Add formatter for manifest.json containing scores

src/dbt_score/cli.py

@@ -1,7 +1,7 @@
 """CLI interface."""
 
 from pathlib import Path
-from typing import Final
+from typing import Final, Literal
 
 import click
 from click.core import ParameterSource
@@ -32,6 +32,14 @@ def cli() -> None:
 
 
 @cli.command()
+@click.option(
+    "--format",
+    "-f",
+    help="Output format. Plain is suitable for terminals, manifest for rich "
+    "documentation.",
+    type=click.Choice(["plain", "manifest"]),
+    default="plain",
+)
 @click.option(
     "--select",
     "-s",
@@ -68,6 +76,7 @@ def cli() -> None:
     default=False,
 )
 def lint(
+    format: Literal["plain", "manifest"],
     select: tuple[str],
     namespace: list[str],
     disabled_rule: list[str],
@@ -92,7 +101,7 @@ def lint(
     if run_dbt_parse:
         dbt_parse()
 
-    lint_dbt_project(manifest, config)
+    lint_dbt_project(manifest_path=manifest, config=config, format=format)
 
 
 @cli.command(name="list")

src/dbt_score/formatters/__init__.py

@@ -7,12 +7,16 @@
 
 if typing.TYPE_CHECKING:
     from dbt_score.evaluation import ModelResultsType
-from dbt_score.models import Model
+from dbt_score.models import ManifestLoader, Model
 
 
 class Formatter(ABC):
     """Abstract class to define a formatter."""
 
+    def __init__(self, manifest_loader: ManifestLoader):
+        """Instantiate a formatter."""
+        self._manifest_loader = manifest_loader
+
     @abstractmethod
     def model_evaluated(
         self, model: Model, results: ModelResultsType, score: float

src/dbt_score/formatters/manifest_formatter.py

@@ -0,0 +1,32 @@
+"""Formatter for a manifest.json."""
+
+
+import copy
+import json
+from typing import Any
+
+from dbt_score.evaluation import ModelResultsType
+from dbt_score.formatters import Formatter
+from dbt_score.models import Model
+
+
+class ManifestFormatter(Formatter):
+    """Formatter to generate manifest.json with score metadata."""
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        """Instantiate a manifest formatter."""
+        self._model_scores: dict[str, float] = {}
+        super().__init__(*args, **kwargs)
+
+    def model_evaluated(
+        self, model: Model, results: ModelResultsType, score: float
+    ) -> None:
+        """Callback when a model has been evaluated."""
+        self._model_scores[model.unique_id] = score
+
+    def project_evaluated(self, score: float) -> None:
+        """Callback when a project has been evaluated."""
+        manifest = copy.copy(self._manifest_loader.raw_manifest)
+        for model_id, score in self._model_scores.items():
+            manifest["nodes"][model_id]["meta"]["score"] = round(score, 1)
+        print(json.dumps(manifest, indent=2))

src/dbt_score/lint.py

@@ -1,16 +1,20 @@
 """Lint dbt models metadata."""
 
 from pathlib import Path
+from typing import Literal
 
 from dbt_score.config import Config
 from dbt_score.evaluation import Evaluation
 from dbt_score.formatters.human_readable_formatter import HumanReadableFormatter
+from dbt_score.formatters.manifest_formatter import ManifestFormatter
 from dbt_score.models import ManifestLoader
 from dbt_score.rule_registry import RuleRegistry
 from dbt_score.scoring import Scorer
 
 
-def lint_dbt_project(manifest_path: Path, config: Config) -> None:
+def lint_dbt_project(
+    manifest_path: Path, config: Config, format: Literal["plain", "manifest"]
+) -> None:
     """Lint dbt manifest."""
     if not manifest_path.exists():
         raise FileNotFoundError(f"Manifest not found at {manifest_path}.")
@@ -20,7 +24,8 @@ def lint_dbt_project(manifest_path: Path, config: Config) -> None:
 
     manifest_loader = ManifestLoader(manifest_path)
 
-    formatter = HumanReadableFormatter()
+    formatters = {"plain": HumanReadableFormatter, "manifest": ManifestFormatter}
+    formatter = formatters[format](manifest_loader=manifest_loader)
 
     scorer = Scorer()
 

tests/conftest.py

@@ -6,6 +6,7 @@
 
 from dbt_score import Model, Rule, RuleViolation, Severity, rule
 from dbt_score.config import Config
+from dbt_score.models import ManifestLoader
 from pytest import fixture
 
 # Configuration
@@ -50,6 +51,12 @@ def raw_manifest(manifest_path) -> Any:
     return json.loads(manifest_path.read_text(encoding="utf-8"))
 
 
+@fixture
+def manifest_loader(manifest_path) -> ManifestLoader:
+    """Return an instantiated and loaded manifest loader."""
+    return ManifestLoader(file_path=manifest_path)
+
+
 # Models
 
 

tests/formatters/test_human_readable_formatter.py

@@ -1,15 +1,22 @@
 """Unit tests for the human readable formatter."""
 
+from typing import Type
+
 from dbt_score.formatters.human_readable_formatter import HumanReadableFormatter
-from dbt_score.rule import RuleViolation
+from dbt_score.rule import Rule, RuleViolation
 
 
 def test_human_readable_formatter_model(
-    capsys, model1, rule_severity_low, rule_severity_medium, rule_severity_critical
+    capsys,
+    manifest_loader,
+    model1,
+    rule_severity_low,
+    rule_severity_medium,
+    rule_severity_critical,
 ):
     """Ensure the formatter has the correct output after model evaluation."""
-    formatter = HumanReadableFormatter()
-    results = {
+    formatter = HumanReadableFormatter(manifest_loader=manifest_loader)
+    results: dict[Type[Rule], RuleViolation | Exception | None] = {
         rule_severity_low: None,
         rule_severity_medium: Exception("Oh noes"),
         rule_severity_critical: RuleViolation("Error"),
@@ -28,9 +35,9 @@ def test_human_readable_formatter_model(
     )
 
 
-def test_human_readable_formatter_project(capsys):
+def test_human_readable_formatter_project(capsys, manifest_loader):
     """Ensure the formatter has the correct output after project evaluation."""
-    formatter = HumanReadableFormatter()
+    formatter = HumanReadableFormatter(manifest_loader=manifest_loader)
     formatter.project_evaluated(10.0)
     stdout = capsys.readouterr().out
     assert stdout == "Project score: \x1B[1m10.0\x1B[0m\n"

tests/formatters/test_manifest_formatter.py

@@ -0,0 +1,58 @@
+"""Unit tests for the manifest formatter."""
+
+import json
+from typing import Type
+
+from dbt_score.formatters.manifest_formatter import ManifestFormatter
+from dbt_score.rule import Rule, RuleViolation
+
+
+def test_manifest_formatter_model(
+    capsys,
+    manifest_loader,
+    model1,
+    rule_severity_low,
+    rule_severity_medium,
+    rule_severity_critical,
+):
+    """Ensure the formatter has the correct output after model evaluation."""
+    formatter = ManifestFormatter(manifest_loader=manifest_loader)
+    results = {
+        rule_severity_low: None,
+        rule_severity_medium: Exception("Oh noes"),
+        rule_severity_critical: RuleViolation("Error"),
+    }
+    formatter.model_evaluated(model1, results, 10.0)
+    stdout = capsys.readouterr().out
+    assert stdout == ""
+
+
+def test_human_readable_formatter_project(  # noqa: PLR0913
+    capsys,
+    manifest_loader,
+    model1,
+    model2,
+    rule_severity_low,
+    rule_severity_medium,
+    rule_severity_critical,
+):
+    """Ensure the formatter has the correct output after project evaluation."""
+    formatter = ManifestFormatter(manifest_loader=manifest_loader)
+    result1: dict[Type[Rule], RuleViolation | Exception | None] = {
+        rule_severity_low: None,
+        rule_severity_medium: Exception("Oh noes"),
+        rule_severity_critical: RuleViolation("Error"),
+    }
+    result2: dict[Type[Rule], RuleViolation | Exception | None] = {
+        rule_severity_low: None,
+        rule_severity_medium: None,
+        rule_severity_critical: None,
+    }
+
+    formatter.model_evaluated(model1, result1, 5.0)
+    formatter.model_evaluated(model2, result2, 10.0)
+    formatter.project_evaluated(7.5)
+    stdout = capsys.readouterr().out
+    new_manifest = json.loads(stdout)
+    assert new_manifest["nodes"]["model.package.model1"]["meta"]["score"] == 5.0
+    assert new_manifest["nodes"]["model.package.model2"]["meta"]["score"] == 10.0

tests/test_lint.py

@@ -13,6 +13,6 @@ def test_lint_dbt_project(mock_evaluation, manifest_path):
     # Instance of classes are the same Mocks
     mock_evaluation.return_value = mock_evaluation
 
-    lint_dbt_project(manifest_path, Config())
+    lint_dbt_project(manifest_path=manifest_path, config=Config(), format="plain")
 
     mock_evaluation.evaluate.assert_called_once()