
"""simple docstring"""







import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_SCREAMING_SNAKE_CASE	       =      50_000
_SCREAMING_SNAKE_CASE	       =      5_000

_SCREAMING_SNAKE_CASE       ,							_SCREAMING_SNAKE_CASE	       =      os.path.split(__file__)
_SCREAMING_SNAKE_CASE	       =      os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))
@get_duration
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     Tuple:







							"""simple docstring"""


							for i in range(lowerCAmelCase__ ):
														__snake_case     			=       dataset[i]
@get_duration
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     str:







							"""simple docstring"""


							for i in range(0							,    len(lowerCAmelCase__ )							,    lowerCAmelCase__ ):
														__snake_case     			=       dataset[i : i + batch_size]
@get_duration
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     Dict:







							"""simple docstring"""


							with dataset.formatted_as(type=lowerCAmelCase__ ):
														for i in range(lowerCAmelCase__ ):
																					__snake_case     			=       dataset[i]
@get_duration
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     Dict:







							"""simple docstring"""


							with dataset.formatted_as(type=lowerCAmelCase__ ):
														for i in range(0							,    lowerCAmelCase__							,    lowerCAmelCase__ ):
																					__snake_case     			=       dataset[i : i + batch_size]
def   __UpperCamelCase   (					)  ->     List[str]:







							"""simple docstring"""


							__snake_case     			=       {'num examples': SPEED_TEST_N_EXAMPLES}
							__snake_case     			=       [
							    (read, {'length': SMALL_TEST}),
							    (read, {'length': SPEED_TEST_N_EXAMPLES}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_00}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10_00}),
							    (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
							    (read_formatted, {'type': 'pandas', 'length': SMALL_TEST}),
							    (read_formatted, {'type': 'torch', 'length': SMALL_TEST}),
							    (read_formatted, {'type': 'tensorflow', 'length': SMALL_TEST}),
							    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10}),
							    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10_00}),
							]

							__snake_case     			=       [
							    (read, {'length': SMALL_TEST}),
							    (read, {'length': SPEED_TEST_N_EXAMPLES}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_00}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10_00}),
							    (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
							    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10}),
							    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10_00}),
							]
							with tempfile.TemporaryDirectory() as tmp_dir:
														print("generating dataset" )
														__snake_case     			=       datasets.Features(
														    {"list": datasets.Sequence(datasets.Value("float32" ) ), "numbers": datasets.Value("float32" )} )
														__snake_case     			=       generate_example_dataset(
														    os.path.join(lowerCAmelCase__							,    "dataset.arrow" )							,    lowerCAmelCase__							,    num_examples=lowerCAmelCase__							,    seq_shapes={"list": (1_00,)}							,    )
														print("first set of iterations" )
														for func, kwargs in functions:
																					print(func.__name__							,    str(lowerCAmelCase__ ) )
																					__snake_case     			=       func(lowerCAmelCase__							,    **lowerCAmelCase__ )

														print("shuffling dataset" )
														__snake_case     			=       dataset.shuffle()
														print("Second set of iterations (after shuffling" )
														for func, kwargs in functions_shuffled:
																					print("shuffled "							,    func.__name__							,    str(lowerCAmelCase__ ) )
																					__snake_case     			=       func(
																					    lowerCAmelCase__							,    **lowerCAmelCase__ )

							with open(lowerCAmelCase__							,    "wb" ) as f:
														f.write(json.dumps(lowerCAmelCase__ ).encode("utf-8" ) )


if __name__ == "__main__":  # useful to run the profiler
		benchmark_iterating()


"""simple docstring"""







from __future__ import annotations

_SCREAMING_SNAKE_CASE	       =      {
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}







class 							__magic_name__     :





					def __init__(				self   :							Any							,						snake_case_   :							dict[str, list[str]]							,						snake_case_   :							str    ):
												__snake_case     			=       graph
												# mapping node to its parent in resulting breadth first tree
												__snake_case     			=       {}
												__snake_case     			=       source_vertex





					def 							lowerCAmelCase      (				self   :							Union[str, Any]    ):
												__snake_case     			=       {self.source_vertex}
												__snake_case     			=       None
												__snake_case     			=       [self.source_vertex]  # first in first out queue

												while queue:
																			__snake_case     			=       queue.pop(0    )
																			for adjacent_vertex in self.graph[vertex]:
																										if adjacent_vertex not in visited:
																																	visited.add(snake_case_    )
																																	__snake_case     			=       vertex
																																	queue.append(snake_case_    )





					def 							lowerCAmelCase      (				self   :							Dict							,						snake_case_   :							str    ):
												if target_vertex == self.source_vertex:
																			return self.source_vertex

												__snake_case     			=       self.parent.get(snake_case_    )
												if target_vertex_parent is None:
																			__snake_case     			=       (
																			    F'''No path from vertex: {self.source_vertex} to vertex: {target_vertex}'''
																			)
																			raise ValueError(snake_case_    )

												return self.shortest_path(snake_case_    ) + F'''->{target_vertex}'''


if __name__ == "__main__":
		_SCREAMING_SNAKE_CASE	       =      Graph(graph, """G""")
		g.breath_first_search()
		print(g.shortest_path("""D"""))
		print(g.shortest_path("""G"""))
		print(g.shortest_path("""Foo"""))
