





"""simple docstring"""
import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases






class    _UpperCAmelCase  (      lowercase_					):


					def       lowerCamelCase			(   self     :Optional[int]	,			__UpperCamelCase     :str	,			__UpperCamelCase     :List[Any]=False						):
												A,      A,      A						=    (
												    filename_skip_take["filename"],
												    filename_skip_take["skip"] if "skip" in filename_skip_take else None,
												    filename_skip_take["take"] if "take" in filename_skip_take else None,
												)
												open(os.path.join(__UpperCamelCase						)	,			"wb"						).close()
												A						=    pa.Table.from_pydict({"filename": [Path(__UpperCamelCase						).name] * 1_00}						)
												if take == -1:
																			A						=    len(__UpperCamelCase						) - skip
												if skip is not None and take is not None:
																			A						=    pa_table.slice(__UpperCamelCase	,			__UpperCamelCase						)
												return pa_table







class    _UpperCAmelCase  (      lowercase_					):


					def       lowerCamelCase			(   self     :Dict						):
												A						=    "my_name"
												A						=    SplitInfo(name="train"	,			num_examples=1_00						)
												A						=    SplitInfo(name="test"	,			num_examples=1_00						)
												A						=    [train_info, test_info]
												A						=    SplitDict()
												split_dict.add(__UpperCamelCase						)
												split_dict.add(__UpperCamelCase						)
												A						=    DatasetInfo(splits=__UpperCamelCase						)

												with tempfile.TemporaryDirectory() as tmp_dir:
																			A						=    ReaderTest(__UpperCamelCase	,			__UpperCamelCase						)

																			A						=    "test[:33%]"
																			A						=    Dataset(**reader.read(__UpperCamelCase	,			__UpperCamelCase	,			__UpperCamelCase						)						)
																			self.assertEqual(dset["filename"][0]	,			f"{name}-test"						)
																			self.assertEqual(dset.num_rows	,			33						)
																			self.assertEqual(dset.num_columns	,			1						)

																			A						=    ["train", "test[:33%]"]
																			A						=    [Split.TRAIN, ReadInstruction.from_spec("test[:33%]"						)]
																			for instructions in [instructionsa, instructionsa]:
																										A						=    [reader.read(__UpperCamelCase	,			__UpperCamelCase	,			__UpperCamelCase						) for instr in instructions]
																										A,      A						=    (Dataset(**__UpperCamelCase						) for dataset_kwargs in datasets_kwargs)
																										self.assertEqual(train_dset["filename"][0]	,			f"{name}-train"						)
																										self.assertEqual(train_dset.num_rows	,			1_00						)
																										self.assertEqual(train_dset.num_columns	,			1						)
																										self.assertIsInstance(train_dset.split	,			__UpperCamelCase						)
																										self.assertEqual(str(train_dset.split						)	,			"train"						)
																										self.assertEqual(test_dset["filename"][0]	,			f"{name}-test"						)
																										self.assertEqual(test_dset.num_rows	,			33						)
																										self.assertEqual(test_dset.num_columns	,			1						)
																										self.assertIsInstance(test_dset.split	,			__UpperCamelCase						)
																										self.assertEqual(str(test_dset.split						)	,			"test[:33%]"						)
																										del train_dset, test_dset


					def       lowerCamelCase			(   self     :Tuple						):
												A						=    "my_name"
												A						=    SplitInfo(name="train"	,			num_examples=10_00	,			shard_lengths=[1_00] * 10						)
												A						=    [train_info]
												A						=    SplitDict()
												split_dict.add(__UpperCamelCase						)
												A						=    DatasetInfo(splits=__UpperCamelCase						)

												with tempfile.TemporaryDirectory() as tmp_dir:
																			A						=    ReaderTest(__UpperCamelCase	,			__UpperCamelCase						)

																			A						=    "train[:33%]"
																			A						=    Dataset(**reader.read(__UpperCamelCase	,			__UpperCamelCase	,			__UpperCamelCase						)						)
																			self.assertEqual(dset["filename"][0]	,			f"{name}-train-00000-of-00010"						)
																			self.assertEqual(dset["filename"][-1]	,			f"{name}-train-00003-of-00010"						)
																			self.assertEqual(dset.num_rows	,			3_30						)
																			self.assertEqual(dset.num_columns	,			1						)


					def       lowerCamelCase			(   self     :Tuple						):
												A						=    SplitInfo(name="train"	,			num_examples=1_00						)
												A						=    SplitInfo(name="test"	,			num_examples=1_00						)
												A						=    SplitDict()
												split_dict.add(__UpperCamelCase						)
												split_dict.add(__UpperCamelCase						)
												A						=    DatasetInfo(splits=__UpperCamelCase						)

												with tempfile.TemporaryDirectory() as tmp_dir:
																			A						=    ReaderTest(__UpperCamelCase	,			__UpperCamelCase						)

																			A						=    [
																			    {"filename": os.path.join(__UpperCamelCase	,			"train"						)},
																			    {"filename": os.path.join(__UpperCamelCase	,			"test"						), "skip": 10, "take": 10},
																			]
																			A						=    Dataset(**reader.read_files(__UpperCamelCase	,			original_instructions="train+test[10:20]"						)						)
																			self.assertEqual(dset.num_rows	,			1_10						)
																			self.assertEqual(dset.num_columns	,			1						)
																			del dset







@pytest.mark.parametrize("in_memory"   ,    [False, True]			)
def    A__							(     UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase			):
							A						=    arrow_file
							with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
														A						=    ArrowReader.read_table(UpperCamelCase   ,    in_memory=UpperCamelCase			)
							assert table.shape == dataset.data.shape
							assert set(table.column_names			) == set(dataset.data.column_names			)
							assert dict(table.to_pydict()			) == dict(dataset.data.to_pydict()			)  # to_pydict returns OrderedDict






@pytest.mark.parametrize("in_memory"   ,    [False, True]			)
def    A__							(     UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase			):
							A						=    arrow_file
							A						=    ArrowReader(""   ,    UpperCamelCase			)
							with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
														A						=    reader.read_files([{"filename": filename}]   ,    in_memory=UpperCamelCase			)
							assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
							A						=    dataset_kwargs["arrow_table"]
							assert table.shape == dataset.data.shape
							assert set(table.column_names			) == set(dataset.data.column_names			)
							assert dict(table.to_pydict()			) == dict(dataset.data.to_pydict()			)  # to_pydict returns OrderedDict






def    A__							(     ):
							assert ReadInstruction("train"   ,    to=10   ,    unit="abs"			).to_spec() == "train[:10]"
							assert ReadInstruction("train"   ,    from_=-80   ,    to=10   ,    unit="%"			).to_spec() == "train[-80%:10%]"

							A						=    "train+test"
							assert ReadInstruction.from_spec(UpperCamelCase			).to_spec() == spec_train_test

							A						=    "train[2:10]"
							assert ReadInstruction.from_spec(UpperCamelCase			).to_spec() == spec_train_abs

							A						=    "train[15%:-20%]"
							assert ReadInstruction.from_spec(UpperCamelCase			).to_spec() == spec_train_pct

							A						=    "train[:10%](closest)"
							assert ReadInstruction.from_spec(UpperCamelCase			).to_spec() == "train[:10%]"

							A						=    "train[:10%](pct1_dropremainder)"
							assert ReadInstruction.from_spec(UpperCamelCase			).to_spec() == spec_train_pct_rounding

							A						=    "train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"
							assert ReadInstruction.from_spec(UpperCamelCase			).to_spec() == spec_train_test_pct_rounding






def    A__							(     ):
							A						=    "dummy"
							A						=    [SplitInfo(name="train"   ,    num_examples=100			)]
							A						=    "train[:33%]"
							A						=    "arrow"
							A						=    "prefix"

							A						=    make_file_instructions(UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase			)
							assert isinstance(UpperCamelCase   ,    UpperCamelCase			)
							assert file_instructions.num_examples == 33
							assert file_instructions.file_instructions == [
							    {"filename": os.path.join(UpperCamelCase   ,    F"{name}-train.arrow"			), "skip": 0, "take": 33}
							]

							A						=    [SplitInfo(name="train"   ,    num_examples=100   ,    shard_lengths=[10] * 10			)]
							A						=    make_file_instructions(UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase			)
							assert isinstance(UpperCamelCase   ,    UpperCamelCase			)
							assert file_instructions.num_examples == 33
							assert file_instructions.file_instructions == [
							    {"filename": os.path.join(UpperCamelCase   ,    F"{name}-train-00000-of-00010.arrow"			), "skip": 0, "take": -1},
							    {"filename": os.path.join(UpperCamelCase   ,    F"{name}-train-00001-of-00010.arrow"			), "skip": 0, "take": -1},
							    {"filename": os.path.join(UpperCamelCase   ,    F"{name}-train-00002-of-00010.arrow"			), "skip": 0, "take": -1},
							    {"filename": os.path.join(UpperCamelCase   ,    F"{name}-train-00003-of-00010.arrow"			), "skip": 0, "take": 3},
							]






@pytest.mark.parametrize("name, expected_exception"   ,    [(None, TypeError), ("", ValueError)]			)
def    A__							(     UpperCamelCase   ,    UpperCamelCase			):
							A						=    [SplitInfo(name="train"   ,    num_examples=100			)]
							A						=    "train"
							A						=    "arrow"
							A						=    "prefix_path"
							with pytest.raises(UpperCamelCase			):
														A						=    make_file_instructions(UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase			)









"""simple docstring"""
from __future__ import annotations

from queue import Queue






def    A__							(     UpperCamelCase   ,    UpperCamelCase			):
							a ^= b
							b ^= a
							a ^= b
							return a, b






def    A__							(     UpperCamelCase   ,    UpperCamelCase			):
							A						=    1
							while (1 << j) < max_node:
														for i in range(1   ,    max_node + 1			):
																					A						=    parent[j - 1][parent[j - 1][i]]
														j += 1
							return parent






def    A__							(     UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase			):
							# u must be deeper in the tree than v
							if level[u] < level[v]:
														A,      A						=    swap(UpperCamelCase   ,    UpperCamelCase			)
							# making depth of u same as depth of v
							for i in range(18   ,    -1   ,    -1			):
														if level[u] - (1 << i) >= level[v]:
																					A						=    parent[i][u]
    # at the same depth if u==v that mean lca is found
							if u == v:
														return u
							# moving both nodes upwards till lca in found
							for i in range(18   ,    -1   ,    -1			):
														if parent[i][u] not in [0, parent[i][v]]:
																					A,      A						=    parent[i][u], parent[i][v]
    # returning longest common ancestor of u,v
							return parent[0][u]






def    A__							(     UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase = 1   ,    ):
							A						=    0
							A						=    Queue(maxsize=UpperCamelCase			)
							q.put(UpperCamelCase			)
							while q.qsize() != 0:
														A						=    q.get()
														for v in graph[u]:
																					if level[v] == -1:
																												A						=    level[u] + 1
																												q.put(UpperCamelCase			)
																												A						=    u
							return level, parent






def    A__							(     ):
							A						=    13
							# initializing with 0
							A						=    [[0 for _ in range(max_node + 10			)] for _ in range(20			)]
							# initializing with -1 which means every node is unvisited
							A						=    [-1 for _ in range(max_node + 10			)]
							A						=    {
							    1: [2, 3, 4],
							    2: [5],
							    3: [6, 7],
							    4: [8],
							    5: [9, 10],
							    6: [11],
							    7: [],
							    8: [12, 13],
							    9: [],
							    10: [],
							    11: [],
							    12: [],
							    13: [],
							}
							A,      A						=    breadth_first_search(UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    UpperCamelCase   ,    1			)
							A						=    create_sparse(UpperCamelCase   ,    UpperCamelCase			)
							print("LCA of node 1 and 3 is: "   ,    lowest_common_ancestor(1   ,    3   ,    UpperCamelCase   ,    UpperCamelCase			)			)
							print("LCA of node 5 and 6 is: "   ,    lowest_common_ancestor(5   ,    6   ,    UpperCamelCase   ,    UpperCamelCase			)			)
							print("LCA of node 7 and 11 is: "   ,    lowest_common_ancestor(7   ,    11   ,    UpperCamelCase   ,    UpperCamelCase			)			)
							print("LCA of node 6 and 7 is: "   ,    lowest_common_ancestor(6   ,    7   ,    UpperCamelCase   ,    UpperCamelCase			)			)
							print("LCA of node 4 and 12 is: "   ,    lowest_common_ancestor(4   ,    12   ,    UpperCamelCase   ,    UpperCamelCase			)			)
							print("LCA of node 8 and 8 is: "   ,    lowest_common_ancestor(8   ,    8   ,    UpperCamelCase   ,    UpperCamelCase			)			)


if __name__ == "__main__":
		main()


