---
Title: Use integrations

description: Prefect integrations are PyPI packages you can install to help you build and integrate your workflows with third parties.
---

## Install an integration package

Install an integration package with `pip`.

For example, to install `prefect-aws` you can:

- install the package directly:
```bash
pip install prefect-aws
```

- install the corresponding extra:
```bash
pip install 'prefect[aws]'
```

See [the `project.optional-dependencies` section of `pyproject.toml`](https://github.com/PrefectHQ/prefect/blob/main/pyproject.toml) for the full list of extras and the versions they specify.

## Register blocks from an integration

Once the package is installed, [register the blocks](/v3/develop/blocks/#registering-blocks-for-use-in-the-prefect-ui) within the integration to view them in the Prefect Cloud UI:

For example, to register the blocks available in `prefect-aws`:

```bash
prefect block register -m prefect_aws
```

To use a block's `load` method, you must have a block [saved](/v3/develop/blocks/#saving-blocks). [Learn more about blocks](/v3/develop/blocks).

## Use tasks and flows from an Integration

Integrations may contain pre-built tasks and flows that can be imported and called within your code.

For example, read a secret from AWS Secrets Manager with the `read_secret` task with the following code:

```python
from prefect import flow
from prefect_aws import AwsCredentials
from prefect_aws.secrets_manager import read_secret

@flow
def connect_to_database():
    aws_credentials = AwsCredentials.load("MY_BLOCK_NAME")
    secret_value = read_secret(
        secret_name="db_password",
        aws_credentials=aws_credentials
    )

    # Then, use secret_value to connect to a database
```

## Customize tasks and flows from an integration

To customize pre-configured tasks or flows, use `with_options`. For example, configure retries for dbt Cloud jobs:
    
```python
from prefect import flow
from prefect_dbt.cloud import DbtCloudCredentials
from prefect_dbt.cloud.jobs import trigger_dbt_cloud_job_run_and_wait_for_completion


custom_run_dbt_cloud_job = trigger_dbt_cloud_job_run_and_wait_for_completion.with_options(
    name="Run My DBT Cloud Job",
    retries=2,
    retry_delay_seconds=10
)

@flow
def run_dbt_job_flow():
    run_result = custom_run_dbt_cloud_job(
        dbt_cloud_credentials=DbtCloudCredentials.load("my-dbt-cloud-credentials"),
        job_id=1
    )


if __name__ == "__main__":  
    run_dbt_job_flow()
```
