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name: configuration-resources description: "Use this sub-skill when implementing or debugging Dagster Pythonic config, RunConfig, ConfigurableResource, EnvVar, resource dependencies, ConfigurableIOManager, or test resource wiring." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Configuration Resources

Use this sub-skill to model Dagster runtime configuration and resource wiring with the Python APIs exported by dagster.

Route Here

• Define asset/op config classes with dagster.Config or dagster.PermissiveConfig.
• Build dagster.RunConfig for materialize, execute_in_process, schedules, sensors, or launch-time resource config.
• Implement resources with dagster.ConfigurableResource, dagster.ResourceDependency, and resource lifecycle hooks.
• Implement IO managers with dagster.ConfigurableIOManager or a configurable IO manager factory.
• Preserve secrets with dagster.EnvVar and debug EnvVar resolution.
• Wire resources in tests with Definitions, build_resources, build_init_resource_context, or direct invocation patterns.

Route Elsewhere

• Asset, op, graph, job, partition, or automation modeling belongs in the asset-definitions sub-skill when that sub-skill exists.
• Dagster instance YAML, deployment configuration, daemons, executors, or webserver operations belong in the deployment-operations sub-skill when that sub-skill exists.
• Repository maintenance, ruff, pyright, package layout, or contribution workflow belongs in the repo-development sub-skill when that sub-skill exists.

Fast Path

1. Pick the model: Config for strict structured config, PermissiveConfig for open-ended extra keys, ConfigurableResource for reusable external services, and ConfigurableIOManager for persistence behavior.
2. Keep runtime config structured: pass instances through RunConfig(ops={...}, resources={...}) instead of hand-building nested dicts when Python code owns the launch.
3. Keep secrets deferred: use EnvVar("NAME") or EnvVar.int("NAME") inside config/resource objects; use .get_value() only for explicit non-Dagster runtime reads.
4. For nested resources, declare dependencies as typed fields on the parent resource, using ResourceDependency[T] when the nested value is a plain object or function rather than a configurable resource class.
5. In tests, prefer the narrowest execution path that exercises the behavior: instantiate config directly for Pydantic validation, call resource methods for pure behavior, and use Definitions/execute_in_process when Dagster resource initialization matters.

References

• Follow references/api-reference.md for API shapes, conversion rules, and code templates.
• Follow references/workflows.md for implementation and testing workflows.
• Follow references/troubleshooting.md for common failures and fixes.
• Run scripts/check_config_resource_shape.py --help or the smoke command in the script output when you need a safe local sanity check of config/resource conversion.