[App] Enable running with spawn context (#15923)

examples/app_installation_commands/app.py

@@ -13,6 +13,10 @@ def run(self):
         print("lmdb successfully installed")
         print("accessing a module in a Work or Flow body works!")
 
+    @property
+    def ready(self) -> bool:
+        return True
+
 
 print(f"accessing an object in main code body works!: version={lmdb.version()}")
 

src/lightning_app/CHANGELOG.md

@@ -19,6 +19,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Added the property `ready` of the LightningFlow to inform when the `Open App` should be visible ([#15921](https://github.com/Lightning-AI/lightning/pull/15921))
 
+- Added private work attributed `_start_method` to customize how to start the works ([#15923](https://github.com/Lightning-AI/lightning/pull/15923))
+
 
 ### Changed
 

src/lightning_app/core/flow.py

@@ -763,6 +763,13 @@ def __init__(self, work):
         super().__init__()
         self.work = work
 
+    @property
+    def ready(self) -> bool:
+        ready = getattr(self.work, "ready", None)
+        if ready:
+            return ready
+        return self.work.url != ""
+
     def run(self):
         if self.work.has_succeeded:
             self.work.stop()

src/lightning_app/core/queues.py

@@ -198,7 +198,8 @@ class MultiProcessQueue(BaseQueue):
     def __init__(self, name: str, default_timeout: float):
         self.name = name
         self.default_timeout = default_timeout
-        self.queue = multiprocessing.Queue()
+        context = multiprocessing.get_context("spawn")
+        self.queue = context.Queue()
 
     def put(self, item):
         self.queue.put(item)

src/lightning_app/core/work.py

@@ -1,3 +1,4 @@
+import sys
 import time
 import warnings
 from copy import deepcopy
@@ -46,6 +47,8 @@ class LightningWork:
     )
 
     _run_executor_cls: Type[WorkRunExecutor] = WorkRunExecutor
+    # TODO: Move to spawn for all Operating System.
+    _start_method = "spawn" if sys.platform == "win32" else "fork"
 
     def __init__(
         self,

src/lightning_app/runners/backends/mp_process.py

@@ -31,7 +31,10 @@ def start(self):
             flow_to_work_delta_queue=self.app.flow_to_work_delta_queues[self.work.name],
             run_executor_cls=self.work._run_executor_cls,
         )
-        self._process = multiprocessing.Process(target=self._work_runner)
+
+        start_method = self.work._start_method
+        context = multiprocessing.get_context(start_method)
+        self._process = context.Process(target=self._work_runner)
         self._process.start()
 
     def kill(self):

tests/tests_app/core/test_queues.py

@@ -5,7 +5,6 @@
 from unittest import mock
 
 import pytest
-import redis
 import requests_mock
 
 from lightning_app import LightningFlow
@@ -23,6 +22,7 @@ def test_queue_api(queue_type, monkeypatch):
 
     This test run all the Queue implementation but we monkeypatch the Redis Queues to avoid external interaction
     """
+    import redis
 
     blpop_out = (b"entry-id", pickle.dumps("test_entry"))
 
@@ -104,12 +104,14 @@ def test_redis_queue_read_timeout(redis_mock):
 
 @pytest.mark.parametrize(
     "queue_type, queue_process_mock",
-    [(QueuingSystem.SINGLEPROCESS, queue), (QueuingSystem.MULTIPROCESS, multiprocessing)],
+    [(QueuingSystem.MULTIPROCESS, multiprocessing)],
 )
 def test_process_queue_read_timeout(queue_type, queue_process_mock, monkeypatch):
 
+    context = mock.MagicMock()
     queue_mocked = mock.MagicMock()
-    monkeypatch.setattr(queue_process_mock, "Queue", queue_mocked)
+    context.Queue = queue_mocked
+    monkeypatch.setattr(queue_process_mock, "get_context", mock.MagicMock(return_value=context))
     my_queue = queue_type.get_readiness_queue()
 
     # default timeout