---
title: prefect-gcp
---

`prefect-gcp` helps you leverage the capabilities of Google Cloud Platform (GCP) in your workflows.
For example, you can run flows on Vertex AI or Cloud Run, read and write data to BigQuery and Cloud Storage, and retrieve secrets with Secret Manager.

## Getting started

### Prerequisites

- A [GCP account](https://cloud.google.com/) and the necessary permissions to access desired services.

### Install `prefect-gcp`

Install `prefect-gcp` as an extra of `prefect`.
If you don't already have `prefect` installed, it will install the newest version of `prefect` as well.

<CodeGroup>

```bash pip
pip install -U "prefect[gcp]"
```

```bash uv
uv pip install -U "prefect[gcp]"
```

</CodeGroup>


If using BigQuery, Cloud Storage, Secret Manager, or Vertex AI, see [additional installation options](#install-extras).

#### Install extras
To install `prefect-gcp` with all additional capabilities, run the install command above and then run the following command:

<CodeGroup>

```bash pip
pip install -U "prefect-gcp[all_extras]"
```

```bash uv
uv pip install -U "prefect-gcp[all_extras]"
```

</CodeGroup>


Or, install extras individually:
<CodeGroup>

```bash pip
# Use Cloud Storage
pip install -U "prefect-gcp[cloud_storage]"

# Use BigQuery
pip install -U "prefect-gcp[bigquery]"

# Use Secret Manager
pip install -U "prefect-gcp[secret_manager]"

# Use Vertex AI
pip install -U "prefect-gcp[aiplatform]"
```

```bash uv
# Use Cloud Storage
uv pip install -U "prefect-gcp[cloud_storage]"

# Use BigQuery
uv pip install -U "prefect-gcp[bigquery]"

# Use Secret Manager
uv pip install -U "prefect-gcp[secret_manager]"

# Use Vertex AI
uv pip install -U "prefect-gcp[aiplatform]"
```

</CodeGroup>

### Register newly installed block types

Register the block types in the module to make them available for use.

```bash
prefect block register -m prefect_gcp
```
## Blocks setup

### Credentials

Authenticate with a service account to use `prefect-gcp` services.

1. Refer to the [GCP service account documentation](https://cloud.google.com/iam/docs/creating-managing-service-account-keys#creating) to create and download a service account key file.
2. Copy the JSON contents.
3. Use the Python code below, replace the placeholders with your information.

```python
from prefect_gcp import GcpCredentials

# replace this PLACEHOLDER dict with your own service account info
service_account_info = {
  "type": "service_account",
  "project_id": "PROJECT_ID",
  "private_key_id": "KEY_ID",
  "private_key": "-----BEGIN PRIVATE KEY-----\nPRIVATE_KEY\n-----END PRIVATE KEY-----\n",
  "client_email": "SERVICE_ACCOUNT_EMAIL",
  "client_id": "CLIENT_ID",
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": "https://accounts.google.com/o/oauth2/token",
  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/SERVICE_ACCOUNT_EMAIL"
}

GcpCredentials(
    service_account_info=service_account_info
).save("CREDENTIALS-BLOCK-NAME")
```
This credential block can be used to create other `prefect_gcp` blocks.

<Warning>
**`service_account_info` vs `service_account_file`**

The advantage of using `service_account_info`, instead of `service_account_file`, is that it is accessible across containers.

If `service_account_file` is used, the provided path *must be available* in the container executing the flow.
</Warning>

### BigQuery

Read data from and write to Google BigQuery within your Prefect flows.

Be sure to [install](#install-extras) `prefect-gcp` with the BigQuery extra.

```python
from prefect_gcp.bigquery import GcpCredentials, BigQueryWarehouse

gcp_credentials = GcpCredentials.load("CREDENTIALS-BLOCK-NAME")

bigquery_block = BigQueryWarehouse(
    gcp_credentials = gcp_credentials,
    fetch_size = 1  # Optional: specify a default number of rows to fetch when calling fetch_many
)
bigquery_block.save("BIGQUERY-BLOCK-NAME")
```

### Secret Manager
Manage secrets in Google Cloud Platform's Secret Manager.

```python
from prefect_gcp import GcpCredentials, GcpSecret
gcp_credentials = GcpCredentials.load("CREDENTIALS-BLOCK-NAME")

gcp_secret = GcpSecret(
    secret_name = "your-secret-name",
    secret_version = "latest",
    gcp_credentials = gcp_credentials
)

gcp_secret.save("SECRET-BLOCK-NAME")
```

### Cloud Storage
Create a block to interact with a GCS bucket.
```python
from prefect_gcp import GcpCredentials, GcsBucket

gcs_bucket = GcsBucket(
    bucket="BUCKET-NAME",
    gcp_credentials=GcpCredentials.load("BIGQUERY-BLOCK-NAME")
)
gcs_bucket.save("GCS-BLOCK-NAME")

```

## Run flows on Google Cloud Run or Vertex AI

Run flows on [Google Cloud Run](https://cloud.google.com/run) or [Vertex AI](https://cloud.google.com/vertex-ai) to dynamically scale your infrastructure.

Prefect Cloud offers [Google Cloud Run push work pools](/v3/how-to-guides/deployment_infra/serverless). Push work pools submit runs directly to Google Cloud Run, instead of requiring a worker to actively poll for flow runs to execute.

See the [Google Cloud Run Worker Guide](/integrations/prefect-gcp/gcp-worker-guide) for a walkthrough of using Google Cloud Run in a hybrid work pool.


## Examples

### Interact with BigQuery

This code creates a new dataset in BigQuery, defines a table, insert rows, and fetches data from the table:

```python
from prefect import flow
from prefect_gcp.bigquery import GcpCredentials, BigQueryWarehouse

@flow
def bigquery_flow():
    all_rows = []
    gcp_credentials = GcpCredentials.load("CREDENTIALS-BLOCK-NAME")

    client = gcp_credentials.get_bigquery_client()
    client.create_dataset("test_example", exists_ok=True)

    with BigQueryWarehouse(gcp_credentials=gcp_credentials) as warehouse:
        warehouse.execute(
            "CREATE TABLE IF NOT EXISTS test_example.customers (name STRING, address STRING);"
        )
        warehouse.execute_many(
            "INSERT INTO test_example.customers (name, address) VALUES (%(name)s, %(address)s);",
            seq_of_parameters=[
                {"name": "Marvin", "address": "Highway 42"},
                {"name": "Ford", "address": "Highway 42"},
                {"name": "Unknown", "address": "Highway 42"},
            ],
        )
        while True:
            # Repeated fetch* calls using the same operation will
            # skip re-executing and instead return the next set of results
            new_rows = warehouse.fetch_many("SELECT * FROM test_example.customers", size=2)
            if len(new_rows) == 0:
                break
            all_rows.extend(new_rows)
    return all_rows


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

### Use Prefect with Google Cloud Storage

Interact with Google Cloud Storage.

The code below uses `prefect_gcp` to upload a file to a Google Cloud Storage bucket and download the same file under a different filename.

```python
from pathlib import Path
from prefect import flow
from prefect_gcp import GcpCredentials, GcsBucket


@flow
def cloud_storage_flow():
    # create a dummy file to upload
    file_path = Path("test-example.txt")
    file_path.write_text("Hello, Prefect!")

    gcp_credentials = GcpCredentials.load("CREDENTIALS-BLOCK-NAME")
    gcs_bucket = GcsBucket(
        bucket="BUCKET-NAME",
        gcp_credentials=gcp_credentials
    )

    gcs_bucket_path = gcs_bucket.upload_from_path(file_path)
    downloaded_file_path = gcs_bucket.download_object_to_path(
        gcs_bucket_path, "downloaded-test-example.txt"
    )
    return downloaded_file_path.read_text()


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

<Info>
**Upload and download directories**

`GcsBucket` supports uploading and downloading entire directories.
</Info>

### Save secrets with Google Secret Manager

Read and write secrets with Google Secret Manager.

Be sure to [install](#instal-prefect-gcp) `prefect-gcp` with the Secret Manager extra.

The code below writes a secret to the Secret Manager, reads the secret data, and deletes the secret.

```python
from prefect import flow
from prefect_gcp import GcpCredentials, GcpSecret


@flow
def secret_manager_flow():
    gcp_credentials = GcpCredentials.load("CREDENTIALS-BLOCK-NAME")
    gcp_secret = GcpSecret(secret_name="test-example", gcp_credentials=gcp_credentials)
    gcp_secret.write_secret(secret_data=b"Hello, Prefect!")
    secret_data = gcp_secret.read_secret()
    gcp_secret.delete_secret()
    return secret_data


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


## Resources

For assistance using GCP, consult the [Google Cloud documentation](https://cloud.google.com/docs).

GCP can also authenticate without storing credentials in a block.
See [Access third-party secrets](/v3/develop/secrets) for an example that uses AWS Secrets Manager and Snowflake.

Refer to the `prefect-gcp` [SDK documentation](https://reference.prefect.io/prefect_gcp/) to explore all of the capabilities of the `prefect-gcp` library.
