S3

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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) yaml version: 0.1.1 default: AWS_ACCESS_KEY_ID: ... AWS_SECRET_ACCESS_KEY: ...

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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.data_preparation.repo_manager import get_repo_path
   from mage_ai.io.config import ConfigFileLoader
   from mage_ai.io.s3 import S3
   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_s3_bucket(**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
   
       return S3.with_config(ConfigFileLoader(config_path, config_profile)).load(
           bucket_name,
           object_key,
       )
   

5. Run the block.

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Errors

S3 connection endpoint URL error

Open the io_config.yaml file at the root of your project (e.g. default_repo/io_config.yaml).

Change the value for the AWS_REGION key to the region of your S3 bucket (e.g. us-west-2).