add nomissingaudits rule

docs/guides/linter.md

@@ -1,5 +1,7 @@
 # Linter guide
 
+![Linter](linter_example.png)
+
 Linting is a powerful tool for improving code quality and consistency. It enables you to automatically validate model definition, ensuring they adhere to your team's best practices.
 
 When a SQLMesh command is executed and the project is loaded, each model's code is checked for compliance with a set of rules you choose.
@@ -68,10 +70,10 @@ Here are all of SQLMesh's built-in linting rules:
 
 | Name                       | Check type  | Explanation                                                                                                              |
 | -------------------------- | ----------- | ------------------------------------------------------------------------------------------------------------------------ |
-| ambiguousorinvalidcolumn  | Correctness | SQLMesh found duplicate columns or was unable to determine whether a column is duplicated or not                         |
-| invalidselectstarexpansion | Correctness | The query's top-level selection may be `SELECT *`, but only if SQLMesh can expand the `SELECT *` into individual columns |
-| noselectstar               | Stylistic   | The query's top-level selection may not be `SELECT *`, even if SQLMesh can expand the `SELECT *` into individual columns |
-
+| `ambiguousorinvalidcolumn`  | Correctness | SQLMesh found duplicate columns or was unable to determine whether a column is duplicated or not                         |
+| `invalidselectstarexpansion` | Correctness | The query's top-level selection may be `SELECT *`, but only if SQLMesh can expand the `SELECT *` into individual columns |
+| `noselectstar`               | Stylistic   | The query's top-level selection may not be `SELECT *`, even if SQLMesh can expand the `SELECT *` into individual columns |
+| `nomissingaudits`             | Governance  | SQLMesh did not find any `audits` in the model's configuration to test data quality.                                                 |
 
 ### User-defined rules
 
@@ -211,7 +213,7 @@ MODEL(
 
 Linting rule violations raise an error by default, preventing the project from running until the violation is addressed.
 
-You may specify that a rule's violation should not error and only log a warning by specifying it in the `warning_rules` key instead of the `rules` key.
+You may specify that a rule's violation should not error and only log a warning by specifying it in the `warn_rules` key instead of the `rules` key.
 
 === "YAML"
 
@@ -221,7 +223,7 @@ You may specify that a rule's violation should not error and only log a warning
       # error if `ambiguousorinvalidcolumn` rule violated
       rules: ["ambiguousorinvalidcolumn"]
       # but only warn if "invalidselectstarexpansion" is violated
-      warning_rules: ["invalidselectstarexpansion"]
+      warn_rules: ["invalidselectstarexpansion"]
     ```
 
 === "Python"
@@ -235,9 +237,9 @@ You may specify that a rule's violation should not error and only log a warning
             # error if `ambiguousorinvalidcolumn` rule violated
             rules=["ambiguousorinvalidcolumn"],
             # but only warn if "invalidselectstarexpansion" is violated
-            warning_rules=["invalidselectstarexpansion"],
+            warn_rules=["invalidselectstarexpansion"],
         )
     )
     ```
 
-SQLMesh will raise an error if the same rule is included in more than one of the `rules`, `warning_rules`, and `ignored_rules` keys since they should be mutually exclusive.
+SQLMesh will raise an error if the same rule is included in more than one of the `rules`, `warn_rules`, and `ignored_rules` keys since they should be mutually exclusive.

sqlmesh/core/linter/rules/builtin.py

@@ -48,4 +48,11 @@ def check_model(self, model: Model) -> t.Optional[RuleViolation]:
         return self.violation(violation_msg)
 
 
+class NoMissingAudits(Rule):
+    """Model `audits` must be configured to test data quality."""
+
+    def check_model(self, model: Model) -> t.Optional[RuleViolation]:
+        return self.violation() if not model.audits else None
+
+
 BUILTIN_RULES = RuleSet(subclasses(__name__, Rule, (Rule,)))

tests/core/test_context.py

@@ -1676,7 +1676,9 @@ def assert_cached_violations_exist(cache: OptimizedQueryCache, model: Model):
     # Case: Ensure NoSelectStar only raises for top-level SELECTs, new model shouldn't raise
     # and thus should also be cached
     model2 = load_sql_based_model(
-        d.parse("MODEL (name test2); SELECT col FROM (SELECT * FROM tbl)")
+        d.parse(
+            "MODEL (name test2, audits (at_least_one(column := col))); SELECT col FROM (SELECT * FROM tbl)"
+        )
     )
     ctx.upsert_model(model2)
 
@@ -1739,7 +1741,7 @@ def assert_cached_violations_exist(cache: OptimizedQueryCache, model: Model):
     create_temp_file(
         tmp_path,
         pathlib.Path(pathlib.Path("models"), "test2.sql"),
-        "MODEL(name test2, ignored_rules ['noselectstar']); SELECT * FROM (SELECT 1 AS col);",
+        "MODEL(name test2, audits (at_least_one(column := col)), ignored_rules ['noselectstar']); SELECT * FROM (SELECT 1 AS col);",
     )
 
     ctx.load()
@@ -1777,7 +1779,12 @@ def model4_entrypoint(context, **kwargs):
         with pytest.raises(LinterError, match=config_err):
             sushi_context.upsert_model(python_model)
 
-    @model(name="memory.sushi.model5", columns={"col": "int"}, owner="test")
+    @model(
+        name="memory.sushi.model5",
+        columns={"col": "int"},
+        owner="test",
+        audits=[("at_least_one", {"column": "col"})],
+    )
     def model5_entrypoint(context, **kwargs):
         yield pd.DataFrame({"col": []})
 

tests/core/test_model.py

@@ -307,6 +307,32 @@ def test_model_qualification(tmp_path: Path):
         )
 
 
+@use_terminal_console
+def test_model_missing_audits(tmp_path: Path):
+    with patch.object(get_console(), "log_warning") as mock_logger:
+        expressions = d.parse(
+            """
+            MODEL (
+                name db.table,
+                kind FULL,
+            );
+
+            SELECT a
+            """
+        )
+
+        ctx = Context(
+            config=Config(linter=LinterConfig(enabled=True, warn_rules=["nomissingaudits"])),
+            paths=tmp_path,
+        )
+        ctx.upsert_model(load_sql_based_model(expressions))
+
+        assert (
+            """Model `audits` must be configured to test data quality."""
+            in mock_logger.call_args[0][0]
+        )
+
+
 @pytest.mark.parametrize(
     "partition_by_input, partition_by_output, output_dialect, expected_exception",
     [