Which IO tool would be appropriate for saving a JSON file locally or to an S3 bucket depending on whether the deployment is local, development, or production?

For saving a JSON file either locally or to an S3 bucket depending on the deployment environment (local, development, or production), you would typically use Dagster's I/O manager concept. An I/O manager in Dagster is responsible for handling the storage and retrieval of data that is produced by and consumed by ops within your pipelines. The documentation suggests using different implementations of resources depending on the environment. For instance, you could use a local filesystem I/O manager for local development and an S3 I/O manager for staging and production environments. Here's how you might approach this: 1. Local Development: Use the built-in

LocalIOManager

or define a custom I/O manager that writes to the local filesystem. You can configure this I/O manager to write to a specific directory on your local machine. 2. Staging/Production: Use Dagster's built-in

S3IOManager

or

S3PickleIOManager

for environments where you want to store assets in an S3 bucket. You would configure this I/O manager with the appropriate S3 bucket and credentials. To switch between these I/O managers based on the environment, you can use Dagster's run configuration system. You can define environment-specific run configurations that specify which I/O manager to use. For example, you might have a

local.yaml

configuration file for local development and a

production.yaml

for your production environment. Here's an example of how you might define these configurations in your

yaml

files:

yaml
# local.yaml
resources:
  io_manager:
    config:
      base_dir: "/path/to/local/directory"

# production.yaml
resources:
  io_manager:
    config:
      s3_bucket: "my-production-bucket"
      s3_prefix: "my-data/"

Then, in your Dagster code, you would reference the

io_manager

key when defining your assets or ops, and Dagster will use the appropriate I/O manager based on the run configuration that is active when you execute your pipeline. Please note that the exact implementation details and the code for setting up these I/O managers can be found in the Dagster documentation and may require some adaptation to fit your specific use case. S3PickleIOManager S3 key formatting button Dagster instance | Dagster Docs button Thank you for your feedback!