




'''simple docstring'''





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


a		:	List[Any]       =      datasets.utils.logging.get_logger(__name__)




@dataclass
class      UpperCamelCase       (	datasets.BuilderConfig       ):
  a     :Union[str, "sqlalchemy.sql.Selectable"]          =					None
  a     :Union[str, "sqlalchemy.engine.Connection", "sqlalchemy.engine.Engine", "sqlite3.Connection"]          =					None
  a     :Optional[Union[str, List[str]]]          =					None
  a     :bool          =					True
  a     :Optional[Union[List, Tuple, Dict]]          =					None
  a     :Optional[Union[List, Dict]]          =					None
  a     :Optional[List[str]]          =					None
  a     :Optional[int]          =					1_0_0_0_0
  a     :Optional[datasets.Features]          =					None



  def     a_							(			self ):







      '''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     a_							(			self		,     __lowerCAmelCase		,     __lowerCAmelCase = None		,     ):







      '''simple docstring'''


      _a				:							Optional[int]							       =      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				:							List[str]							       =      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				:							Optional[int]							       =      sqlalchemy.create_engine(config_kwargs["""con"""].split("""://""" )[0] + """://""" )
                  _a				:							Tuple							       =      str(sql.compile(dialect=engine.dialect ) )
                  _a				:							int							       =      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				:							Any							       =      config_kwargs["""con"""]
      if not isinstance(__lowerCAmelCase		,     __lowerCAmelCase ):
          _a				:							Tuple							       =      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     a_							(			self ):







      '''simple docstring'''


      _a				:							Any							       =      {
          """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      UpperCamelCase       (	datasets.ArrowBasedBuilder       ):
  a     :List[Any]          =					SqlConfig



  def     a_							(			self ):







      '''simple docstring'''


      return datasets.DatasetInfo(features=self.config.features )



  def     a_							(			self		,     __lowerCAmelCase ):







      '''simple docstring'''


      return [datasets.SplitGenerator(name=datasets.Split.TRAIN		,     gen_kwargs={} )]



  def     a_							(			self		,     __lowerCAmelCase ):







      '''simple docstring'''


      if self.config.features is not None:
          _a				:							List[Any]							       =      self.config.features.arrow_schema
          if all(not require_storage_cast(__lowerCAmelCase ) for feature in self.config.features.values() ):
              # cheaper cast
              _a				:							str							       =      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				:							Optional[Any]							       =      table_cast(__lowerCAmelCase		,     __lowerCAmelCase )
      return pa_table



  def     a_							(			self ):







      '''simple docstring'''


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










from __future__ import annotations


def __A       ( __lowerCAmelCase					,						__lowerCAmelCase					,						__lowerCAmelCase					,						)->    list[float | int]:





						"""simple docstring"""



						if not all((nth_term, start_term_a, common_ratio_r)      ):
												return []
						_UpperCAmelCase							   =     []
						_UpperCAmelCase							   =     1
						_UpperCAmelCase							   =     common_ratio_r
						for _ in range(int(__lowerCAmelCase      )      ):
												if not series:
																		series.append(__lowerCAmelCase      )
												else:
																		power += 1
																		series.append(float(start_term_a * multiple      )      )
																		_UpperCAmelCase							   =     pow(float(__lowerCAmelCase      )					,						__lowerCAmelCase      )
						return series


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		_a       =    float(input('''Enter the last number (n term) of the Geometric Series'''))
		_a       =    float(input('''Enter the starting term (a) of the Geometric Series'''))
		_a       =    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))
