# ...
@workflow.defn(name="YourWorkflow")
class YourWorkflow:
    @workflow.run
    async def run(self, name: str) -> str:
        return await workflow.execute_activity(
            your_activity,
            YourParams("Hello", name),
            start_to_close_timeout=timedelta(seconds=10),
        )
```

## Run a Worker Process {#run-a-dev-worker}

**How to run a Worker Process using the Temporal Python SDK.**

The [Worker Process](/workers#worker-process) is where Workflow Functions and Activity Functions are executed.

- Each [Worker Entity](/workers#worker-entity) in the Worker Process must register the exact Workflow Types and Activity
  Types it may execute.
- Each Worker Entity must also associate itself with exactly one [Task Queue](/task-queue).
- Each Worker Entity polling the same Task Queue must be registered with the same Workflow Types and Activity Types.

A [Worker Entity](/workers#worker-entity) is the component within a Worker Process that listens to a specific Task
Queue.

Although multiple Worker Entities can be in a single Worker Process, a single Worker Entity Worker Process may be
perfectly sufficient. For more information, see the [Worker tuning guide](/develop/worker-performance).

A Worker Entity contains a Workflow Worker and/or an Activity Worker, which makes progress on Workflow Executions and
Activity Executions, respectively.

To develop a Worker, use the `Worker()` constructor and add your Client, Task Queue, Workflows, and Activities as
arguments. The following code example creates a Worker that polls for tasks from the Task Queue and executes the
Workflow. When a Worker is created, it accepts a list of Workflows in the workflows parameter, a list of Activities in
the activities parameter, or both.

  
    View the source code
  {' '}
  in the context of the rest of the application code.

```python
from temporalio.client import Client
from temporalio.worker import Worker