'''simple docstring'''


import contextlib
import os
import sqlitea

import pytest

from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy





def       lowerCAmelCase					(		UpperCamelCase__				:   Any    ,					UpperCamelCase__				:   Dict       ):


	"""simple docstring"""
	assert isinstance(UpperCamelCase__    ,					UpperCamelCase__       )
	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





@require_sqlalchemy
@pytest.mark.parametrize('''keep_in_memory'''    ,					[False, True]       )
def       lowerCAmelCase					(		UpperCamelCase__				:   List[Any]    ,					UpperCamelCase__				:   int    ,					UpperCamelCase__				:   List[Any]    ,					UpperCamelCase__				:   List[str]       ):


	"""simple docstring"""
	__UpperCAmelCase							=			tmp_path / '''cache'''
	__UpperCAmelCase							=			{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		__UpperCAmelCase							=			SqlDatasetReader(
		    '''dataset'''    ,					'''sqlite:///''' + sqlite_path    ,					cache_dir=UpperCamelCase__    ,					keep_in_memory=UpperCamelCase__       ).read()
	_check_sql_dataset(UpperCamelCase__    ,					UpperCamelCase__       )





@require_sqlalchemy
@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					(		UpperCamelCase__				:   Optional[Any]    ,					UpperCamelCase__				:   Union[str, Any]    ,					UpperCamelCase__				:   Any    ,					UpperCamelCase__				:   Tuple       ):


	"""simple docstring"""
	__UpperCAmelCase							=			tmp_path / '''cache'''
	__UpperCAmelCase							=			{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
	__UpperCAmelCase							=			features.copy() if features else default_expected_features
	__UpperCAmelCase							=			(
	    Features({feature: Value(UpperCamelCase__       ) for feature, dtype in features.items()}       ) if features is not None else None
	)
	__UpperCAmelCase							=			SqlDatasetReader('''dataset'''    ,					'''sqlite:///''' + sqlite_path    ,					features=UpperCamelCase__    ,					cache_dir=UpperCamelCase__       ).read()
	_check_sql_dataset(UpperCamelCase__    ,					UpperCamelCase__       )





def       lowerCAmelCase					(		UpperCamelCase__				:   List[str]       ):


	"""simple docstring"""
	with contextlib.closing(sqlitea.connect(UpperCamelCase__       )       ) as con:
		__UpperCAmelCase							=			con.cursor()
		cur.execute('''SELECT * FROM dataset'''       )
		for row in cur:
			yield row





@require_sqlalchemy
def       lowerCAmelCase					(		UpperCamelCase__				:   Optional[int]    ,					UpperCamelCase__				:   List[Any]    ,					UpperCamelCase__				:   int       ):


	"""simple docstring"""
	__UpperCAmelCase							=			tmp_path / '''cache'''
	__UpperCAmelCase							=			os.path.join(UpperCamelCase__    ,					'''tmp.sql'''       )
	__UpperCAmelCase							=			SqlDatasetReader('''dataset'''    ,					'''sqlite:///''' + sqlite_path    ,					cache_dir=UpperCamelCase__       ).read()
	SqlDatasetWriter(UpperCamelCase__    ,					'''dataset'''    ,					'''sqlite:///''' + output_sqlite_path    ,					num_proc=1       ).write()

	__UpperCAmelCase							=			iter_sql_file(UpperCamelCase__       )
	__UpperCAmelCase							=			iter_sql_file(UpperCamelCase__       )

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





@require_sqlalchemy
def       lowerCAmelCase					(		UpperCamelCase__				:   int    ,					UpperCamelCase__				:   int    ,					UpperCamelCase__				:   Any       ):


	"""simple docstring"""
	__UpperCAmelCase							=			tmp_path / '''cache'''
	__UpperCAmelCase							=			os.path.join(UpperCamelCase__    ,					'''tmp.sql'''       )
	__UpperCAmelCase							=			SqlDatasetReader('''dataset'''    ,					'''sqlite:///''' + sqlite_path    ,					cache_dir=UpperCamelCase__       ).read()
	SqlDatasetWriter(UpperCamelCase__    ,					'''dataset'''    ,					'''sqlite:///''' + output_sqlite_path    ,					num_proc=2       ).write()

	__UpperCAmelCase							=			iter_sql_file(UpperCamelCase__       )
	__UpperCAmelCase							=			iter_sql_file(UpperCamelCase__       )

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





@require_sqlalchemy
def       lowerCAmelCase					(		UpperCamelCase__				:   str    ,					UpperCamelCase__				:   Tuple    ,					UpperCamelCase__				:   str       ):


	"""simple docstring"""
	__UpperCAmelCase							=			tmp_path / '''cache'''
	__UpperCAmelCase							=			os.path.join(UpperCamelCase__    ,					'''tmp.sql'''       )
	__UpperCAmelCase							=			SqlDatasetReader('''dataset'''    ,					'''sqlite:///''' + sqlite_path    ,					cache_dir=UpperCamelCase__       ).read()
	with pytest.raises(UpperCamelCase__       ):
		SqlDatasetWriter(UpperCamelCase__    ,					'''dataset'''    ,					'''sqlite:///''' + output_sqlite_path    ,					num_proc=0       ).write()

'''simple docstring'''


from __future__ import annotations

from statistics import mean





def       lowerCAmelCase					(		UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   int       ):


	"""simple docstring"""
	__UpperCAmelCase							=			[0] * no_of_processes
	__UpperCAmelCase							=			[0] * no_of_processes

	# Initialize remaining_time to waiting_time.

	for i in range(UpperCamelCase__       ):
		__UpperCAmelCase							=			burst_time[i]
	__UpperCAmelCase							=			[]

	__UpperCAmelCase							=			0
	__UpperCAmelCase							=			0

	# When processes are not completed,
	# A process whose arrival time has passed \
	# and has remaining execution time is put into the ready_process.
	# The shortest process in the ready_process, target_process is executed.

	while completed != no_of_processes:
		__UpperCAmelCase							=			[]
		__UpperCAmelCase							=			-1

		for i in range(UpperCamelCase__       ):
			if (arrival_time[i] <= total_time) and (remaining_time[i] > 0):
				ready_process.append(UpperCamelCase__       )

		if len(UpperCamelCase__       ) > 0:
			__UpperCAmelCase							=			ready_process[0]
			for i in ready_process:
				if remaining_time[i] < remaining_time[target_process]:
					__UpperCAmelCase							=			i
			total_time += burst_time[target_process]
			completed += 1
			__UpperCAmelCase							=			0
			__UpperCAmelCase							=			(
			    total_time - arrival_time[target_process] - burst_time[target_process]
			)
		else:
			total_time += 1

	return waiting_time





def       lowerCAmelCase					(		UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   int    ,					UpperCamelCase__				:   list[int]       ):


	"""simple docstring"""
	__UpperCAmelCase							=			[0] * no_of_processes
	for i in range(UpperCamelCase__       ):
		__UpperCAmelCase							=			burst_time[i] + waiting_time[i]
	return turn_around_time


if __name__ == "__main__":
					print("[TEST CASE 01]")

					__lowerCAmelCase	:       List[Any]						       =	4
					__lowerCAmelCase	:       List[Any]						       =	[2, 5, 3, 7]
					__lowerCAmelCase	:       Tuple						       =	[0, 0, 0, 0]
					__lowerCAmelCase	:       Optional[int]						       =	calculate_waitingtime(arrival_time, burst_time, no_of_processes)
					__lowerCAmelCase	:       Dict						       =	calculate_turnaroundtime(
					    burst_time, no_of_processes, waiting_time
					)

					# Printing the Result
					print("PID\tBurst Time\tArrival Time\tWaiting Time\tTurnaround Time")
					for i, process_id in enumerate(list(range(1, 5))):
										print(
										    F"""{process_id}\t{burst_time[i]}\t\t\t{arrival_time[i]}\t\t\t\t"""
										    F"""{waiting_time[i]}\t\t\t\t{turn_around_time[i]}"""
										)
					print(F"""\nAverage waiting time = {mean(waiting_time):.5f}""")
					print(F"""Average turnaround time = {mean(turn_around_time):.5f}""")
