📄️ build
The dbt build command will:
📄️ clean
dbt clean is a utility function that deletes the paths specified within the clean-targets list in the dbt_project.yml file. It helps by removing unnecessary files or directories generated during the execution of other dbt commands, ensuring a clean state for the project.
📄️ clone
The dbt clone command clones selected nodes from the specified state to the target schema(s). This command makes use of the clone materialization:
📄️ docs
Generate and serve the docs for your dbt project.
📄️ compile
The dbt compile command creates executable SQL from models, data tests, analyses, functions, and snapshots.
📄️ debug
Use dbt debug to test database connections and check system setup.
📄️ deps
dbt deps pulls the most recent version of the dependencies listed in your packages.yml from git. See Package-Management for more information.
📄️ environment
The dbt platform CLI provides the dbt environment command for environment and connection details. If you're using or , use dbt debug to inspect profile, target, and connection — or use dbtf debug if you have more than one dbt CLI and want to inspect .
📄️ init
dbt init helps get you started using !
📄️ invocation
The dbt invocation command is available in the and allows you to:
📄️ ls (list)
Read this guide on how dbt's ls (list) command can be used to list resources in your dbt project.
📄️ parse
Read this guide on how dbt's parse command can be used to parse your dbt project and write detailed timing information.
📄️ retry
dbt retry re-executes the last dbt command from the node point of failure.
📄️ rpc
Remote Procedure Call (rpc) dbt server compiles and runs queries, and provides methods that enable you to list and terminate running processes.
📄️ run
The dbt run command executes your compiled SQL models against a target database.
📄️ run-operation
Read this guide on how dbt's run-operation command can be used to invoke a macro.
📄️ seed
The dbt seed command loads static CSV files from your project’s seed-paths into your as tables. Use seeds for small, version-controlled reference datasets you want to keep alongside your project, such as country codes, region mappings, or a list of business-defined categories.
📄️ show
Use dbt show to:
📄️ snapshot
The dbt snapshot command executes the Snapshots defined in your project. Snapshots record changes to your source data over time by implementing type-2 Slowly Changing Dimensions. Run dbt snapshot on a schedule (for example, daily) to capture changes in your source tables.
📄️ source
The dbt source command provides subcommands that are useful when working with source data. This command provides one subcommand, dbt source freshness.
📄️ test
dbt test runs data tests defined on models, sources, snapshots, and seeds and unit tests defined on SQL models. It expects that you have already created those resources through the appropriate commands.
📄️ version
The --version command-line flag returns information about the currently installed version of or the . This flag is not supported when invoking dbt in other runtimes (for example, the IDE or scheduled runs).