Update Python SDK to 1.20.0

.github/workflows/ci.yml

@@ -15,13 +15,13 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python: ["3.10", "3.13"]
+        python: ["3.10", "3.14"]
         os: [ubuntu-latest, macos-intel, macos-arm, windows-latest]
         include:
           - os: macos-intel
-            runsOn: macos-13
+            runsOn: macos-15-intel
           - os: macos-arm
-            runsOn: macos-14
+            runsOn: macos-latest
     runs-on: ${{ matrix.runsOn || matrix.os }}
     steps:
       - uses: astral-sh/setup-uv@v5

bedrock/basic/workflows.py

@@ -10,7 +10,6 @@
 class BasicBedrockWorkflow:
     @workflow.run
     async def run(self, prompt: str) -> str:
-
         workflow.logger.info("Prompt: %s" % prompt)
 
         response = await workflow.execute_activity_method(

bedrock/entity/workflows.py

@@ -31,7 +31,6 @@ async def run(
         self,
         params: BedrockParams,
     ) -> str:
-
         if params and params.conversation_summary:
             self.conversation_history.append(
                 ("conversation_summary", params.conversation_summary)

cloud_export_to_parquet/workflows.py

@@ -7,9 +7,9 @@
 with workflow.unsafe.imports_passed_through():
     from cloud_export_to_parquet.data_trans_activities import (
         DataTransAndLandActivityInput,
+        GetObjectKeysActivityInput,
         data_trans_and_land,
         get_object_keys,
-        GetObjectKeysActivityInput,
     )
 from dataclasses import dataclass
 

custom_converter/shared.py

@@ -54,7 +54,7 @@ def __init__(self) -> None:
         # Just add ours as first before the defaults
         super().__init__(
             GreetingEncodingPayloadConverter(),
-            *DefaultPayloadConverter.default_encoding_payload_converters
+            *DefaultPayloadConverter.default_encoding_payload_converters,
         )
 
 

custom_metric/worker.py

@@ -25,7 +25,6 @@ def intercept_activity(
 
 class CustomScheduleToStartInterceptor(ActivityInboundInterceptor):
     async def execute_activity(self, input: ExecuteActivityInput):
-
         schedule_to_start = (
             activity.info().started_time
             - activity.info().current_attempt_scheduled_time

eager_wf_start/run.py

@@ -12,7 +12,6 @@
 
 
 async def main():
-
     # Note that the worker and client run in the same process and share the same client connection.
     config = ClientConfig.load_client_connect_config()
     config.setdefault("target_host", "localhost:7233")

env_config/__init__.py

@@ -1 +0,0 @@
-

gevent_async/worker.py

@@ -48,7 +48,6 @@ async def async_main():
     # running this async main. The max_workers here needs to have enough room to
     # support the max concurrent activities/workflows settings.
     with GeventExecutor(max_workers=200) as executor:
-
         # Run a worker for the workflow and activities
         async with Worker(
             client,
@@ -68,7 +67,6 @@ async def async_main():
             max_concurrent_activities=100,
             max_concurrent_workflow_tasks=100,
         ):
-
             # Wait until interrupted
             logging.info("Worker started, ctrl+c to exit")
             await interrupt_event.wait()

hello/hello_activity.py

@@ -61,7 +61,6 @@ async def main():
         # This same thread pool could be passed to multiple workers if desired.
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_activity_async.py

@@ -57,7 +57,6 @@ async def main():
         # to supply an activity executor because they run in
         # the worker's event loop.
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_activity_choice.py

@@ -95,7 +95,6 @@ async def main():
         activities=[order_apples, order_bananas, order_cherries, order_oranges],
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_activity_heartbeat.py

@@ -54,7 +54,6 @@ async def main():
         activities=[compose_greeting],
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_activity_method.py

@@ -50,7 +50,6 @@ async def main():
         workflows=[MyWorkflow],
         activities=[my_activities.do_database_thing],
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_activity_multiprocess.py

@@ -68,7 +68,6 @@ async def main():
             multiprocessing.Manager()
         ),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_activity_retry.py

@@ -58,7 +58,6 @@ async def main():
         activities=[compose_greeting],
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_async_activity_completion.py

@@ -81,7 +81,6 @@ async def main():
         workflows=[GreetingWorkflow],
         activities=[composer.compose_greeting],
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_cancellation.py

@@ -65,7 +65,6 @@ async def main():
         activities=[never_complete_activity, cleanup_activity],
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         # While the worker is running, use the client to start the workflow.
         # Note, in many production setups, the client would be in a completely
         # separate process from the worker.

hello/hello_child_workflow.py

@@ -44,7 +44,6 @@ async def main():
         task_queue="hello-child-workflow-task-queue",
         workflows=[GreetingWorkflow, ComposeGreetingWorkflow],
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_continue_as_new.py

@@ -33,7 +33,6 @@ async def main():
         task_queue="hello-continue-as-new-task-queue",
         workflows=[LoopingWorkflow],
     ):
-
         # While the worker is running, use the client to run the workflow. Note,
         # in many production setups, the client would be in a completely
         # separate process from the worker.

hello/hello_cron.py

@@ -46,7 +46,6 @@ async def main():
         activities=[compose_greeting],
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         print("Running workflow once a minute")
 
         # While the worker is running, use the client to start the workflow.

hello/hello_exception.py

@@ -52,7 +52,6 @@ async def main():
         activities=[compose_greeting],
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_local_activity.py

@@ -45,7 +45,6 @@ async def main():
         activities=[compose_greeting],
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_mtls.py

@@ -82,7 +82,6 @@ async def main():
         activities=[compose_greeting],
         activity_executor=ThreadPoolExecutor(5),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_parallel_activity.py

@@ -54,7 +54,6 @@ async def main():
         activities=[say_hello_activity],
         activity_executor=ThreadPoolExecutor(10),
     ):
-
         # While the worker is running, use the client to run the workflow and
         # print out its result. Note, in many production setups, the client
         # would be in a completely separate process from the worker.

hello/hello_query.py

@@ -39,7 +39,6 @@ async def main():
         task_queue="hello-query-task-queue",
         workflows=[GreetingWorkflow],
     ):
-
         # While the worker is running, use the client to start the workflow.
         # Note, in many production setups, the client would be in a completely
         # separate process from the worker.

hello/hello_search_attributes.py

@@ -27,7 +27,6 @@ async def main():
         task_queue="hello-search-attributes-task-queue",
         workflows=[GreetingWorkflow],
     ):
-
         # While the worker is running, use the client to start the workflow.
         # Note, in many production setups, the client would be in a completely
         # separate process from the worker.

hello/hello_signal.py

@@ -53,7 +53,6 @@ async def main():
         task_queue="hello-signal-task-queue",
         workflows=[GreetingWorkflow],
     ):
-
         # While the worker is running, use the client to start the workflow.
         # Note, in many production setups, the client would be in a completely
         # separate process from the worker.

message_passing/waiting_for_handlers/starter.py

@@ -37,7 +37,9 @@ async def _check_run(
             wait_for_stage=client.WorkflowUpdateStage.ACCEPTED,
         )
     except Exception as e:
-        print(f"    🔴 caught exception while starting update: {e}: {e.__cause__ or ''}")
+        print(
+            f"    🔴 caught exception while starting update: {e}: {e.__cause__ or ''}"
+        )
 
     if exit_type == WorkflowExitType.CANCELLATION:
         await wf_handle.cancel()

message_passing/waiting_for_handlers_and_compensation/starter.py

@@ -39,7 +39,9 @@ async def _check_run(
             wait_for_stage=client.WorkflowUpdateStage.ACCEPTED,
         )
     except Exception as e:
-        print(f"    🔴 caught exception while starting update: {e}: {e.__cause__ or ''}")
+        print(
+            f"    🔴 caught exception while starting update: {e}: {e.__cause__ or ''}"
+        )
 
     if exit_type == WorkflowExitType.CANCELLATION:
         await wf_handle.cancel()

nexus_sync_operations/handler/worker.py

@@ -22,7 +22,7 @@ async def main(client: Optional[Client] = None):
     if client is None:
         config = ClientConfig.load_client_connect_config()
         config.setdefault("target_host", "localhost:7233")
-        config.setdefault("namespace", NAMESPACE),
+        (config.setdefault("namespace", NAMESPACE),)
         client = await Client.connect(**config)
 
     # Create the nexus service handler instance, starting the long-running entity workflow that

openai_agents/agent_patterns/workflows/forcing_tool_use_workflow.py

@@ -59,9 +59,10 @@ async def run(self, tool_use_behavior: str = "default") -> str:
         config = RunConfig()
 
         if tool_use_behavior == "default":
-            behavior: Literal[
-                "run_llm_again", "stop_on_first_tool"
-            ] | ToolsToFinalOutputFunction = "run_llm_again"
+            behavior: (
+                Literal["run_llm_again", "stop_on_first_tool"]
+                | ToolsToFinalOutputFunction
+            ) = "run_llm_again"
         elif tool_use_behavior == "first_tool":
             behavior = "stop_on_first_tool"
         elif tool_use_behavior == "custom":

openai_agents/basic/workflows/agent_lifecycle_workflow.py

@@ -71,7 +71,6 @@ class FinalResult(BaseModel):
 class AgentLifecycleWorkflow:
     @workflow.run
     async def run(self, max_number: int) -> FinalResult:
-
         multiply_agent = Agent(
             name="Multiply Agent",
             instructions="Multiply the number by 2 and then return the final result.",

openai_agents/basic/workflows/dynamic_system_prompt_workflow.py

@@ -26,9 +26,9 @@ class DynamicSystemPromptWorkflow:
     @workflow.run
     async def run(self, user_message: str, style: Optional[str] = None) -> str:
         if style is None:
-            selected_style: Literal[
-                "haiku", "pirate", "robot"
-            ] = workflow.random().choice(["haiku", "pirate", "robot"])
+            selected_style: Literal["haiku", "pirate", "robot"] = (
+                workflow.random().choice(["haiku", "pirate", "robot"])
+            )
         else:
             # Validate that the provided style is one of the allowed values
             if style not in ["haiku", "pirate", "robot"]:

openai_agents/customer_service/customer_service.py

@@ -77,9 +77,9 @@ async def on_seat_booking_handoff(
 ### AGENTS
 
 
-def init_agents() -> Tuple[
-    Agent[AirlineAgentContext], Dict[str, Agent[AirlineAgentContext]]
-]:
+def init_agents() -> (
+    Tuple[Agent[AirlineAgentContext], Dict[str, Agent[AirlineAgentContext]]]
+):
     """
     Initialize the agents for the airline customer service workflow.
     :return: triage agent

pyproject.toml

@@ -6,7 +6,7 @@ authors = [{ name = "Temporal Technologies Inc", email = "sdk@temporal.io" }]
 requires-python = ">=3.10"
 readme = "README.md"
 license = "MIT"
-dependencies = ["temporalio>=1.19.0,<2"]
+dependencies = ["temporalio>=1.20.0,<2"]
 
 [project.urls]
 Homepage = "https://github.com/temporalio/samples-python"
@@ -16,8 +16,7 @@ Documentation = "https://docs.temporal.io/docs/python"
 
 [dependency-groups]
 dev = [
-    "black>=22.3.0,<23",
-    "isort>=5.10.1,<6",
+    "ruff>=0.5.0,<0.6",
     "mypy>=1.4.1,<2",
     "pytest>=7.1.2,<8",
     "pytest-asyncio>=0.18.3,<0.19",
@@ -37,7 +36,7 @@ encryption = [
     "cryptography>=38.0.1,<39",
     "aiohttp>=3.8.1,<4",
 ]
-gevent = ["gevent==25.4.2 ; python_version >= '3.8'"]
+gevent = ["gevent>=25.4.2 ; python_version >= '3.8'"]
 langchain = [
     "langchain>=0.1.7,<0.2 ; python_version >= '3.8.1' and python_version < '4.0'",
     "langchain-openai>=0.0.6,<0.0.7 ; python_version >= '3.8.1' and python_version < '4.0'",
@@ -119,8 +118,8 @@ requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [tool.poe.tasks]
-format = [{cmd = "uv run black ."}, {cmd = "uv run isort ."}]
-lint = [{cmd = "uv run black --check ."}, {cmd = "uv run isort --check-only ."}, {ref = "lint-types" }]
+format = [{cmd = "uv run ruff check --select I --fix"}, {cmd = "uv run ruff format"}]
+lint = [{cmd = "uv run ruff check --select I"}, {cmd = "uv run ruff format --check"}, {ref = "lint-types"}]
 lint-types = "uv run --all-groups mypy --check-untyped-defs --namespace-packages ."
 test = "uv run --all-groups pytest"
 
@@ -130,9 +129,8 @@ log_cli = true
 log_cli_level = "INFO"
 log_cli_format = "%(asctime)s [%(levelname)8s] %(message)s (%(filename)s:%(lineno)s)"
 
-[tool.isort]
-profile = "black"
-skip_gitignore = true
+[tool.ruff]
+target-version = "py310"
 
 [tool.mypy]
 ignore_missing_imports = true

sentry/README.md

@@ -3,6 +3,8 @@
 This sample shows how to configure [Sentry](https://sentry.io) SDK (version 2) to intercept and capture errors from the Temporal SDK
 for workflows and activities. The integration adds some useful context to the errors, such as the activity type, task queue, etc.
 
+Note: Sentry currently does not support Python 3.14, likewise this sample does not support Python 3.14.
+
 ## Further details
 
 This is a small modification of the original example Sentry integration in this repo based on SDK v1. The integration

tests/hello/hello_change_log_level_test.py

@@ -10,7 +10,6 @@
 
 
 async def test_workflow_with_log_capture(client: Client):
-
     log_stream = io.StringIO()
     handler = logging.StreamHandler(log_stream)
     handler.setLevel(logging.ERROR)