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API & Datasets: Pull Configuration, Explore Data

This section covers two things: how your local api.ts gets generated, and what datasets, fields, and operations are available on the platform. Prerequisites: you are logged in, and the current App Code and environment are correct (see Configuration).

Why api pull comes first​

The dataset aliases and request wrappers used in your frontend typically come from the project's API directory (defaults to ./src/api/, configurable via apiDir). When this falls out of sync with the platform, you may see issues like "alias not found" or "list request failed." It's a good habit to pull in these scenarios:

  • Right after joining a project or running project init
  • After adding, removing, or modifying datasets or models on the platform
  • After switching appcode / env

Command:

rabetbase api pull

Specify an output directory:

rabetbase api pull --output ./src/api

After pulling, you'll have a local model list aligned with the current App. Downstream commands like codegen and dataset --alias rely on these aliases.

List all models (datasets) under the current application​

When you want a quick look in the terminal without opening files:

rabetbase api list

In multi-app mode, models are listed per App based on your configuration (output format can be changed with --format json / table).

Read-only dataset exploration​

List datasets (supports server-side filtering, no need to pull everything):

rabetbase dataset list
rabetbase dataset list --name order
rabetbase dataset list --code <32-digit-code>

View full details of a specific dataset (fields, metadata, etc.):

rabetbase dataset detail --code <32-digit-code>

If you've already run api pull, you can use an alias instead of the long code:

rabetbase dataset detail --alias order

See which operations a dataset supports (filter, getOne, create, etc.):

rabetbase dataset operations --alias order
rabetbase dataset operations --alias order --operation filter

Adding --operation shows the parameter definitions for that operation, which is useful when writing BFF scripts or generating code.

Explore relationships between tables​

Before writing cross-table queries, complex SQL, or having AI write scripts for you, understanding table relationships can save a lot of rework:

rabetbase dataset links

Filter by database:

rabetbase dataset links --db <database-name-or-ID>

The output includes fields, primary/foreign keys, and association types between datasets. Add --verbose for the raw response.

Generate API documentation (optional)​

To export API documentation for the current datasets (default directory and options are listed in rabetbase api doc --help):

rabetbase api doc
rabetbase api doc --datasetcode ds1,ds2

This is useful for sharing with teammates or keeping records. It does not affect your day-to-day development workflow.

Summary​

  • api pull: Keep your local API configuration in sync with the platform.
  • api list: Quickly scan models from the terminal.
  • dataset list / detail / operations: Explore a dataset from overview to details.
  • dataset links: View table and dataset relationships. Worth running before writing SQL or BFF scripts.

Next: To write platform-hosted custom SQL, read Custom SQL: From Authoring to Execution.