Generic

columns_have_description

All columns of a model should have a description.

Source code

@rule
def columns_have_description(model: Model) -> RuleViolation | None:
    """All columns of a model should have a description."""
    invalid_column_names = [
        column.name for column in model.columns if not column.description
    ]
    if invalid_column_names:
        max_length = 60
        message = f"Columns lack a description: {', '.join(invalid_column_names)}."
        if len(message) > max_length:
            message = f"{message[:max_length]}…"
        return RuleViolation(message=message)

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.columns_have_description"]
severity = 2

has_description

A model should have a description.

Source code

@rule
def has_description(model: Model) -> RuleViolation | None:
    """A model should have a description."""
    if not model.description:
        return RuleViolation(message="Model lacks a description.")

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.has_description"]
severity = 2

has_example_sql

The documentation of a model should have an example query.

Source code

@rule(severity=Severity.LOW)
def has_example_sql(model: Model) -> RuleViolation | None:
    """The documentation of a model should have an example query."""
    if model.language == "sql":
        if "```sql" not in (model.description or ""):
            return RuleViolation(
                "The model description does not include an example SQL query."
            )

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.has_example_sql"]
severity = 1

has_no_unused_is_incremental

Non-incremental model does not make use of is_incremental().

Source code

@rule(rule_filters={is_table()})
def has_no_unused_is_incremental(model: Model) -> RuleViolation | None:
    """Non-incremental model does not make use of is_incremental()."""
    if (
        model.config.get("materialized") != "incremental"
        and "is_incremental()" in model.raw_code
    ):
        return RuleViolation("Non-incremental model makes use of is_incremental().")

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.has_no_unused_is_incremental"]
severity = 2

has_owner

A model should have an owner.

Source code

@rule
def has_owner(model: Model) -> RuleViolation | None:
    """A model should have an owner."""
    if not model.meta.get("owner"):
        return RuleViolation(message="Model lacks an owner.")

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.has_owner"]
severity = 2

has_uniqueness_test

Model has uniqueness test for primary key.

Source code

@rule(rule_filters={is_table()})
def has_uniqueness_test(model: Model) -> RuleViolation | None:
    """Model has uniqueness test for primary key."""
    # ruff: noqa: C901 [too-complex]

    # Single-column PK
    for column in model.columns:
        for column_constraint in column.constraints:
            if column_constraint.type == "primary_key":
                for data_test in column.tests:
                    if data_test.type == "unique":
                        return None
                return RuleViolation(
                    f"No unique constraint defined on PK column {column.name}."
                )

    # Composite PK
    pk_columns: list[str] = []
    for model_constraint in model.constraints:
        if model_constraint.type == "primary_key":
            pk_columns = model_constraint.columns or []
            break

    if not pk_columns:  # No PK, no need for uniqueness test
        return None

    for data_test in model.tests:
        if data_test.type == "unique_combination_of_columns":
            if set(data_test.kwargs.get("combination_of_columns")) == set(pk_columns):  # type: ignore
                return None
    return RuleViolation(
        f"No uniqueness test defined and matching PK {','.join(pk_columns)}."
    )

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.has_uniqueness_test"]
severity = 2

seed_columns_have_description

All columns of a seed should have a description.

Source code

@rule
def seed_columns_have_description(seed: Seed) -> RuleViolation | None:
    """All columns of a seed should have a description."""
    invalid_column_names = [
        column.name for column in seed.columns if not column.description
    ]
    if invalid_column_names:
        max_length = 60
        message = f"Columns lack a description: {', '.join(invalid_column_names)}."
        if len(message) > max_length:
            message = f"{message[:max_length]}…"
        return RuleViolation(message=message)

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.seed_columns_have_description"]
severity = 2

seed_has_description

A seed should have a description.

Source code

@rule
def seed_has_description(seed: Seed) -> RuleViolation | None:
    """A seed should have a description."""
    if not seed.description:
        return RuleViolation(message="Seed lacks a description.")

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.seed_has_description"]
severity = 2

seed_has_owner

A seed should have an owner.

Source code

@rule
def seed_has_owner(seed: Seed) -> RuleViolation | None:
    """A seed should have an owner."""
    meta = seed.config.get("meta", {})
    if not meta.get("owner"):
        return RuleViolation(message="Seed lacks an owner.")

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.seed_has_owner"]
severity = 2

single_column_uniqueness_at_column_level

Single-column uniqueness test must be defined as a column test.

Source code

@rule(rule_filters={is_table()})
def single_column_uniqueness_at_column_level(model: Model) -> RuleViolation | None:
    """Single-column uniqueness test must be defined as a column test."""
    for data_test in model.tests:
        if data_test.type == "unique_combination_of_columns":
            if len(data_test.kwargs.get("combination_of_columns", [])) == 1:
                return RuleViolation(
                    "Single-column uniqueness test must be defined as a column test."
                )

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.single_column_uniqueness_at_column_level"]
severity = 2

single_pk_defined_at_column_level

Single-column PK must be defined as a column constraint.

Source code

@rule(rule_filters={is_table()})
def single_pk_defined_at_column_level(model: Model) -> RuleViolation | None:
    """Single-column PK must be defined as a column constraint."""
    for constraint in model.constraints:
        if constraint.type == "primary_key":
            if constraint.columns is not None and len(constraint.columns) == 1:
                return RuleViolation(
                    f"Single-column PK {constraint.columns[0]} must be defined as a "
                    f"column constraint."
                )

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.single_pk_defined_at_column_level"]
severity = 2

snapshot_has_strategy

A snapshot should have a strategy.

Source code

@rule
def snapshot_has_strategy(snapshot: Snapshot) -> RuleViolation | None:
    """A snapshot should have a strategy."""
    if not snapshot.config.get("strategy"):
        return RuleViolation(message="Snapshot lacks a strategy.")

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.snapshot_has_strategy"]
severity = 2

snapshot_has_unique_key

A snapshot should have a unique key.

Source code

@rule
def snapshot_has_unique_key(snapshot: Snapshot) -> RuleViolation | None:
    """A snapshot should have a unique key."""
    if not snapshot.config.get("unique_key"):
        return RuleViolation(message="Snapshot lacks a unique key.")

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.snapshot_has_unique_key"]
severity = 2

sql_has_reasonable_number_of_lines

The SQL query of a model should not be too long.

Source code

@rule
def sql_has_reasonable_number_of_lines(
    model: Model, max_lines: int = 200
) -> RuleViolation | None:
    """The SQL query of a model should not be too long."""
    count_lines = len(model.raw_code.split("\n"))
    if count_lines > max_lines:
        return RuleViolation(
            message=f"SQL query too long: {count_lines} lines (> {max_lines})."
        )

Default configuration

pyproject.toml

[tool.dbt-score.rules."dbt_score.rules.generic.sql_has_reasonable_number_of_lines"]
severity = 2
max_lines = 200