Upstream Hypothesis plugin

This registration was previously handled by pytest-trio (before Hypothesis supported entry-point plugins).

Upstreaming it means that we'll get the behavior we want for unittest, for functions people call by hand, and so on.

pyproject.toml

@@ -62,6 +62,9 @@ Homepage = "https://github.com/python-trio/trio"
 Documentation = "https://trio.readthedocs.io/"
 Changelog = "https://trio.readthedocs.io/en/latest/history.html"
 
+[project.entry-points.hypothesis]
+trio = "trio._core._run:_hypothesis_plugin_setup"
+
 [tool.setuptools]
 # This means, just install *everything* you see under trio/, even if it
 # doesn't look like a source file, so long as it appears in MANIFEST.in:

src/trio/_core/_run.py

@@ -103,14 +103,23 @@ def _public(fn: FnT) -> FnT:
 
 
 # When running under Hypothesis, we want examples to be reproducible and
-# shrinkable.  pytest-trio's Hypothesis integration monkeypatches this
-# variable to True, and registers the Random instance _r for Hypothesis
-# to manage for each test case, which together should make Trio's task
+# shrinkable.  We therefore register `_hypothesis_plugin_setup()` as a
+# plugin, so that importing *Hypothesis* will make Trio's task
 # scheduling loop deterministic.  We have a test for that, of course.
+# Before Hypothesis supported entry-point plugins this integration was
+# handled by pytest-trio, but we want it to work in e.g. unittest too.
 _ALLOW_DETERMINISTIC_SCHEDULING: Final = False
 _r = random.Random()
 
 
+def _hypothesis_plugin_setup() -> None:
+    from hypothesis import register_random
+
+    global _ALLOW_DETERMINISTIC_SCHEDULING
+    _ALLOW_DETERMINISTIC_SCHEDULING = True  # type: ignore
+    register_random(_r)
+
+
 def _count_context_run_tb_frames() -> int:
     """Count implementation dependent traceback frames from Context.run()