



import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, 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
from datasets.utils.py_utils import Literal


lowercase_										=  datasets.utils.logging.get_logger(__name__)

lowercase_										=  ["names", "prefix"]
lowercase_										=  ["warn_bad_lines", "error_bad_lines", "mangle_dupe_cols"]
lowercase_										=  ["encoding_errors", "on_bad_lines"]
lowercase_										=  ["date_format"]
@dataclass
class 					_snake_case      (       datasets.BuilderConfig):
				UpperCamelCase__					:       Any  		=""","""
				UpperCamelCase__					:       List[Any]  		=None
				UpperCamelCase__					:       Optional[int]  		="""infer"""
				UpperCamelCase__					:       Dict  		=None
				UpperCamelCase__					:       List[str]  		=None
				UpperCamelCase__					:       int  		=None
				UpperCamelCase__					:       Optional[Any]  		=None
				UpperCamelCase__					:       Tuple  		=None
				UpperCamelCase__					:       str  		=True
				UpperCamelCase__					:       Optional[Any]  		=None
				UpperCamelCase__					:       Union[str, Any]  		=None
				UpperCamelCase__					:       Tuple  		=None
				UpperCamelCase__					:       Any  		=None
				UpperCamelCase__					:       Optional[int]  		=False
				UpperCamelCase__					:       str  		=None
				UpperCamelCase__					:       Any  		=None
				UpperCamelCase__					:       str  		=None
				UpperCamelCase__					:       str  		=True
				UpperCamelCase__					:       str  		=True
				UpperCamelCase__					:       Tuple  		=False
				UpperCamelCase__					:       Tuple  		=True
				UpperCamelCase__					:       int  		=None
				UpperCamelCase__					:       Any  		="""."""
				UpperCamelCase__					:       List[str]  		=None
				UpperCamelCase__					:       Dict  		="""\""""
				UpperCamelCase__					:       str  		=0
				UpperCamelCase__					:       Any  		=None
				UpperCamelCase__					:       Tuple  		=None
				UpperCamelCase__					:       int  		=None
				UpperCamelCase__					:       Optional[Any]  		=None
				UpperCamelCase__					:       Dict  		=True
				UpperCamelCase__					:       Any  		=True
				UpperCamelCase__					:       str  		=0
				UpperCamelCase__					:       Union[str, Any]  		=True
				UpperCamelCase__					:       List[Any]  		=False
				UpperCamelCase__					:       Optional[Any]  		=None
				UpperCamelCase__					:       int  		=1_0_0_0_0
				UpperCamelCase__					:       List[Any]  		=None
				UpperCamelCase__					:       Tuple  		="""strict"""
				UpperCamelCase__					:       List[str]  		="""error"""
				UpperCamelCase__					:       List[str]  		=None




				def 				A__   (    self       :    int    ):
							if self.delimiter is not None:
										lowercase__       	=					self.delimiter
							if self.column_names is not None:
										lowercase__       	=					self.column_names




				@property
				def 				A__   (    self       :    int    ):
							lowercase__       	=					{
							    "sep": self.sep,
							    "header": self.header,
							    "names": self.names,
							    "index_col": self.index_col,
							    "usecols": self.usecols,
							    "prefix": self.prefix,
							    "mangle_dupe_cols": self.mangle_dupe_cols,
							    "engine": self.engine,
							    "converters": self.converters,
							    "true_values": self.true_values,
							    "false_values": self.false_values,
							    "skipinitialspace": self.skipinitialspace,
							    "skiprows": self.skiprows,
							    "nrows": self.nrows,
							    "na_values": self.na_values,
							    "keep_default_na": self.keep_default_na,
							    "na_filter": self.na_filter,
							    "verbose": self.verbose,
							    "skip_blank_lines": self.skip_blank_lines,
							    "thousands": self.thousands,
							    "decimal": self.decimal,
							    "lineterminator": self.lineterminator,
							    "quotechar": self.quotechar,
							    "quoting": self.quoting,
							    "escapechar": self.escapechar,
							    "comment": self.comment,
							    "encoding": self.encoding,
							    "dialect": self.dialect,
							    "error_bad_lines": self.error_bad_lines,
							    "warn_bad_lines": self.warn_bad_lines,
							    "skipfooter": self.skipfooter,
							    "doublequote": self.doublequote,
							    "memory_map": self.memory_map,
							    "float_precision": self.float_precision,
							    "chunksize": self.chunksize,
							    "encoding_errors": self.encoding_errors,
							    "on_bad_lines": self.on_bad_lines,
							    "date_format": self.date_format,
							}

							# some kwargs must not be passed if they don't have a default value
							# some others are deprecated and we can also not pass them if they are the default value
							for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
										if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig(),       a_    ):
													del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
							if not (datasets.config.PANDAS_VERSION.major >= 2):
										for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
													del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
							if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
										for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
													del pd_read_csv_kwargs[pd_read_csv_parameter]

							return pd_read_csv_kwargs
class 					_snake_case      (       datasets.ArrowBasedBuilder):
				UpperCamelCase__					:       Optional[Any]  		=CsvConfig




				def 				A__   (    self       :    Any    ):
							return datasets.DatasetInfo(features=self.config.features    )




				def 				A__   (    self       :    str,       __lowercase       :    Dict    ):
							if not self.config.data_files:
										raise ValueError(F'''At least one data file must be specified, but got data_files={self.config.data_files}'''    )
							lowercase__       	=					dl_manager.download_and_extract(self.config.data_files    )
							if isinstance(a_,       (str, list, tuple)    ):
										lowercase__       	=					data_files
										if isinstance(a_,       a_    ):
													lowercase__       	=					[files]
										lowercase__       	=					[dl_manager.iter_files(a_    ) for file in files]
										return [datasets.SplitGenerator(name=datasets.Split.TRAIN,       gen_kwargs={"files": files}    )]
							lowercase__       	=					[]
							for split_name, files in data_files.items():
										if isinstance(a_,       a_    ):
													lowercase__       	=					[files]
										lowercase__       	=					[dl_manager.iter_files(a_    ) for file in files]
										splits.append(datasets.SplitGenerator(name=a_,       gen_kwargs={"files": files}    )    )
							return splits




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




				def 				A__   (    self       :    Dict,       __lowercase       :    int    ):
							lowercase__       	=					self.config.features.arrow_schema if self.config.features else None
							# dtype allows reading an int column as str
							lowercase__       	=					(
							    {
							        name: dtype.to_pandas_dtype() if not require_storage_cast(a_    ) else object
							        for name, dtype, feature in zip(schema.names,       schema.types,       self.config.features.values()    )
							    }
							    if schema is not None
							    else None
							)
							for file_idx, file in enumerate(itertools.chain.from_iterable(a_    )    ):
										lowercase__       	=					pd.read_csv(a_,       iterator=a_,       dtype=a_,       **self.config.pd_read_csv_kwargs    )
										try:
													for batch_idx, df in enumerate(a_    ):
																lowercase__       	=					pa.Table.from_pandas(a_    )
																# Uncomment for debugging (will print the Arrow table size and elements)
																# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
																# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																yield (file_idx, batch_idx), self._cast_table(a_    )
										except ValueError as e:
													logger.error(F'''Failed to read file \'{file}\' with error {type(a_    )}: {e}'''    )
													raise









import numpy as np


class 	__snake_case   :
		def __init__(							self						):







						"""simple docstring"""
						lowerCAmelCase__		  =  (0, 0)
						lowerCAmelCase__		  =  None
						lowerCAmelCase__		  =  0
						lowerCAmelCase__		  =  0
						lowerCAmelCase__		  =  0
		def __eq__(							self    ,a_						):







						"""simple docstring"""
						return self.position == cell.position



		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						print(self.position						)



class 	__snake_case   :
		def __init__(							self    ,a_=(5, 5)						):







						"""simple docstring"""
						lowerCAmelCase__		  =  np.zeros(a_						)
						lowerCAmelCase__		  =  world_size[0]
						lowerCAmelCase__		  =  world_size[1]
		def 						SCREAMING_SNAKE_CASE_					(							self						):







						"""simple docstring"""
						print(self.w						)



		def 						SCREAMING_SNAKE_CASE_					(							self    ,a_						):







						"""simple docstring"""
						lowerCAmelCase__		  =  [
						    (-1, -1),
						    (-1, 0),
						    (-1, 1),
						    (0, -1),
						    (0, 1),
						    (1, -1),
						    (1, 0),
						    (1, 1),
						]
						lowerCAmelCase__		  =  cell.position[0]
						lowerCAmelCase__		  =  cell.position[1]
						lowerCAmelCase__		  =  []
						for n in neughbour_cord:
										lowerCAmelCase__		  =  current_x + n[0]
										lowerCAmelCase__		  =  current_y + n[1]
										if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
														lowerCAmelCase__		  =  Cell()
														lowerCAmelCase__		  =  (x, y)
														lowerCAmelCase__		  =  cell
														neighbours.append(a_						)
						return neighbours







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__					)	->     int:



				"""simple docstring"""





				lowerCAmelCase__		  =  []
				lowerCAmelCase__		  =  []
				_open.append(snake_case__					)

				while _open:
								lowerCAmelCase__		  =  np.argmin([n.f for n in _open]					)
								lowerCAmelCase__		  =  _open[min_f]
								_closed.append(_open.pop(snake_case__					)					)
								if current == goal:
												break
								for n in world.get_neigbours(snake_case__					):
												for c in _closed:
																if c == n:
																				continue
												lowerCAmelCase__		  =  current.g + 1
												lowerCAmelCase__  ,   lowerCAmelCase__		  =  n.position
												lowerCAmelCase__  ,   lowerCAmelCase__		  =  goal.position
												lowerCAmelCase__		  =  (ya - ya) ** 2 + (xa - xa) ** 2
												lowerCAmelCase__		  =  n.h + n.g

												for c in _open:
																if c == n and c.f < n.f:
																				continue
												_open.append(snake_case__					)
				lowerCAmelCase__		  =  []
				while current.parent is not None:
								path.append(current.position					)
								lowerCAmelCase__		  =  current.parent
				path.append(current.position					)
				return path[::-1]


if __name__ == "__main__":
	_lowerCAmelCase	:   str    =   Gridworld()
	# Start position and goal
	_lowerCAmelCase	:   List[Any]    =   Cell()
	_lowerCAmelCase	:   List[str]    =   (0, 0)
	_lowerCAmelCase	:   Optional[int]    =   Cell()
	_lowerCAmelCase	:   int    =   (4, 4)
	print(f"""path from {start.position} to {goal.position}""")
	_lowerCAmelCase	:   Optional[int]    =   astar(world, start, goal)
	#   Just for visual reasons.
	for i in s:
		_lowerCAmelCase	:   int    =   1
	print(world.w)
