dg CLI

dg check

Commands for checking the integrity of your Dagster code.

dg check [OPTIONS] COMMAND [ARGS]...

defs

Loads and validates your Dagster definitions using a Dagster instance.

If run inside a deployment directory, this command will launch all code locations in the deployment. If launched inside a code location directory, it will launch only that code location.

When running, this command sets the environment variable DAGSTER_IS_DEFS_VALIDATION_CLI=1. This environment variable can be used to control the behavior of your code in validation mode.

This command returns an exit code 1 when errors are found, otherwise an exit code 0.

dg check defs [OPTIONS]

Options:

--log-level <log_level>

Set the log level for dagster services.

Default: 'warning'Options: critical | error | warning | info | debug

--log-format <log_format>

Format of the logs for dagster services

Default: 'colored'Options: colored | json | rich

-v, --verbose: Show verbose error messages, including system frames in stack traces.

--check-yaml, --no-check-yaml: Whether to schema-check defs.yaml files for the project before loading and checking all definitions.

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

--verbose: Enable verbose output for debugging.

yaml

Check defs.yaml files against their schemas, showing validation errors.

dg check yaml [OPTIONS] [PATHS]...

Options:

--watch: Watch for changes to the component files and re-validate them.

--validate-requirements, --no-validate-requirements: Validate environment variables in requirements for all components in the given module.

--verbose: Enable verbose output for debugging.

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

Arguments:

PATHS: Optional argument(s)

dg dev

Start a local instance of Dagster.

If run inside a workspace directory, this command will launch all projects in the workspace. If launched inside a project directory, it will launch only that project.

dg dev [OPTIONS]

Options:

--code-server-log-level <code_server_log_level>

Set the log level for code servers spun up by dagster services.

Default: 'warning'Options: critical | error | warning | info | debug

--log-level <log_level>

Set the log level for dagster services.

Default: 'info'Options: critical | error | warning | info | debug

--log-format <log_format>

Format of the logs for dagster services

Default: 'colored'Options: colored | json | rich

-p, --port <port>: Port to use for the Dagster webserver.

-h, --host <host>: Host to use for the Dagster webserver.

--live-data-poll-rate <live_data_poll_rate>

Rate at which the dagster UI polls for updated asset data (in milliseconds)

Default: 2000

--check-yaml, --no-check-yaml: Whether to schema-check defs.yaml files for the project before starting the dev server.

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

--verbose: Enable verbose output for debugging.

--autoload-defs-module-name <autoload_defs_module_name>: A module to import and recursively search through for definitions.

-m, --module-name <module_name>: Specify module or modules (flag can be used multiple times) where dagster definitions reside as top-level symbols/variables and load each module as a code location in the current python environment.

-f, --python-file <python_file>: Specify python file or files (flag can be used multiple times) where dagster definitions reside as top-level symbols/variables and load each file as a code location in the current python environment.

-d, --working-directory <working_directory>: Specify working directory to use when loading the repository or job

-w, --workspace <workspace>: Path to workspace file. Argument can be provided multiple times.

--empty-workspace: Allow an empty workspace

Environment variables:

DAGSTER_autoload_defs_module_name: Provide a default for --autoload-defs-module-name

DAGSTER_MODULE_NAME: Provide a default for --module-name

DAGSTER_PYTHON_FILE: Provide a default for --python-file

DAGSTER_WORKING_DIRECTORY: Provide a default for --working-directory

dg launch

Launch a Dagster run.

dg launch [OPTIONS]

Options:

--assets <assets>: Comma-separated Asset selection to target

--job <job>: Job to target

--partition <partition>: Asset partition to target

--partition-range <partition_range>: Asset partition range to target i.e. <start>…<end>

--config-json <config_json>: JSON string of config to use for the launched run.

-c, --config <config>: Specify one or more run config files. These can also be file patterns. If more than one run config file is captured then those files are merged. Files listed first take precedence.

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

--verbose: Enable verbose output for debugging.

-a, --attribute <attribute>: Attribute that is either a 1) repository or job or 2) a function that returns a repository or job

--package-name <package_name>: Specify Python package where repository or job function lives

--autoload-defs-module-name <autoload_defs_module_name>: A module to import and recursively search through for definitions.

-m, --module-name <module_name>: Specify module where dagster definitions reside as top-level symbols/variables and load the module as a code location in the current python environment.

-f, --python-file <python_file>: Specify python file where dagster definitions reside as top-level symbols/variables and load the file as a code location in the current python environment.

-d, --working-directory <working_directory>: Specify working directory to use when loading the repository or job

Environment variables:

DAGSTER_ATTRIBUTE: Provide a default for --attribute

DAGSTER_PACKAGE_NAME: Provide a default for --package-name

DAGSTER_autoload_defs_module_name: Provide a default for --autoload-defs-module-name

DAGSTER_MODULE_NAME: Provide a default for --module-name

DAGSTER_PYTHON_FILE: Provide a default for --python-file

DAGSTER_WORKING_DIRECTORY: Provide a default for --working-directory

dg list

Commands for listing Dagster entities.

dg list [OPTIONS] COMMAND [ARGS]...

components

List all available Dagster component types in the current Python environment.

dg list components [OPTIONS]

Options:

-p, --package <package>: Filter by package name.

--json: Output as JSON instead of a table.

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

--verbose: Enable verbose output for debugging.

defs

List registered Dagster definitions in the current project environment.

dg list defs [OPTIONS]

Options:

--json: Output as JSON instead of a table.

-p, --path <path>: Path to the definitions to list.

-a, --assets <assets>: Asset selection to list.

-c, --columns <columns>: Columns to display. Either a comma-separated list of column names, or multiple invocations of the flag. Available columns: key, group, deps, kinds, description, tags, metadata, cron

--verbose: Enable verbose output for debugging.

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

envs

List environment variables from the .env file of the current project.

dg list envs [OPTIONS]

Options:

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

--verbose: Enable verbose output for debugging.

projects

List projects in the current workspace.

dg list projects [OPTIONS]

Options:

--verbose: Enable verbose output for debugging.

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

registry-modules

List dg plugins and their corresponding objects in the current Python environment.

dg list registry-modules [OPTIONS]

Options:

--json: Output as JSON instead of a table.

--target-path <target_path>: Specify a directory to use to load the context for this command. This will typically be a folder with a dg.toml or pyproject.toml file in it.

--verbose: Enable verbose output for debugging.

dg scaffold

Commands for scaffolding Dagster entities.

dg scaffold [OPTIONS] COMMAND [ARGS]...

Commands:

build-artifacts: Scaffolds a Dockerfile to build the given Dagster project or workspace.

component

Scaffold of a custom Dagster component type.

This command must be run inside a Dagster project directory. The component type scaffold

will be placed in submodule <project_name>.lib.<name>.

defs: Commands for scaffolding Dagster code.

github-actions

Scaffold a GitHub Actions workflow for a Dagster project.

This command will create a GitHub Actions workflow in the .github/workflows directory.

dg scaffold example

Note: Before scaffolding definitions with dg, you must create a project with the create-dagster CLI and activate its virtual environment.

You can use the dg scaffold defs command to scaffold a new asset underneath the defs folder. In this example, we scaffold an asset named my_asset.py and write it to the defs/assets directory:

dg scaffold defs dagster.asset assets/my_asset.py

Creating a component at /.../my-project/src/my_project/defs/assets/my_asset.py.

Once the asset has been scaffolded, we can see that a new file has been added to defs/assets, and view its contents:

tree

.
├── pyproject.toml
├── src
│ └── my_project
│     ├── __init__.py
│     └── defs
│         ├── __init__.py
│         └── assets
│             └── my_asset.py
├── tests
│ └── __init__.py
└── uv.lock

cat src/my_project/defs/assets/my_asset.py

import dagster as dg

@dg.asset
def my_asset(context: dg.AssetExecutionContext) -> dg.MaterializeResult: ...

Note: You can run dg scaffold defs from within any directory in your project and the resulting files will always be created in the <project-name>/src/<project_name>/defs/ folder.

In the above example, the scaffolded asset contains a basic commented-out definition. You can replace this definition with working code:

import dagster as dg


@dg.asset(group_name="my_group")
def my_asset(context: dg.AssetExecutionContext) -> None:
    """Asset that greets you."""
    context.log.info("hi!")

To confirm that the new asset now appears in the list of definitions, run dg list defs:

dg list defs

┏━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Section ┃ Definitions                                                     ┃
┡━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Assets  │ ┏━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓ │
│         │ ┃ Key      ┃ Group    ┃ Deps ┃ Kinds ┃ Description            ┃ │
│         │ ┡━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩ │
│         │ │ my_asset │ my_group │      │       │ Asset that greets you. │ │
│         │ └──────────┴──────────┴──────┴───────┴────────────────────────┘ │
└─────────┴─────────────────────────────────────────────────────────────────┘

dg check​

defs​

yaml​

dg dev​

dg launch​

dg list​

components​

defs​

envs​

projects​

registry-modules​

dg scaffold​

dg scaffold example​

dg check

defs

yaml

dg dev

dg launch

dg list

components

defs

envs

projects

registry-modules

dg scaffold

dg scaffold example