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Catalog Checks: Catalog Seeds#

Note

The below checks require both catalog.json and manifest.json to be present.

Functions:

Name Description
check_seed_columns_are_all_documented

All columns in a seed CSV file should be included in the seed's properties file, i.e. .yml file.

check_seed_columns_are_all_documented #

All columns in a seed CSV file should be included in the seed's properties file, i.e. .yml file.

Warning

This check is only supported for dbt 1.9.0 and above.

Rationale

Seed CSV files often serve as reference data (e.g. country codes, product categories) that are queried directly by downstream models. When a column exists in the CSV but not in the properties file, it is invisible to documentation tools, data catalogues, and column-level tests. This check ensures that every column in a seed is explicitly declared, making it easier for consumers to understand the seed's schema and for teams to apply descriptions and tests uniformly.

Receives at execution time:

Name Type Description
catalog_node CatalogNodeEntry

The CatalogNodeEntry object to check.
manifest_obj ManifestObject

The ManifestObject object parsed from manifest.json.
seeds list[SeedNode]

List of SeedNode objects parsed from manifest.json.

Other Parameters (passed via config file):

Name Type Description
description str | None

Description of what the check does and why it is implemented.
exclude str | None

Regex pattern to match the seed path. Seed paths that match the pattern will not be checked.
include str | None

Regex pattern to match the seed path. Only seed paths that match the pattern will be checked.
severity Literal[error, warn] | None

Severity level of the check. Default: error.

Example(s): 

catalog_checks:
    - name: check_seed_columns_are_all_documented

Source code in src/dbt_bouncer/checks/catalog/check_catalog_seeds.py 
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@check
def check_seed_columns_are_all_documented(catalog_node, ctx):
    """All columns in a seed CSV file should be included in the seed's properties file, i.e. `.yml` file.

    !!! warning

        This check is only supported for dbt 1.9.0 and above.

    !!! info "Rationale"

        Seed CSV files often serve as reference data (e.g. country codes, product categories) that are queried directly by downstream models. When a column exists in the CSV but not in the properties file, it is invisible to documentation tools, data catalogues, and column-level tests. This check ensures that every column in a seed is explicitly declared, making it easier for consumers to understand the seed's schema and for teams to apply descriptions and tests uniformly.

    Receives:
        catalog_node (CatalogNodeEntry): The CatalogNodeEntry object to check.
        manifest_obj (ManifestObject): The ManifestObject object parsed from `manifest.json`.
        seeds (list[SeedNode]): List of SeedNode objects parsed from `manifest.json`.

    Other Parameters:
        description (str | None): Description of what the check does and why it is implemented.
        exclude (str | None): Regex pattern to match the seed path. Seed paths that match the pattern will not be checked.
        include (str | None): Regex pattern to match the seed path. Only seed paths that match the pattern will be checked.
        severity (Literal["error", "warn"] | None): Severity level of the check. Default: `error`.

    Example(s):
        ```yaml
        catalog_checks:
            - name: check_seed_columns_are_all_documented
        ```

    """
    if catalog_node.unique_id is not None and catalog_node.unique_id.startswith(
        "seed."
    ):
        seed = next(s for s in ctx.seeds if s.unique_id == catalog_node.unique_id)

        seed_columns = seed.columns or {}
        undocumented_columns = [
            v.name
            for _, v in catalog_node.columns.items()
            if v.name not in seed_columns
        ]

        if undocumented_columns:
            fail(
                f"`{get_clean_model_name(seed.unique_id)}` has columns that are not included in the seed properties file: {undocumented_columns}"
            )