






from __future__ import annotations

from collections import deque
from enum import Enum
from math import atana, degrees
from sys import maxsize







class 				lowerCamelCase_     (	UpperCamelCase__     ):
							SCREAMING_SNAKE_CASE_						     =			1
							SCREAMING_SNAKE_CASE_						     =			2
							SCREAMING_SNAKE_CASE_						     =			3
							def __repr__(						self		:					Any					):





								'''simple docstring'''



								return F"""{self.__class__.__name__}.{self.name}"""





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_,  snake_case_  )   ->  float:


	"""simple docstring"""



	a		=			point
	return degrees(atana(y - miny,  x - minx  )  )





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_,  snake_case_  )   ->  Direction:


	"""simple docstring"""



	a		=			starting
	a		=			via
	a		=			target
	a		=			degrees(atana(ya - ya,  xa - xa  )  )
	via_angle %= 3_6_0
	a		=			degrees(atana(ya - ya,  xa - xa  )  )
	target_angle %= 3_6_0
	# t-
	#  \ \
	#   \ v
	#    \|
	#     s
	# via_angle is always lower than target_angle, if direction is left.
	# If they are same, it means they are on a same line of convex hull.
	if target_angle > via_angle:
		return Direction.left
	elif target_angle == via_angle:
		return Direction.straight
	else:
		return Direction.right





def   SCREAMING_SNAKE_CASE__						(   snake_case_  )   ->  list[tuple[int, int]]:


	"""simple docstring"""



	if len(__a  ) <= 2:
		# There is no convex hull
		raise ValueError('''graham_scan: argument must contain more than 3 points.'''  )
	if len(__a  ) == 3:
		return points
	# find the lowest and the most left point
	a		=			0
	a		=			maxsize, maxsize
	for i, point in enumerate(__a  ):
		a		=			point[0]
		a		=			point[1]
		if y < miny:
			a		=			y
			a		=			x
			a		=			i
		if y == miny and x < minx:
			a		=			x
			a		=			i

    # remove the lowest and the most left point from points for preparing for sort
	points.pop(__a  )

	a		=			sorted(__a,  key=lambda snake_case_  : angle_comparer(__a,  __a,  __a  )  )
	# This insert actually costs complexity,
	# and you should instead add (minx, miny) into stack later.
	# I'm using insert just for easy understanding.
	sorted_points.insert(0,  (minx, miny)  )

	a		=			deque()
	stack.append(sorted_points[0]  )
	stack.append(sorted_points[1]  )
	stack.append(sorted_points[2]  )
	# In any ways, the first 3 points line are towards left.
	# Because we sort them the angle from minx, miny.
	a		=			Direction.left

	for i in range(3,  len(__a  )  ):
		while True:
			a		=			stack[-2]
			a		=			stack[-1]
			a		=			sorted_points[i]
			a		=			check_direction(__a,  __a,  __a  )

			if next_direction == Direction.left:
				a		=			Direction.left
				break
			if next_direction == Direction.straight:
				if current_direction == Direction.left:
					# We keep current_direction as left.
					# Because if the straight line keeps as straight,
					# we want to know if this straight line is towards left.
					break
				elif current_direction == Direction.right:
					# If the straight line is towards right,
					# every previous points on those straigh line is not convex hull.
					stack.pop()
			if next_direction == Direction.right:
				stack.pop()
		stack.append(sorted_points[i]  )
	return list(__a  )













import sys
from dataclasses import dataclass
from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast


if TYPE_CHECKING:
				import sqlitea

				import sqlalchemy


UpperCamelCase__						:      Tuple								=					datasets.utils.logging.get_logger(__name__)







@dataclass
class 				lowerCamelCase_     (	datasets.BuilderConfig     ):
							SCREAMING_SNAKE_CASE_						     =			None
							SCREAMING_SNAKE_CASE_						     =			None
							SCREAMING_SNAKE_CASE_						     =			None
							SCREAMING_SNAKE_CASE_						     =			True
							SCREAMING_SNAKE_CASE_						     =			None
							SCREAMING_SNAKE_CASE_						     =			None
							SCREAMING_SNAKE_CASE_						     =			None
							SCREAMING_SNAKE_CASE_						     =			1_00_00
							SCREAMING_SNAKE_CASE_						     =			None
							def  SCREAMING_SNAKE_CASE_ (						self		:					Optional[Any]					):





								'''simple docstring'''



								if self.sql is None:
									raise ValueError('''sql must be specified'''					)
								if self.con is None:
									raise ValueError('''con must be specified'''					)
							def  SCREAMING_SNAKE_CASE_ (						self		:					Any							,__lowerCamelCase		:					dict							,__lowerCamelCase		:					Optional[datasets.Features] = None							,):





								'''simple docstring'''



								a		=			config_kwargs.copy()
								# We need to stringify the Selectable object to make its hash deterministic

								# The process of stringifying is explained here: http://docs.sqlalchemy.org/en/latest/faq/sqlexpressions.html
								a		=			config_kwargs['''sql''']
								if not isinstance(__lowerCamelCase							,__lowerCamelCase					):
									if datasets.config.SQLALCHEMY_AVAILABLE and "sqlalchemy" in sys.modules:
										import sqlalchemy

										if isinstance(__lowerCamelCase							,sqlalchemy.sql.Selectable					):
											a		=			sqlalchemy.create_engine(config_kwargs['''con'''].split('''://'''					)[0] + '''://'''					)
											a		=			str(sql.compile(dialect=engine.dialect					)					)
											a		=			sql_str
										else:
											raise TypeError(
											    F"""Supported types for 'sql' are string and sqlalchemy.sql.Selectable but got {type(__lowerCamelCase					)}: {sql}"""					)
									else:
										raise TypeError(
										    F"""Supported types for 'sql' are string and sqlalchemy.sql.Selectable but got {type(__lowerCamelCase					)}: {sql}"""					)
								a		=			config_kwargs['''con''']
								if not isinstance(__lowerCamelCase							,__lowerCamelCase					):
									a		=			id(__lowerCamelCase					)
									logger.info(
									    F"""SQL connection 'con' of type {type(__lowerCamelCase					)} couldn't be hashed properly. To enable hashing, specify 'con' as URI string instead."""					)

								return super().create_config_id(__lowerCamelCase							,custom_features=__lowerCamelCase					)




							@property
							def  SCREAMING_SNAKE_CASE_ (						self		:					Dict					):





								'''simple docstring'''



								a		=			{
								    '''index_col''': self.index_col,
								    '''columns''': self.columns,
								    '''params''': self.params,
								    '''coerce_float''': self.coerce_float,
								    '''parse_dates''': self.parse_dates,
								}
								return pd_read_sql_kwargs







class 				lowerCamelCase_     (	datasets.ArrowBasedBuilder     ):
							SCREAMING_SNAKE_CASE_						     =			SqlConfig
							def  SCREAMING_SNAKE_CASE_ (						self		:					Optional[Any]					):





								'''simple docstring'''



								return datasets.DatasetInfo(features=self.config.features					)
							def  SCREAMING_SNAKE_CASE_ (						self		:					Union[str, Any]							,__lowerCamelCase		:					int					):





								'''simple docstring'''



								return [datasets.SplitGenerator(name=datasets.Split.TRAIN							,gen_kwargs={}					)]
							def  SCREAMING_SNAKE_CASE_ (						self		:					Tuple							,__lowerCamelCase		:					pa.Table					):





								'''simple docstring'''



								if self.config.features is not None:
									a		=			self.config.features.arrow_schema
									if all(not require_storage_cast(__lowerCamelCase					) for feature in self.config.features.values()					):
										# cheaper cast
										a		=			pa.Table.from_arrays([pa_table[field.name] for field in schema]							,schema=__lowerCamelCase					)
									else:
										# more expensive cast; allows str <-> int/float or str to Audio for example
										a		=			table_cast(__lowerCamelCase							,__lowerCamelCase					)
								return pa_table




							def  SCREAMING_SNAKE_CASE_ (						self		:					str					):





								'''simple docstring'''



								a		=			self.config.chunksize
								a		=			pd.read_sql(
								    self.config.sql							,self.config.con							,chunksize=__lowerCamelCase							,**self.config.pd_read_sql_kwargs					)
								a		=			[sql_reader] if chunksize is None else sql_reader
								for chunk_idx, df in enumerate(__lowerCamelCase					):
									a		=			pa.Table.from_pandas(__lowerCamelCase					)
									yield chunk_idx, self._cast_table(__lowerCamelCase					)





