# # 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: # . # # Originally licensed under the Apache License, Version 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]], )