Google Cloud Storage

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Add credentials

1. Create a new pipeline or open an existing pipeline.
2. Expand the left side of your screen to view the file browser.
3. Scroll down and click on a file named io_config.yaml.
4. Enter the following keys and values under the key named default (you can have multiple profiles, add it under whichever is relevant to you)

version: 0.1.1
default:
  # Option 1: Path to service account JSON file
  GOOGLE_SERVICE_ACC_KEY_FILEPATH: /path/to/service_account_credentials.json

  # Option 2: Inline credentials (e.g. from env or secrets)
  # GOOGLE_SERVICE_ACC_KEY: "{{ json_value(env_var('GCP_CREDENTIALS_JSON'), 'private_key') }}"
  # Or use mage_secret_var / aws_secret_var etc. for the full credentials object

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Using Python block

1. Create a new pipeline or open an existing pipeline.
2. Add a data loader or transformer block (the code snippet below is for a data loader).
3. Select Generic (no template).
4. Enter this code snippet (note: change the config_profile from default if you have a different profile):
   from mage_ai.settings.repo import get_repo_path
   from mage_ai.io.config import ConfigFileLoader
   from mage_ai.io.google_cloud_storage import GoogleCloudStorage
   from os import path
   from pandas import DataFrame
   
   if 'data_loader' not in globals():
       from mage_ai.data_preparation.decorators import data_loader
   
   
   @data_loader
   def load_from_gcs(**kwargs) -> DataFrame:
       config_path = path.join(get_repo_path(), 'io_config.yaml')
       config_profile = 'default'
   
       bucket_name = '...'  # Change to your bucket name
       object_key = '...'   # Change to your object key (e.g. path/to/file.parquet)
   
       return GoogleCloudStorage.with_config(
           ConfigFileLoader(config_path, config_profile)
       ).load(bucket_name, object_key)
   
5. Run the block.

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Export data to Google Cloud Storage

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.google_cloud_storage import GoogleCloudStorage
from os import path
from pandas import DataFrame

if 'data_exporter' not in globals():
    from mage_ai.data_preparation.decorators import data_exporter


@data_exporter
def export_data_to_gcs(df: DataFrame, **kwargs) -> None:
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    bucket_name = '...'
    object_key = '...'

    GoogleCloudStorage.with_config(
        ConfigFileLoader(config_path, config_profile)
    ).export(df, bucket_name, object_key)

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Supported formats

• .csv
• .json
• .parquet

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Permissions

• Storage Object Viewer – to read objects
• Storage Object Creator – to write objects
• Storage Object Admin – for full read/write/delete