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#
# This file is licensed under the Affero General Public License (AGPL) version 3.
#
# Copyright 2020 The Matrix.org Foundation C.I.C.
# Copyright (C) 2023 New Vector, Ltd
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# See the GNU Affero General Public License for more details:
# <https://www.gnu.org/licenses/agpl-3.0.html>.
#
# Originally licensed under the Apache License, Version 2.0:
# <http://www.apache.org/licenses/LICENSE-2.0>.
#
# [This file includes modifications made by New Vector Limited]
#
#
from typing import Dict, Iterable, List, Sequence
from synapse.util.iterutils import (
chunk_seq,
sorted_topologically,
sorted_topologically_batched,
)
from tests.unittest import TestCase
class ChunkSeqTests(TestCase):
def test_short_seq(self) -> None:
parts = chunk_seq("123", 8)
self.assertEqual(
list(parts),
["123"],
)
def test_long_seq(self) -> None:
parts = chunk_seq("abcdefghijklmnop", 8)
self.assertEqual(
list(parts),
["abcdefgh", "ijklmnop"],
)
def test_uneven_parts(self) -> None:
parts = chunk_seq("abcdefghijklmnop", 5)
self.assertEqual(
list(parts),
["abcde", "fghij", "klmno", "p"],
)
def test_empty_input(self) -> None:
parts: Iterable[Sequence] = chunk_seq([], 5)
self.assertEqual(
list(parts),
[],
)
class SortTopologically(TestCase):
def test_empty(self) -> None:
"Test that an empty graph works correctly"
graph: Dict[int, List[int]] = {}
self.assertEqual(list(sorted_topologically([], graph)), [])
def test_handle_empty_graph(self) -> None:
"Test that a graph where a node doesn't have an entry is treated as empty"
graph: Dict[int, List[int]] = {}
# For disconnected nodes the output is simply sorted.
self.assertEqual(list(sorted_topologically([1, 2], graph)), [1, 2])
def test_disconnected(self) -> None:
"Test that a graph with no edges work"
graph: Dict[int, List[int]] = {1: [], 2: []}
# For disconnected nodes the output is simply sorted.
self.assertEqual(list(sorted_topologically([1, 2], graph)), [1, 2])
def test_linear(self) -> None:
"Test that a simple `4 -> 3 -> 2 -> 1` graph works"
graph: Dict[int, List[int]] = {1: [], 2: [1], 3: [2], 4: [3]}
self.assertEqual(list(sorted_topologically([4, 3, 2, 1], graph)), [1, 2, 3, 4])
def test_subset(self) -> None:
"Test that only sorting a subset of the graph works"
graph: Dict[int, List[int]] = {1: [], 2: [1], 3: [2], 4: [3]}
self.assertEqual(list(sorted_topologically([4, 3], graph)), [3, 4])
def test_fork(self) -> None:
"Test that a forked graph works"
graph: Dict[int, List[int]] = {1: [], 2: [1], 3: [1], 4: [2, 3]}
# Valid orderings are `[1, 3, 2, 4]` or `[1, 2, 3, 4]`, but we should
# always get the same one.
self.assertEqual(list(sorted_topologically([4, 3, 2, 1], graph)), [1, 2, 3, 4])
def test_duplicates(self) -> None:
"Test that a graph with duplicate edges work"
graph: Dict[int, List[int]] = {1: [], 2: [1, 1], 3: [2, 2], 4: [3]}
self.assertEqual(list(sorted_topologically([4, 3, 2, 1], graph)), [1, 2, 3, 4])
def test_multiple_paths(self) -> None:
"Test that a graph with multiple paths between two nodes work"
graph: Dict[int, List[int]] = {1: [], 2: [1], 3: [2], 4: [3, 2, 1]}
self.assertEqual(list(sorted_topologically([4, 3, 2, 1], graph)), [1, 2, 3, 4])
class SortTopologicallyBatched(TestCase):
"Test cases for `sorted_topologically_batched`"
def test_empty(self) -> None:
"Test that an empty graph works correctly"
graph: Dict[int, List[int]] = {}
self.assertEqual(list(sorted_topologically_batched([], graph)), [])
def test_handle_empty_graph(self) -> None:
"Test that a graph where a node doesn't have an entry is treated as empty"
graph: Dict[int, List[int]] = {}
# For disconnected nodes the output is simply sorted.
self.assertEqual(list(sorted_topologically_batched([1, 2], graph)), [[1, 2]])
def test_disconnected(self) -> None:
"Test that a graph with no edges work"
graph: Dict[int, List[int]] = {1: [], 2: []}
# For disconnected nodes the output is simply sorted.
self.assertEqual(list(sorted_topologically_batched([1, 2], graph)), [[1, 2]])
def test_linear(self) -> None:
"Test that a simple `4 -> 3 -> 2 -> 1` graph works"
graph: Dict[int, List[int]] = {1: [], 2: [1], 3: [2], 4: [3]}
self.assertEqual(
list(sorted_topologically_batched([4, 3, 2, 1], graph)),
[[1], [2], [3], [4]],
)
def test_subset(self) -> None:
"Test that only sorting a subset of the graph works"
graph: Dict[int, List[int]] = {1: [], 2: [1], 3: [2], 4: [3]}
self.assertEqual(list(sorted_topologically_batched([4, 3], graph)), [[3], [4]])
def test_fork(self) -> None:
"Test that a forked graph works"
graph: Dict[int, List[int]] = {1: [], 2: [1], 3: [1], 4: [2, 3]}
# Valid orderings are `[1, 3, 2, 4]` or `[1, 2, 3, 4]`, but we should
# always get the same one.
self.assertEqual(
list(sorted_topologically_batched([4, 3, 2, 1], graph)), [[1], [2, 3], [4]]
)
def test_duplicates(self) -> None:
"Test that a graph with duplicate edges work"
graph: Dict[int, List[int]] = {1: [], 2: [1, 1], 3: [2, 2], 4: [3]}
self.assertEqual(
list(sorted_topologically_batched([4, 3, 2, 1], graph)),
[[1], [2], [3], [4]],
)
def test_multiple_paths(self) -> None:
"Test that a graph with multiple paths between two nodes work"
graph: Dict[int, List[int]] = {1: [], 2: [1], 3: [2], 4: [3, 2, 1]}
self.assertEqual(
list(sorted_topologically_batched([4, 3, 2, 1], graph)),
[[1], [2], [3], [4]],
)
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