

"""simple docstring"""





import math
from collections.abc import Generator




def 						_A						(						UpperCamelCase_  : int)			->		Generator[int, None, None]:
   '''simple docstring'''


   __lowercase			=		(i for i in range(1,    (max_n + 1)))
   for i in (n for n in numbers if n > 1):
      for j in range(2,    UpperCamelCase_):
         if (i % j) == 0:
            break
      else:
         yield i




def 						_A						(						UpperCamelCase_  : int)			->		Generator[int, None, None]:
   '''simple docstring'''


   __lowercase			=		(i for i in range(1,    (max_n + 1)))
   for i in (n for n in numbers if n > 1):
      # only need to check for factors up to sqrt(i)
      __lowercase			=		int(math.sqrt(UpperCamelCase_)) + 1
      for j in range(2,    UpperCamelCase_):
         if (i % j) == 0:
            break
      else:
         yield i




def 						_A						(						UpperCamelCase_  : int)			->		Generator[int, None, None]:
   '''simple docstring'''


   __lowercase			=		(i for i in range(1,    (max_n + 1),    2))
   # It's useless to test even numbers as they will not be prime
   if max_n > 2:
      yield 2  # Because 2 will not be tested, it's necessary to yield it now
   for i in (n for n in numbers if n > 1):
      __lowercase			=		int(math.sqrt(UpperCamelCase_)) + 1
      for j in range(3,    UpperCamelCase_,    2):
         # As we removed the even numbers, we don't need them now
         if (i % j) == 0:
            break
      else:
         yield i




def 						_A						(						)			->		Dict:
   '''simple docstring'''


   from timeit import timeit

   __lowercase			=		"from __main__ import slow_primes, primes, fast_primes"
   print(timeit("slow_primes(1_000_000_000_000)",    setup=UpperCamelCase_,    number=1000000))
   print(timeit("primes(1_000_000_000_000)",    setup=UpperCamelCase_,    number=1000000))
   print(timeit("fast_primes(1_000_000_000_000)",    setup=UpperCamelCase_,    number=1000000))


if __name__ == "__main__":
   _a				   =							int(input('Calculate primes up to:\n>> ').strip())
   for ret in primes(number):
      print(ret)
   benchmark()







"""simple docstring"""





import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Value
from datasets.packaged_modules.json.json import Json




@pytest.fixture
def 						_A						(						UpperCamelCase_  : str)			->		Tuple:
   '''simple docstring'''


   __lowercase			=		tmp_path / "file.jsonl"
   __lowercase			=		textwrap.dedent(
       "\\n        {\"col_1\": -1}\n        {\"col_1\": 1, \"col_2\": 2}\n        {\"col_1\": 10, \"col_2\": 20}\n        ")
   with open(UpperCamelCase_,    "w") as f:
      f.write(UpperCamelCase_)
   return str(UpperCamelCase_)




@pytest.fixture
def 						_A						(						UpperCamelCase_  : str)			->		Any:
   '''simple docstring'''


   __lowercase			=		tmp_path / "file_utf16_encoded.jsonl"
   __lowercase			=		textwrap.dedent(
       "\\n        {\"col_1\": -1}\n        {\"col_1\": 1, \"col_2\": 2}\n        {\"col_1\": 10, \"col_2\": 20}\n        ")
   with open(UpperCamelCase_,    "w",    encoding="utf-16") as f:
      f.write(UpperCamelCase_)
   return str(UpperCamelCase_)




@pytest.fixture
def 						_A						(						UpperCamelCase_  : Optional[int])			->		Optional[Any]:
   '''simple docstring'''


   __lowercase			=		tmp_path / "file_with_list_of_dicts.json"
   __lowercase			=		textwrap.dedent(
       "\\n        [\n            {\"col_1\": -1},\n            {\"col_1\": 1, \"col_2\": 2},\n            {\"col_1\": 10, \"col_2\": 20}\n        ]\n        ")
   with open(UpperCamelCase_,    "w") as f:
      f.write(UpperCamelCase_)
   return str(UpperCamelCase_)




@pytest.fixture
def 						_A						(						UpperCamelCase_  : str)			->		int:
   '''simple docstring'''


   __lowercase			=		tmp_path / "file_with_list_of_dicts_field.json"
   __lowercase			=		textwrap.dedent(
       "\\n        {\n            \"field1\": 1,\n            \"field2\": \"aabb\",\n            \"field3\": [\n                {\"col_1\": -1},\n                {\"col_1\": 1, \"col_2\": 2},\n                {\"col_1\": 10, \"col_2\": 20}\n            ]\n        }\n        ")
   with open(UpperCamelCase_,    "w") as f:
      f.write(UpperCamelCase_)
   return str(UpperCamelCase_)




@pytest.mark.parametrize(
    "file_fixture, config_kwargs",    [
        ("jsonl_file", {}),
        ("jsonl_file_utf16_encoded", {"encoding": "utf-16"}),
        ("json_file_with_list_of_dicts", {}),
        ("json_file_with_list_of_dicts_field", {"field": "field3"}),
    ],    )
def 						_A						(						UpperCamelCase_  : Any,    UpperCamelCase_  : List[Any],    UpperCamelCase_  : Optional[Any])			->		List[Any]:
   '''simple docstring'''


   __lowercase			=		Json(**UpperCamelCase_)
   __lowercase			=		json._generate_tables([[request.getfixturevalue(UpperCamelCase_)]])
   __lowercase			=		pa.concat_tables([table for _, table in generator])
   assert pa_table.to_pydict() == {"col_1": [-1, 1, 10], "col_2": [None, 2, 20]}




@pytest.mark.parametrize(
    "file_fixture, config_kwargs",    [
        (
            "jsonl_file",
            {"features": Features({"col_1": Value("int64"), "col_2": Value("int64"), "missing_col": Value("string")})},
        ),
        (
            "json_file_with_list_of_dicts",
            {"features": Features({"col_1": Value("int64"), "col_2": Value("int64"), "missing_col": Value("string")})},
        ),
        (
            "json_file_with_list_of_dicts_field",
            {
                "field": "field3",
                "features": Features(
                    {"col_1": Value("int64"), "col_2": Value("int64"), "missing_col": Value("string")}),
            },
        ),
    ],    )
def 						_A						(						UpperCamelCase_  : Optional[int],    UpperCamelCase_  : int,    UpperCamelCase_  : str)			->		Optional[int]:
   '''simple docstring'''


   __lowercase			=		Json(**UpperCamelCase_)
   __lowercase			=		json._generate_tables([[request.getfixturevalue(UpperCamelCase_)]])
   __lowercase			=		pa.concat_tables([table for _, table in generator])
   assert pa_table.to_pydict() == {"col_1": [-1, 1, 10], "col_2": [None, 2, 20], "missing_col": [None, None, None]}




