Mikael Frosthage
02/06/2024, 4:55 PMScout
02/06/2024, 4:55 PMS3PickleIOManager
. The S3PickleIOManager
assigns each op output to a unique filepath containing the run ID, step key, and output name. For assets, it assigns each asset to a single filesystem path, at <base_dir>/<asset_key>
. If the asset key has multiple components, the final component is used as the name of the file, and the preceding components as parent directories under the base_dir. Here's an example from the documentation on how to use the `S3PickleIOManager`: python from dagster import asset, Definitions from dagster_aws.s3 import S3PickleIOManager, S3Resource @asset def asset1(): # create df ... return df @asset def asset2(asset1): return asset1[:5] defs = Definitions( assets=[asset1, asset2], resources={ "io_manager": S3PickleIOManager( s3_resource=S3Resource(), s3_bucket="my-cool-bucket", s3_prefix="my-cool-prefix", ) } )
In this example, the S3PickleIOManager
is configured with a specific S3 bucket and prefix. The assets asset1
and asset2
will be stored in the specified S3 bucket with the prefix my-cool-prefix
. If you need to customize the file path further, you might consider subclassing the S3PickleIOManager
and overriding the methods responsible for generating the file paths. This approach is suggested in a discussion on GitHub where a user wanted to save files with specific metadata using the S3 IO Manager. The user was able to subclass and create a custom IO Manager that met their requirements. Keep in mind that the exact file path and name will depend on the implementation of the IO Manager and the asset key structure you define. If you need to customize the behavior beyond what is provided by default, creating a subclass and overriding the necessary methods would be the way to go.Mikael Frosthage
02/07/2024, 1:09 PMScout
02/07/2024, 1:09 PMS3PickleIOManager
does not provide a direct way to customize filenames with dynamic content such as the current date out of the box. One approach to achieve this is to create a custom IOManager that inherits from S3PickleIOManager
or another suitable base class and override the _get_path
method to incorporate the current date into the filename. Here's a conceptual example of how you might implement such a custom IOManager: python from dagster_aws.s3.io_manager import S3PickleIOManager from datetime import datetime class DailyS3PickleIOManager(S3PickleIOManager): def _get_path(self, context): # Generate the current date string date_str = datetime.now().strftime("%Y-%m-%d") # Construct the path with the current date return f"{super()._get_path(context)}/{date_str}.pkl" # Then, in your Dagster setup, you would use your custom IOManager: from dagster import resource @resource def daily_s3_pickle_io_manager(init_context): return DailyS3PickleIOManager( s3_bucket=init_context.resource_config["s3_bucket"], s3_prefix=init_context.resource_config["s3_prefix"], s3_client=init_context.resources.s3, ) # And in your pipeline definition, you would specify your custom IOManager: from dagster import pipeline @pipeline( mode_defs=[ ModeDefinition( resource_defs={ "io_manager": daily_s3_pickle_io_manager, "s3": s3_resource, } ) ] ) def my_pipeline(): # define your pipeline here
Please note that this is a conceptual example and may require adjustments to fit your specific use case. You would need to ensure that the _get_path
method constructs the S3 path according to your requirements, including the correct handling of the context to access the necessary metadata for path construction. Remember to test your custom IOManager thoroughly to ensure that it behaves as expected and that the generated file paths are correct.Mikael Frosthage
02/07/2024, 1:28 PMScout
02/07/2024, 1:28 PMpipeline
decorator is deprecated in favor of the @job
decorator in recent versions of Dagster, and I apologize for the oversight. Additionally, the S3PickleIOManager
does not have a method called _get_path
. Instead, you would need to override the methods responsible for generating the file paths. To customize the file path with a date, you would need to subclass the IOManager
and implement the logic for path generation within the handle_output
and load_input
methods. Here's a revised conceptual example using the @io_manager
decorator and the @job
decorator: python from dagster import io_manager, OutputContext, IOManager from dagster_aws.s3 import s3_resource from datetime import datetime class DailyS3IOManager(IOManager): def __init__(self, s3_bucket, s3_prefix, s3_client): self.s3_bucket = s3_bucket self.s3_prefix = s3_prefix self.s3_client = s3_client def handle_output(self, context: OutputContext, obj): # Generate the current date string date_str = datetime.now().strftime("%Y-%m-%d") # Construct the S3 key with the current date s3_key = f"{self.s3_prefix}/{context.asset_key.path[-1]}/{date_str}.pkl" # Use the S3 client to upload the object to S3 # ... def load_input(self, context): # Logic to retrieve and return the data from S3 # ... @io_manager def daily_s3_io_manager(init_context): return DailyS3IOManager( s3_bucket=init_context.resource_config["s3_bucket"], s3_prefix=init_context.resource_config["s3_prefix"], s3_client=init_context.resources.s3, ) # And in your job definition, you would specify your custom IOManager: from dagster import job @job( resource_defs={ "io_manager": daily_s3_io_manager, "s3": s3_resource, } ) def my_job(): # define your job here
In this example, DailyS3IOManager
is a custom IOManager that generates an S3 key that includes the current date when handling outputs. The handle_output
method is responsible for uploading the object to S3, and the load_input
method would contain the logic to download the object from S3. Please ensure that you implement the S3 upload and download logic within the handle_output
and load_input
methods, respectively. This example is a starting point and will need to be fleshed out with the actual logic for interacting with S3. Again, I apologize for any confusion, and thank you for pointing out the inaccuracies in the initial response.