dandri/synapse
1
0
Fork 0
mirror of https://github.com/element-hq/synapse.git synced 2026-05-25 22:54:07 +00:00
Code Issues Packages Projects Releases Wiki Activity

Use type hinting generics in standard collections (#19046)

Browse Source 
aka PEP 585, added in Python 3.9

 - https://peps.python.org/pep-0585/
 - https://docs.astral.sh/ruff/rules/non-pep585-annotation/
This commit is contained in:
Andrew Ferrazzutti
2025-10-22 17:48:19 -04:00
committed by GitHub
parent cba3a814c6
commit fc244bb592
539 changed files with 4599 additions and 5066 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/util/test_itertools.py
+17 -17
View File
@@ -18,7 +18,7 @@
# [This file includes modifications made by New Vector Limited]
#
#
from typing import Dict, Iterable, List, Sequence
from typing import Iterable, Sequence
from synapse.util.iterutils import (
chunk_seq,
@@ -67,13 +67,13 @@ class SortTopologically(TestCase):
def test_empty(self) -> None:
"Test that an empty graph works correctly"
graph: Dict[int, List[int]] = {}
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]] = {}
graph: dict[int, list[int]] = {}
# For disconnected nodes the output is simply sorted.
self.assertEqual(list(sorted_topologically([1, 2], graph)), [1, 2])
@@ -81,7 +81,7 @@ class SortTopologically(TestCase):
def test_disconnected(self) -> None:
"Test that a graph with no edges work"
graph: Dict[int, List[int]] = {1: [], 2: []}
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])
@@ -89,19 +89,19 @@ class SortTopologically(TestCase):
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]}
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]}
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]}
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.
@@ -109,13 +109,13 @@ class SortTopologically(TestCase):
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]}
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]}
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])
@@ -126,13 +126,13 @@ class SortTopologicallyBatched(TestCase):
def test_empty(self) -> None:
"Test that an empty graph works correctly"
graph: Dict[int, List[int]] = {}
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]] = {}
graph: dict[int, list[int]] = {}
# For disconnected nodes the output is simply sorted.
self.assertEqual(list(sorted_topologically_batched([1, 2], graph)), [[1, 2]])
@@ -140,7 +140,7 @@ class SortTopologicallyBatched(TestCase):
def test_disconnected(self) -> None:
"Test that a graph with no edges work"
graph: Dict[int, List[int]] = {1: [], 2: []}
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]])
@@ -148,7 +148,7 @@ class SortTopologicallyBatched(TestCase):
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]}
graph: dict[int, list[int]] = {1: [], 2: [1], 3: [2], 4: [3]}
self.assertEqual(
list(sorted_topologically_batched([4, 3, 2, 1], graph)),
@@ -157,13 +157,13 @@ class SortTopologicallyBatched(TestCase):
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]}
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]}
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.
@@ -173,7 +173,7 @@ class SortTopologicallyBatched(TestCase):
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]}
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)),
@@ -182,7 +182,7 @@ class SortTopologicallyBatched(TestCase):
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]}
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)),