# Worker processes - Python SDK

> Shows how to run Worker processes with the Python SDK

## Run a Worker Process 

**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.

<div className="copycode-notice-container">
  <a href="https://github.com/temporalio/documentation/blob/main/sample-apps/python/your_app/run_worker_dacx.py">
    View the source code
  </a>{' '}
  in the context of the rest of the application code.
</div>

```python
from temporalio.client import Client
from temporalio.worker import Worker
# ...
# ...
async def main():
    client = await Client.connect("localhost:7233")
    worker = Worker(
        client,
        task_queue="your-task-queue",
        workflows=[YourWorkflow],
        activities=[your_activity],
    )
    await worker.run()

if __name__ == "__main__":
    asyncio.run(main())
```

### Register types 

**How to register types using the Temporal Python SDK.**

All Workers listening to the same Task Queue name must be registered to handle the exact same Workflows Types and
Activity Types.

If a Worker polls a Task for a Workflow Type or Activity Type it does not know about, it fails that Task. However, the
failure of the Task does not cause the associated Workflow Execution to fail.

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.

<div className="copycode-notice-container">
  <a href="https://github.com/temporalio/documentation/blob/main/sample-apps/python/your_app/run_worker_dacx.py">
    View the source code
  </a>{' '}
  in the context of the rest of the application code.
</div>

```python
# ...
async def main():
    client = await Client.connect("localhost:7233")
    worker = Worker(
        client,
        task_queue="your-task-queue",
        workflows=[YourWorkflow],
        activities=[your_activity],
    )
    await worker.run()

if __name__ == "__main__":
    asyncio.run(main())
```