diff --git a/tests/unit/test_model_generation.py b/tests/unit/test_model_generation.py new file mode 100644 index 00000000..f3a0e583 --- /dev/null +++ b/tests/unit/test_model_generation.py @@ -0,0 +1,94 @@ +from __future__ import annotations + +import json +import subprocess +import sys +from typing import TYPE_CHECKING + +from scripts.postprocess_generated_models import ( + REPO_ROOT, + RESOURCE_INPUT_TYPEDDICTS, + build_alias_map, + postprocess_models, + postprocess_typeddicts, +) + +if TYPE_CHECKING: + from pathlib import Path + +MINIMAL_SPEC = { + 'openapi': '3.1.0', + 'info': {'title': 'Test', 'version': '1.0.0'}, + 'paths': {}, + 'components': { + 'schemas': { + 'RunStatus': {'type': 'string', 'enum': ['READY', 'RUNNING', 'SUCCEEDED']}, + 'Run': { + 'type': 'object', + 'required': ['id', 'startedAt', 'status'], + 'properties': { + 'id': {'type': 'string'}, + 'startedAt': {'type': 'string', 'format': 'date-time'}, + 'status': {'$ref': '#/components/schemas/RunStatus'}, + }, + }, + # Post-processing fails unless every TypedDict seed is present in the generated file. Each gets its own + # field, so `reuse_model` doesn't turn them into empty subclasses of one shared class. + **{ + name: { + 'type': 'object', + 'required': [f'{name[0].lower()}{name[1:]}Id'], + 'properties': {f'{name[0].lower()}{name[1:]}Id': {'type': 'string'}}, + } + for name in RESOURCE_INPUT_TYPEDDICTS + }, + } + }, +} + + +def run_datamodel_codegen(*args: str) -> None: + # Running from the repository root makes datamodel-codegen pick up `[tool.datamodel-codegen]` from `pyproject.toml`. + subprocess.run( # noqa: S603 + [sys.executable, '-m', 'datamodel_code_generator', *args], + check=True, + cwd=REPO_ROOT, + ) + + +def test_model_generation_pipeline(tmp_path: Path) -> None: + """The `generate-models` pipeline (both codegen passes and post-processing) runs on a minimal spec.""" + # PR CI never runs `poe generate-models`, so this catches a dependency update that breaks the generator. + spec_path = tmp_path / 'openapi.json' + spec_path.write_text(json.dumps(MINIMAL_SPEC)) + models_path = tmp_path / '_models.py' + literals_path = tmp_path / '_literals.py' + typeddicts_path = tmp_path / '_typeddicts.py' + + run_datamodel_codegen('--input', str(spec_path), '--output', str(models_path), '--alias-generator', 'to_camel') + run_datamodel_codegen( + '--input', + str(spec_path), + '--output', + str(typeddicts_path), + '--output-model-type', + 'typing.TypedDict', + '--no-use-closed-typed-dict', + ) + postprocess_models(models_path, literals_path) + postprocess_typeddicts(typeddicts_path, build_alias_map(models_path.read_text())) + + models = models_path.read_text() + assert "@docs_group('Models')\nclass Run(BaseModel):" in models + assert 'alias_generator=to_camel' in models + assert 'started_at: AwareDatetime' in models + assert 'from apify_client._literals import RunStatus' in models + assert 'class RunStatus' not in models + + literals = literals_path.read_text() + assert "RunStatus = Literal[\n 'READY',\n 'RUNNING',\n 'SUCCEEDED',\n] | str" in literals + + typeddicts = typeddicts_path.read_text() + assert 'class RequestDict(TypedDict):\n request_id: str' in typeddicts + assert 'class RequestCamelDict(TypedDict):\n requestId: str' in typeddicts + assert 'class Run' not in typeddicts