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# ask-ai
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Slackbot

02/18/2024, 12:21 PM
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Scout

02/18/2024, 12:21 PM
Based on the documentation, I/O managers in Dagster are responsible for handling the storage and retrieval of data for assets and op outputs. When you implement a custom I/O manager, you define the
handle_output
method to specify how and where to write data, and the
load_input
method to specify how to retrieve that data for downstream steps. In your scenario, you want the
handle_output
method to write data to a specific path (e.g.,
repo/branch_asset/asset1
) and then attempt to merge it into another path (e.g.,
repo/develop/asset1
). If the merge is successful, the next step should read from the merged path. To achieve this, you could implement custom logic within your I/O manager to handle the merge operation. After writing the data to the initial path in
handle_output
, you would perform the merge operation. If the merge is successful, you would need to ensure that the
load_input
method of the I/O manager knows to read from the new merged path (
repo/develop/asset1
) for the subsequent steps. Here's a simplified example based on the documentation's guidance on custom I/O managers:
Copy code
python
from dagster import IOManager, OutputContext, InputContext

class MyCustomIOManager(IOManager):
    def handle_output(self, context: OutputContext, obj):
        # Write to the initial path
        initial_path = f"repo/branch_asset/{context.asset_key.path}"
        write_data_to_path(initial_path, obj)
        
        # Attempt to merge into the develop path
        develop_path = f"repo/develop/{context.asset_key.path}"
        if merge_to_develop(initial_path, develop_path):
            # If merge is successful, record the develop path for later retrieval
            record_develop_path_for_retrieval(context, develop_path)

    def load_input(self, context: InputContext):
        # Retrieve the develop path recorded during handle_output
        develop_path = retrieve_develop_path_for_retrieval(context)
        return read_data_from_path(develop_path)

# Utility functions used by the IOManager
def write_data_to_path(path, data):
    # Logic to write data to the specified path
    pass

def merge_to_develop(initial_path, develop_path):
    # Logic to merge data from initial_path to develop_path
    # Return True if merge is successful, False otherwise
    pass

def record_develop_path_for_retrieval(context, develop_path):
    # Logic to record the develop path for later retrieval by load_input
    pass

def retrieve_develop_path_for_retrieval(context):
    # Logic to retrieve the develop path recorded by handle_output
    pass

def read_data_from_path(path):
    # Logic to read data from the specified path
    pass
In this example,
write_data_to_path
writes the data to the initial path,
merge_to_develop
attempts to merge the data into
the develop path,
record_develop_path_for_retrieval
records the develop path for later retrieval, and
read_data_from_path
reads the data from the develop path. Please note that the actual implementation of the merge operation and the recording/retrieval of the develop path would depend on your specific use case and storage backend. You would need to ensure that the
record_develop_path_for_retrieval
and
retrieve_develop_path_for_retrieval
functions are capable of persisting and accessing the necessary information across different steps or runs of your pipeline. Keep in mind that this is a conceptual example, and you would need to adapt it to fit your specific requirements and the details of your storage system.