake_case							=				row_index + 1
          # Calculate the number of distinct elements in a row
          _snake_case							=				sum(divmod(_UpperCamelCase ,						2   )   )
          _snake_case							=				[
              temp_row[i - 1] + temp_row[i] for i in range(1 ,						distinct_elements + 1   )
          ]
          _snake_case							=				row_first_half[: (row_index + 1) // 2]
          row_second_half.reverse()
          _snake_case							=				row_first_half + row_second_half
          result.append(_UpperCamelCase   )

     return result





def      __a     (       )						->			None:

     """simple docstring"""




     from collections.abc import Callable
     from timeit import timeit

     def benchmark_a_function(_UpperCamelCase:   Callable ,						_UpperCamelCase:   int   ) -> None:
          _snake_case							=				F"""{func.__name__}({value})"""
          _snake_case							=				timeit(F"""__main__.{call}""" ,						setup="import __main__"   )
          # print(f"{call:38} = {func(value)} -- {timing:.4f} seconds")
          print(F"""{call:38} -- {timing:.4f} seconds"""   )

     for value in range(15   ):  # (1, 7, 14):
          for func in (generate_pascal_triangle, generate_pascal_triangle_optimized):
               benchmark_a_function(_UpperCamelCase ,						_UpperCamelCase   )
          print()


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   benchmark()


