# -*- coding: utf-8 -*- """孟德尔/亲本一致性检验正式 tc 套件：TestClient 走真实 API + 落库/隔离 golden 断言。 fixture（镜像 e2e_mendelian_persist）：P1/P2 全 0/1 → T1、P3/P4 全 0/0 → T2（5 标记）。 T1 全 0/0 → rate=1.0 兼容；T2 全 1/1 → 每标记 alien → rate=0.0 → flag。 经真实 HTTP 端点 POST /api/v1/bre/genotype_call/mendelian/check/run 断言： [1] 返回 check_id / isolated=1 / cleared=0 + 计数 2/1/0/0 [2] bre_mendelian_check 批次落库（阈值/计数/data_version/input_hash） [3] 子表 2 行：T1 rate=1.0 flag=false / T2 rate=0.0 flag=true incompatible=5 [4] T2 进入隔离注册表 bre_pedigree_exclusion（source=mendelian / source_check_id） [5] 阈值 0.0 重跑 → flagged=0 / cleared=1 + 隔离行清除（可逆） [6] GET 只读预览零回归（无 check_id / 纯计算） 依赖: Redis + PG 正常（TestClient 走真实 lifespan）。运行后自动清理。 """ import os os.environ["ENVIRONMENT"] = "dev" os.environ["PYTHONUTF8"] = "1" import sys, asyncio # noqa: E402 sys.path.insert(0, r"d:\dpb\dpb\backend") import main # noqa: E402 from fastapi.testclient import TestClient # noqa: E402 from sqlalchemy import delete, select # noqa: E402 from app.core.database import create_async_engine_and_session # noqa: E402 from app.api.v1.module_system.user.model import UserModel # noqa: E402 (注册 mapper) from app.api.v1.module_bre.target.model import TargetModel # noqa: E402 from app.api.v1.module_bre.trait.model import TraitModel # noqa: E402 from app.api.v1.module_bre.germplasm.model import BreedingGermplasmModel # noqa: E402 from app.api.v1.module_bre.cross_combination.model import CrossCombinationModel # noqa: E402 from app.api.v1.module_bre.tree.model import TreeModel, TreePedigreeExclusionModel # noqa: E402 from app.api.v1.module_bre.trait_observation.model import TraitObservationModel # noqa: E402 from app.api.v1.module_bre.marker.model import MarkerModel # noqa: E402 from app.api.v1.module_bre.genotype_dataset.model import GenotypingDatasetModel # noqa: E402 from app.api.v1.module_bre.genotype_sample.model import GenotypeSampleModel # noqa: E402 from app.api.v1.module_bre.genotype_call.model import ( # noqa: E402 GenotypeCallModel, MendelianCheckModel, MendelianCheckTreeModel, ) from app.api.v1.module_bre.genotype_call.service import GENOTYPE_DATA_VERSION # noqa: E402 create_app = main.create_app TOKEN = None ok, fail = 0, 0 PREFIX = "TC_MEND" tokens: dict[str, list[int]] = { "germ": [], "tree": [], "combo": [], "target": [], "marker": [], "dataset": [], "sample": [], "call": [], "obs": [], } check_ids: list[int] = [] FIX: dict = {} def check(name, cond, detail=""): global ok, fail if cond: ok += 1 print(f" [ok] {name} {detail}") else: fail += 1 print(f" [FAIL] {name} {detail}") def login(client): global TOKEN d = {"username": "super", "password": "123456", "grant_type": "password", "login_type": "PC端"} r = client.post("/api/v1/system/auth/login", data=d) b = r.json() if r.status_code == 200 and b.get("code") == 0: TOKEN = b["data"]["access_token"] return key = client.get("/api/v1/system/auth/captcha/get").json()["data"]["key"] client.post("/api/v1/system/auth/captcha/slider/complete", json={"captcha_key": key}) d["captcha_key"] = key r = client.post("/api/v1/system/auth/login", data=d) b = r.json() assert r.status_code == 200 and b.get("code") == 0, f"LOGIN FAIL {r.status_code} {b}" TOKEN = b["data"]["access_token"] def auth(): return {"Authorization": f"Bearer {TOKEN}"} async def _build_fixture() -> None: engine, sf = create_async_engine_and_session() try: async with sf() as db: target = TargetModel(target_name=f"{PREFIX}-T", created_id=1) db.add(target) await db.flush() tokens["target"].append(target.id) trait = TraitModel(trait_code=f"tM_{PREFIX}", trait_name=f"果径{PREFIX}", data_type="numeric", unit="mm", is_core="1", direction="desc", into_ebv="1", default_h2=0.5, created_id=1) db.add(trait) await db.flush() P1 = BreedingGermplasmModel(cultivar_name=f"{PREFIX}-P1", can_be_female=True, created_id=1) P2 = BreedingGermplasmModel(cultivar_name=f"{PREFIX}-P2", can_be_male=True, created_id=1) P3 = BreedingGermplasmModel(cultivar_name=f"{PREFIX}-P3", can_be_female=True, created_id=1) P4 = BreedingGermplasmModel(cultivar_name=f"{PREFIX}-P4", can_be_male=True, created_id=1) db.add_all([P1, P2, P3, P4]) await db.flush() tokens["germ"] += [P1.id, P2.id, P3.id, P4.id] C0 = CrossCombinationModel(combination_code=f"{PREFIX}-C0", bre_target_id=target.id, female_parent_id=P1.id, male_parent_id=P2.id, design_type="full_diallel", created_id=1) C1 = CrossCombinationModel(combination_code=f"{PREFIX}-C1", bre_target_id=target.id, female_parent_id=P3.id, male_parent_id=P4.id, design_type="full_diallel", created_id=1) db.add_all([C0, C1]) await db.flush() tokens["combo"] += [C0.id, C1.id] T1 = TreeModel(combination_id=C0.id, tree_no=f"{PREFIX}-T1", status="alive", stage="evaluation", generation="F1", dam_id=P1.id, sire_id=P2.id, created_id=1) T2 = TreeModel(combination_id=C1.id, tree_no=f"{PREFIX}-T2", status="alive", stage="evaluation", generation="F1", dam_id=P3.id, sire_id=P4.id, created_id=1) db.add_all([T1, T2]) await db.flush() tokens["tree"] += [T1.id, T2.id] FIX.update({"T1": T1.id, "T2": T2.id, "P1": P1.id, "P2": P2.id, "P3": P3.id, "P4": P4.id}) o1 = TraitObservationModel(tree_id=T1.id, combination_id=C0.id, trait_id=trait.id, value_numeric=25.0, evaluate_year=2025, created_id=1) o2 = TraitObservationModel(tree_id=T2.id, combination_id=C1.id, trait_id=trait.id, value_numeric=20.0, evaluate_year=2025, created_id=1) db.add_all([o1, o2]) await db.flush() tokens["obs"] += [o1.id, o2.id] markers = [] for j in range(5): m = MarkerModel(marker_name=f"{PREFIX}-M{j + 1}", marker_type="SNP", chromosome=str(j), position=j * 100, created_id=1) db.add(m) markers.append(m) await db.flush() tokens["marker"] = [m.id for m in markers] mids = [m.id for m in markers] ds = GenotypingDatasetModel(dataset_name=f"{PREFIX}-DS", platform="SNP", purpose="MD", created_id=1) db.add(ds) await db.flush() tokens["dataset"].append(ds.id) FIX["dataset_id"] = ds.id def mk_sample(ds_id, no, source_type, source_id): s = GenotypeSampleModel(sample_name=no, dataset_id=ds_id, source_type=source_type, source_id=source_id, created_id=1) db.add(s) return s samp = [ mk_sample(ds.id, f"{PREFIX}-P1-S", "germplasm", P1.id), mk_sample(ds.id, f"{PREFIX}-P2-S", "germplasm", P2.id), mk_sample(ds.id, f"{PREFIX}-P3-S", "germplasm", P3.id), mk_sample(ds.id, f"{PREFIX}-P4-S", "germplasm", P4.id), mk_sample(ds.id, f"{PREFIX}-T1-S", "tree", T1.id), mk_sample(ds.id, f"{PREFIX}-T2-S", "tree", T2.id), ] await db.flush() tokens["sample"] = [s.id for s in samp] calls = [] gt_map = {"P1": "0/1", "P2": "0/1", "P3": "0/0", "P4": "0/0", "T1": "0/0", "T2": "1/1"} for name, s in zip(("P1", "P2", "P3", "P4", "T1", "T2"), samp): for mid in mids: calls.append(GenotypeCallModel(sample_id=s.id, marker_id=mid, allele=gt_map[name], created_id=1)) db.add_all(calls) await db.flush() tokens["call"] = [c.id for c in calls] await db.commit() finally: await engine.dispose() async def _verify_and_cleanup() -> None: engine, sf = create_async_engine_and_session() try: async with sf() as db: r = FIX["run1"] # ---- [2] 批次落库 ---- crow = await db.get(MendelianCheckModel, r["check_id"]) check("[2] bre_mendelian_check 落库（阈值/计数/data_version/input_hash）", crow is not None and float(crow.compat_threshold) == 0.98 and crow.trees_checked == 2 and crow.trees_flagged == 1 and crow.data_version == GENOTYPE_DATA_VERSION and crow.input_hash, f"v={crow.data_version if crow else None}") # ---- [3] 子表 ---- childs = (await db.execute(select(MendelianCheckTreeModel).where( MendelianCheckTreeModel.check_id == r["check_id"]))).scalars().all() child_by_tree = {int(c.tree_id): c for c in childs} check("[3] 子表 2 行：T1 rate=1.0 flag=false / T2 rate=0.0 flag=true incompatible=5", len(childs) == 2 and float(child_by_tree[FIX["T1"]].compatibility_rate) == 1.0 and not child_by_tree[FIX["T1"]].flag and float(child_by_tree[FIX["T2"]].compatibility_rate) == 0.0 and child_by_tree[FIX["T2"]].flag and child_by_tree[FIX["T2"]].status == "checked" and child_by_tree[FIX["T2"]].incompatible == 5, f"T1={child_by_tree[FIX['T1']].compatibility_rate}/{child_by_tree[FIX['T1']].flag} " f"T2={child_by_tree[FIX['T2']].compatibility_rate}/{child_by_tree[FIX['T2']].flag}") # ---- [4] 隔离注册表在 main_ 中 run1 后立即验（run2 会清除），此处只验 [5] ---- # ---- [5] 可逆：隔离行清除 ---- if FIX.get("run2"): excl2 = (await db.execute(select(TreePedigreeExclusionModel).where( TreePedigreeExclusionModel.is_deleted.is_(False), TreePedigreeExclusionModel.tree_id == FIX["T2"]))).scalars().all() check("[5] 阈值 0.0 后 T2 隔离行已清除", len(excl2) == 0, f"n={len(excl2)}") # ---- cleanup ---- if tokens["tree"]: await db.execute(delete(TreePedigreeExclusionModel).where( TreePedigreeExclusionModel.tree_id.in_(tokens["tree"]))) if check_ids: await db.execute(delete(MendelianCheckTreeModel).where( MendelianCheckTreeModel.check_id.in_(check_ids))) await db.execute(delete(MendelianCheckModel).where( MendelianCheckModel.id.in_(check_ids))) if tokens["call"]: await db.execute(delete(GenotypeCallModel).where( GenotypeCallModel.id.in_(tokens["call"]))) if tokens["sample"]: await db.execute(delete(GenotypeSampleModel).where( GenotypeSampleModel.id.in_(tokens["sample"]))) if tokens["marker"]: await db.execute(delete(MarkerModel).where(MarkerModel.id.in_(tokens["marker"]))) if tokens["dataset"]: await db.execute(delete(GenotypingDatasetModel).where( GenotypingDatasetModel.id.in_(tokens["dataset"]))) if tokens["obs"]: await db.execute(delete(TraitObservationModel).where( TraitObservationModel.id.in_(tokens["obs"]))) if tokens["tree"]: await db.execute(delete(TreeModel).where(TreeModel.id.in_(tokens["tree"]))) if tokens["combo"]: await db.execute(delete(CrossCombinationModel).where( CrossCombinationModel.id.in_(tokens["combo"]))) if tokens["germ"]: await db.execute(delete(BreedingGermplasmModel).where( BreedingGermplasmModel.id.in_(tokens["germ"]))) await db.execute(delete(TraitModel).where(TraitModel.trait_code == f"tM_{PREFIX}")) if tokens["target"]: await db.execute(delete(TargetModel).where(TargetModel.id.in_(tokens["target"]))) await db.commit() print(f"[cleanup] 孟德尔 tc 数据已清（check={len(check_ids)}）") finally: await engine.dispose() async def _check_isolated(check_id: int) -> None: """run1 落库后立即查隔离注册表（必须在 run2 清除之前验）。""" engine, sf = create_async_engine_and_session() try: async with sf() as db: excl = (await db.execute(select(TreePedigreeExclusionModel).where( TreePedigreeExclusionModel.is_deleted.is_(False), TreePedigreeExclusionModel.tree_id == FIX["T2"]))).scalars().all() check("[4] T2 进入隔离注册表（source=mendelian / source_check_id）", len(excl) == 1 and excl[0].source_type == "mendelian" and excl[0].source_check_id == check_id, f"n={len(excl)}") finally: await engine.dispose() async def _wipe() -> None: """启动前清理本前缀残留（防上次进程被杀/建 fixture 中途失败留下的脏数据）。""" engine, sf = create_async_engine_and_session() try: async with sf() as db: ds_ids = list((await db.execute(select(GenotypingDatasetModel.id).where( GenotypingDatasetModel.dataset_name.like(f"{PREFIX}-%")))).scalars()) tree_ids = list((await db.execute(select(TreeModel.id).where( TreeModel.tree_no.like(f"{PREFIX}-%")))).scalars()) if tree_ids: await db.execute(delete(TreePedigreeExclusionModel).where( TreePedigreeExclusionModel.tree_id.in_(tree_ids))) check_ids = list((await db.execute(select(MendelianCheckModel.id).where( MendelianCheckModel.dataset_id.in_(ds_ids)))).scalars()) if check_ids: await db.execute(delete(MendelianCheckTreeModel).where( MendelianCheckTreeModel.check_id.in_(check_ids))) await db.execute(delete(MendelianCheckModel).where( MendelianCheckModel.id.in_(check_ids))) if ds_ids: sample_ids = list((await db.execute(select(GenotypeSampleModel.id).where( GenotypeSampleModel.dataset_id.in_(ds_ids)))).scalars()) if sample_ids: await db.execute(delete(GenotypeCallModel).where( GenotypeCallModel.sample_id.in_(sample_ids))) await db.execute(delete(GenotypeSampleModel).where( GenotypeSampleModel.id.in_(sample_ids))) await db.execute(delete(GenotypingDatasetModel).where( GenotypingDatasetModel.id.in_(ds_ids))) if tree_ids: obs_ids = list((await db.execute(select(TraitObservationModel.id).where( TraitObservationModel.tree_id.in_(tree_ids)))).scalars()) if obs_ids: await db.execute(delete(TraitObservationModel).where( TraitObservationModel.id.in_(obs_ids))) await db.execute(delete(TreeModel).where(TreeModel.id.in_(tree_ids))) marker_ids = list((await db.execute(select(MarkerModel.id).where( MarkerModel.marker_name.like(f"{PREFIX}-%")))).scalars()) if marker_ids: await db.execute(delete(MarkerModel).where(MarkerModel.id.in_(marker_ids))) combo_ids = list((await db.execute(select(CrossCombinationModel.id).where( CrossCombinationModel.combination_code.like(f"{PREFIX}-%")))).scalars()) if combo_ids: await db.execute(delete(CrossCombinationModel).where( CrossCombinationModel.id.in_(combo_ids))) germ_ids = list((await db.execute(select(BreedingGermplasmModel.id).where( BreedingGermplasmModel.cultivar_name.like(f"{PREFIX}-%")))).scalars()) if germ_ids: await db.execute(delete(BreedingGermplasmModel).where( BreedingGermplasmModel.id.in_(germ_ids))) await db.execute(delete(TraitModel).where(TraitModel.trait_code == f"tM_{PREFIX}")) await db.execute(delete(TargetModel).where( TargetModel.target_name.like(f"{PREFIX}-%"))) await db.commit() print(f"[preclean] 孟德尔 tc 前缀残留已清（ds={len(ds_ids)} tree={len(tree_ids)}）") finally: await engine.dispose() def main_() -> None: asyncio.run(_wipe()) asyncio.run(_build_fixture()) try: with TestClient(create_app()) as client: login(client) H = auth() # ---- [1] POST run ---- r = client.post("/api/v1/bre/genotype_call/mendelian/check/run", json={"dataset_id": FIX["dataset_id"], "compat_threshold": 0.98}, headers=H) check("[HTTP] mendelian/check/run 200", r.status_code == 200, f"{r.status_code} {str(r.text)[:150]}") b = r.json() data = b.get("data") if b.get("code") == 0 else None check("[1] 返回 check_id / isolated=1 / cleared=0", data is not None and isinstance(data["check_id"], int) and data["isolated"] == 1 and data["cleared"] == 0, f"{data}") if data: FIX["run1"] = data check_ids.append(data["check_id"]) check("[1] 汇总计数 checked=2 / flagged=1 / no_parents=0 / missing=0", data["trees_checked"] == 2 and data["trees_flagged"] == 1 and data["trees_no_parents"] == 0 and data["trees_missing_parent_genotype"] == 0, f"{data['trees_checked']}/{data['trees_flagged']}") # ---- [4] 隔离注册表：run1 刚落库即验（run2 阈值 0.0 会清除）---- asyncio.run(_check_isolated(FIX["run1"]["check_id"])) # ---- [5] 阈值 0.0 重跑（可逆）---- r2 = client.post("/api/v1/bre/genotype_call/mendelian/check/run", json={"dataset_id": FIX["dataset_id"], "compat_threshold": 0.0}, headers=H) b2 = r2.json() d2 = b2.get("data") if r2.status_code == 200 and b2.get("code") == 0 else None check("[5] 阈值 0.0：flagged=0 / isolated=0 / cleared=1", d2 is not None and d2["trees_flagged"] == 0 and d2["isolated"] == 0 and d2["cleared"] == 1, f"{d2}") if d2: FIX["run2"] = d2 check_ids.append(d2["check_id"]) # ---- [6] GET 只读预览零回归 ---- g = client.get("/api/v1/bre/genotype_call/mendelian/check", params={"dataset_id": FIX["dataset_id"], "compat_threshold": 0.98}, headers=H) gb = g.json() gd = gb.get("data") if g.status_code == 200 and gb.get("code") == 0 else None check("[6] GET 只读预览原结构（无 check_id / 纯计算）", gd is not None and "check_id" not in gd and gd["trees_flagged"] == 1 and len(gd["trees"]) == 2 and gd["summary"]["incompatible_markers"] == 5, f"flagged={gd and gd['trees_flagged']}") finally: asyncio.run(_verify_and_cleanup()) print(f"\n===== 孟德尔 tc 套件：ok={ok} fail={fail} =====") if __name__ == "__main__": main_() sys.exit(1 if fail else 0)