# Workflow Timeouts - Python SDK

> Optimize Workflow Execution with Temporal Python SDK - Set Workflow Timeouts and Retry Policies efficiently.

## Workflow timeouts 

Each Workflow timeout controls the maximum duration of a different aspect of a Workflow Execution.

Before we continue, we want to note that we generally do not recommend setting Workflow Timeouts, because Workflows are designed to be long-running and resilient.
Instead, setting a Timeout can limit its ability to handle unexpected delays or long-running processes.
If you need to perform an action inside your Workflow after a specific period of time, we recommend using a Timer.

Workflow timeouts are set when [starting the Workflow Execution](#workflow-timeouts).

- **[Workflow Execution Timeout](/encyclopedia/detecting-workflow-failures#workflow-execution-timeout)** - restricts the maximum amount of time that a single Workflow Execution can be executed.
- **[Workflow Run Timeout](/encyclopedia/detecting-workflow-failures#workflow-run-timeout):** restricts the maximum amount of time that a single Workflow Run can last.
- **[Workflow Task Timeout](/encyclopedia/detecting-workflow-failures#workflow-task-timeout):** restricts the maximum amount of time that a Worker can execute a Workflow Task.

Set the timeout to either the [`start_workflow()`](https://python.temporal.io/temporalio.client.Client.html#start_workflow) or [`execute_workflow()`](https://python.temporal.io/temporalio.client.Client.html#execute_workflow) asynchronous methods.

Available timeouts are:

- `execution_timeout`
- `run_timeout`
- `task_timeout`

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

```python
# ...
    result = await client.execute_workflow(
        YourWorkflow.run,
        "your timeout argument",
        id="your-workflow-id",
        task_queue="your-task-queue",
        # Set Workflow Timeout duration
        execution_timeout=timedelta(seconds=2),
        # run_timeout=timedelta(seconds=2),
        # task_timeout=timedelta(seconds=2),
    )
```

## Workflow retries 

**How to set a Workflow Retry Policy using the Temporal Python SDK**

A Retry Policy can work in cooperation with the timeouts to provide fine controls to optimize the execution experience.

Use a [Retry Policy](/encyclopedia/retry-policies) to retry a Workflow Execution in the event of a failure.

Workflow Executions do not retry by default, and Retry Policies should be used with Workflow Executions only in certain situations.

Set the Retry Policy to either the [`start_workflow()`](https://python.temporal.io/temporalio.client.Client.html#start_workflow) or [`execute_workflow()`](https://python.temporal.io/temporalio.client.Client.html#execute_workflow) asynchronous methods.

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

```python
# ...
    handle = await client.execute_workflow(
        YourWorkflow.run,
        "your retry policy argument",
        id="your-workflow-id",
        task_queue="your-task-queue",
        retry_policy=RetryPolicy(maximum_interval=timedelta(seconds=2)),
    )
```