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