Merge branch 'main' into fix/fastapi-pydantic-model

Author: elena-kolevska

.github/workflows/fossa.yaml

@@ -43,12 +43,12 @@ jobs:
         uses: actions/checkout@v4
 
       - name: "Run FOSSA Scan"
-        uses: fossas/fossa-action@v1.4.0 # Use a specific version if locking is preferred
+        uses: fossas/fossa-action@v1.7.0 # Use a specific version if locking is preferred
         with:
           api-key: ${{ env.FOSSA_API_KEY }}
 
       - name: "Run FOSSA Test"
-        uses: fossas/fossa-action@v1.4.0 # Use a specific version if locking is preferred
+        uses: fossas/fossa-action@v1.7.0 # Use a specific version if locking is preferred
         with:
           api-key: ${{ env.FOSSA_API_KEY }}
           run-tests: true

dapr/actor/runtime/_reminder_data.py

@@ -36,7 +36,7 @@ def __init__(
         reminder_name: str,
         state: Optional[bytes],
         due_time: timedelta,
-        period: timedelta,
+        period: Optional[timedelta] = None,
         ttl: Optional[timedelta] = None,
     ):
         """Creates new :class:`ActorReminderData` instance.
@@ -77,7 +77,7 @@ def due_time(self) -> timedelta:
         return self._due_time
 
     @property
-    def period(self) -> timedelta:
+    def period(self) -> Optional[timedelta]:
         """Gets period of Actor Reminder."""
         return self._period
 

dapr/actor/runtime/actor.py

@@ -112,7 +112,7 @@ async def register_reminder(
         name: str,
         state: bytes,
         due_time: timedelta,
-        period: timedelta,
+        period: Optional[timedelta] = None,
         ttl: Optional[timedelta] = None,
     ) -> None:
         """Registers actor reminder.

dapr/actor/runtime/mock_actor.py

@@ -86,7 +86,7 @@ async def register_reminder(
         name: str,
         state: bytes,
         due_time: timedelta,
-        period: timedelta,
+        period: Optional[timedelta] = None,
         ttl: Optional[timedelta] = None,
     ) -> None:
         """Adds actor reminder to self._state_manager._mock_reminders.

dapr/actor/runtime/state_manager.py

@@ -56,7 +56,7 @@ def ttl_in_seconds(self) -> Optional[int]:
         return self._ttl_in_seconds
 
     @ttl_in_seconds.setter
-    def ttl_in_seconds(self, new_ttl_in_seconds: int) -> None:
+    def ttl_in_seconds(self, new_ttl_in_seconds: Optional[int]) -> None:
         self._ttl_in_seconds = new_ttl_in_seconds
 
 

dapr/clients/grpc/_request.py

@@ -109,7 +109,7 @@ def __init__(
         super(InvokeMethodRequest, self).__init__(())
 
         self._content_type = content_type
-        self._http_verb = None
+        self._http_verb: Optional[str] = None
         self._http_querystring: Dict[str, str] = {}
 
         self.set_data(data)
@@ -127,7 +127,7 @@ def http_verb(self) -> Optional[str]:
     @http_verb.setter
     def http_verb(self, val: Optional[str]) -> None:
         """Sets HTTP method to Dapr invocation request."""
-        if val not in self.HTTP_METHODS:
+        if val is not None and val not in self.HTTP_METHODS:
             raise ValueError(f'{val} is the invalid HTTP verb.')
         self._http_verb = val
 

daprdocs/content/en/python-sdk-docs/python-actor.md

@@ -104,6 +104,8 @@ result = await mock_actor.recieve_reminder(name, state, due_time, period, _ttl)
 
 **To allow for more fine-grained control, the `_on_activate` method will not be called automatically the way it is when Dapr initializes a new Actor instance. You should call it manually as needed as part of your tests.**
 
+**A current limitation of the mock actor system is that it does not call the `_on_pre_actor_method` and `_on_post_actor_method` methods. You can always call these methods manually as part of a test.**
+
 The `__init__`, `register_timer`, `unregister_timer`, `register_reminder`, `unregister_reminder` methods are all overwritten by the MockActor class that gets applied as a mixin via `create_mock_actor`. If your actor itself overwrites these methods, those modifications will themselves be overwritten and the actor will likely not behave as you expect.
 
 *note: `__init__` is a special case where you are expected to define it as*

examples/workflow/task_chaining.py

@@ -31,7 +31,7 @@ def task_chain_workflow(ctx: wf.DaprWorkflowContext, wf_input: int):
     return [result1, result2, result3]
 
 
-@wfr.activity(name='step10')
+@wfr.activity(name='step1')
 def step1(ctx, activity_input):
     print(f'Step 1: Received input: {activity_input}.')
     # Do some work

tools/requirements.txt

@@ -1 +1,2 @@
 grpcio-tools==1.62.3
+mypy-protobuf==3.6.0