




"""simple docstring"""





import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases

def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						assert isinstance(lowerCamelCase      ,			lowerCamelCase		)
						assert dataset.num_rows == 4
						assert dataset.num_columns == 3
						assert dataset.column_names == ["col_1", "col_2", "col_3"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize('''keep_in_memory'''      ,			[False, True]		)
def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						snake_case__       :					List[Any]										=					tmp_path / '''cache'''
						snake_case__       :					int										=					{'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												snake_case__       :					Optional[Any]										=					CsvDatasetReader(lowerCamelCase      ,			cache_dir=lowerCamelCase      ,			keep_in_memory=lowerCamelCase		).read()
						_check_csv_dataset(lowerCamelCase      ,			lowerCamelCase		)

@pytest.mark.parametrize(
    '''features'''      ,			[
        None,
        {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''},
        {'''col_1''': '''string''', '''col_2''': '''string''', '''col_3''': '''string'''},
        {'''col_1''': '''int32''', '''col_2''': '''int32''', '''col_3''': '''int32'''},
        {'''col_1''': '''float32''', '''col_2''': '''float32''', '''col_3''': '''float32'''},
    ]      ,			)
def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						snake_case__       :					Optional[Any]										=					tmp_path / '''cache'''
						# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
						snake_case__       :					Dict										=					{'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						snake_case__       :					Optional[int]										=					features.copy() if features else default_expected_features
						snake_case__       :					str										=					(
						    Features({feature: Value(lowerCamelCase		) for feature, dtype in features.items()}		) if features is not None else None
						)
						snake_case__       :					List[Any]										=					CsvDatasetReader(lowerCamelCase      ,			features=lowerCamelCase      ,			cache_dir=lowerCamelCase		).read()
						_check_csv_dataset(lowerCamelCase      ,			lowerCamelCase		)

@pytest.mark.parametrize('''split'''      ,			[None, NamedSplit('''train'''		), '''train''', '''test''']		)
def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						snake_case__       :					str										=					tmp_path / '''cache'''
						snake_case__       :					int										=					{'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						snake_case__       :					List[str]										=					CsvDatasetReader(lowerCamelCase      ,			cache_dir=lowerCamelCase      ,			split=lowerCamelCase		).read()
						_check_csv_dataset(lowerCamelCase      ,			lowerCamelCase		)
						assert dataset.split == split if split else "train"

@pytest.mark.parametrize('''path_type'''      ,			[str, list]		)
def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						if issubclass(lowerCamelCase      ,			lowerCamelCase		):
												snake_case__       :					List[str]										=					csv_path
						elif issubclass(lowerCamelCase      ,			lowerCamelCase		):
												snake_case__       :					List[str]										=					[csv_path]
						snake_case__       :					Optional[Any]										=					tmp_path / '''cache'''
						snake_case__       :					Any										=					{'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						snake_case__       :					Tuple										=					CsvDatasetReader(lowerCamelCase      ,			cache_dir=lowerCamelCase		).read()
						_check_csv_dataset(lowerCamelCase      ,			lowerCamelCase		)

def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase=("train",)		):
						'''simple docstring'''


						assert isinstance(lowerCamelCase      ,			lowerCamelCase		)
						for split in splits:
												snake_case__       :					Any										=					dataset_dict[split]
												assert dataset.num_rows == 4
												assert dataset.num_columns == 3
												assert dataset.column_names == ["col_1", "col_2", "col_3"]
												for feature, expected_dtype in expected_features.items():
																		assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize('''keep_in_memory'''      ,			[False, True]		)
def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						snake_case__       :					List[Any]										=					tmp_path / '''cache'''
						snake_case__       :					int										=					{'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												snake_case__       :					Union[str, Any]										=					CsvDatasetReader({'''train''': csv_path}      ,			cache_dir=lowerCamelCase      ,			keep_in_memory=lowerCamelCase		).read()
						_check_csv_datasetdict(lowerCamelCase      ,			lowerCamelCase		)

@pytest.mark.parametrize(
    '''features'''      ,			[
        None,
        {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''},
        {'''col_1''': '''string''', '''col_2''': '''string''', '''col_3''': '''string'''},
        {'''col_1''': '''int32''', '''col_2''': '''int32''', '''col_3''': '''int32'''},
        {'''col_1''': '''float32''', '''col_2''': '''float32''', '''col_3''': '''float32'''},
    ]      ,			)
def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						snake_case__       :					Tuple										=					tmp_path / '''cache'''
						# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
						snake_case__       :					List[Any]										=					{'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						snake_case__       :					str										=					features.copy() if features else default_expected_features
						snake_case__       :					List[Any]										=					(
						    Features({feature: Value(lowerCamelCase		) for feature, dtype in features.items()}		) if features is not None else None
						)
						snake_case__       :					List[str]										=					CsvDatasetReader({'''train''': csv_path}      ,			features=lowerCamelCase      ,			cache_dir=lowerCamelCase		).read()
						_check_csv_datasetdict(lowerCamelCase      ,			lowerCamelCase		)

@pytest.mark.parametrize('''split'''      ,			[None, NamedSplit('''train'''		), '''train''', '''test''']		)
def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						if split:
												snake_case__       :					List[str]										=					{split: csv_path}
						else:
												snake_case__       :					int										=					{'''train''': csv_path, '''test''': csv_path}
						snake_case__       :					Tuple										=					tmp_path / '''cache'''
						snake_case__       :					Optional[int]										=					{'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						snake_case__       :					List[str]										=					CsvDatasetReader(lowerCamelCase      ,			cache_dir=lowerCamelCase		).read()
						_check_csv_datasetdict(lowerCamelCase      ,			lowerCamelCase      ,			splits=list(path.keys()		)		)
						assert all(dataset[split].split == split for split in path.keys()		)

def 		lowerCAmelCase							( lowerCamelCase		):
						'''simple docstring'''


						with open(lowerCamelCase      ,			encoding='''utf-8'''		) as csvfile:
												yield from csv.reader(lowerCamelCase		)

def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						snake_case__       :					Optional[int]										=					tmp_path / '''cache'''
						snake_case__       :					Any										=					os.path.join(lowerCamelCase      ,			'''tmp.csv'''		)
						snake_case__       :					Any										=					CsvDatasetReader({'''train''': csv_path}      ,			cache_dir=lowerCamelCase		).read()
						CsvDatasetWriter(dataset['''train''']      ,			lowerCamelCase      ,			num_proc=1		).write()

						snake_case__       :					str										=					iter_csv_file(lowerCamelCase		)
						snake_case__       :					Tuple										=					iter_csv_file(lowerCamelCase		)

						for rowa, rowa in zip(lowerCamelCase      ,			lowerCamelCase		):
												assert rowa == rowa

def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						snake_case__       :					Optional[Any]										=					tmp_path / '''cache'''
						snake_case__       :					Any										=					os.path.join(lowerCamelCase      ,			'''tmp.csv'''		)
						snake_case__       :					List[Any]										=					CsvDatasetReader({'''train''': csv_path}      ,			cache_dir=lowerCamelCase		).read()
						CsvDatasetWriter(dataset['''train''']      ,			lowerCamelCase      ,			num_proc=2		).write()

						snake_case__       :					int										=					iter_csv_file(lowerCamelCase		)
						snake_case__       :					Any										=					iter_csv_file(lowerCamelCase		)

						for rowa, rowa in zip(lowerCamelCase      ,			lowerCamelCase		):
												assert rowa == rowa

def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase		):
						'''simple docstring'''


						snake_case__       :					List[Any]										=					tmp_path / '''cache'''
						snake_case__       :					int										=					os.path.join(lowerCamelCase      ,			'''tmp.csv'''		)
						snake_case__       :					Dict										=					CsvDatasetReader({'''train''': csv_path}      ,			cache_dir=lowerCamelCase		).read()
						with pytest.raises(lowerCamelCase		):
												CsvDatasetWriter(dataset['''train''']      ,			lowerCamelCase      ,			num_proc=0		)








"""simple docstring"""





from __future__ import annotations

def 		lowerCAmelCase							( lowerCamelCase      ,			lowerCamelCase      ,			lowerCamelCase      ,			):
						'''simple docstring'''


						if not all((nth_term, start_term_a, common_ratio_r)		):
												return []
						snake_case__       :					list[float | int]										=					[]
						snake_case__       :					List[str]										=					1
						snake_case__       :					Dict										=					common_ratio_r
						for _ in range(int(lowerCamelCase		)		):
												if not series:
																		series.append(lowerCamelCase		)
												else:
																		power += 1
																		series.append(float(start_term_a * multiple		)		)
																		snake_case__       :					Tuple										=					pow(float(lowerCamelCase		)      ,			lowerCamelCase		)
						return series


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							_lowercase	      =    float(input("""Enter the last number (n term) of the Geometric Series"""))
							_lowercase	      =    float(input("""Enter the starting term (a) of the Geometric Series"""))
							_lowercase	      =    float(
							    input("""Enter the common ratio between two terms (r) of the Geometric Series""")
							)
							print("""Formula of Geometric Series => a + ar + ar^2 ... +ar^n""")
							print(geometric_series(nth_term, start_term_a, common_ratio_r))


