"""Workflow tuning preserves evidence boundaries and limits expensive work.""" import asyncio from datetime import UTC, datetime from types import SimpleNamespace as N from unittest.mock import AsyncMock, MagicMock import pytest def test_keyword_queries_match_independently_and_escape_literals(trading): from sqlalchemy import select from sqlalchemy.dialects.postgresql import dialect from alphapulse.models.risk import NewsSummary from alphapulse.news_risk.retrieval import terms_for, matching terms = terms_for('小鹏 交付 50%') condition, score = matching(NewsSummary, terms) query = select(NewsSummary.id).where(condition).order_by(score.desc()).compile(dialect=dialect()) assert ' OR ' in str(query) assert any('50/%' in str(v) for v in query.params.values()) assert terms_for('ignored', ['央行']) == ['央行','中国人民银行'] with pytest.raises(ValueError): terms_for(' ') def test_low_star_shortlist_rotates_domains_and_keeps_recent(trading): from alphapulse.news_risk.briefing import shortlist items = [{'id':i,'category':str(i%4),'importance_stars':2,'updated_at':f'2026-11-{i+1:02}'} for i in range(24)] chosen = shortlist(items) assert len(chosen) == 12 assert len({p['category'] for p in chosen[:4]}) == 4 assert chosen[0]['id'] == 23 def test_plan_time_is_distinct_from_occurrence(trading): from alphapulse.news_risk.contracts import PackageTimePoint point = dict(occurred_at=None,time_precision='unknown',time_text='明天',reported_at=None, description='拟发布',verification='partial',evidence_refs=[{'article_id':1,'quote':'明天'}]) value=PackageTimePoint(**point,planned_at='2026-11-03T00:00:00+08:00',planned_precision='day',period_text='2026年10月') assert value.occurred_at is None and value.planned_at.day == 3 with pytest.raises(ValueError): PackageTimePoint(**point,planned_precision='day') def test_attempted_selection_needs_no_date_range(trading): from alphapulse.api.risk import ReprocessIn assert ReprocessIn(selection='attempted',modes=['review']).start is None with pytest.raises(ValueError): ReprocessIn(modes=['review']) def test_exclusive_grouping_does_not_admit_realtime(trading,monkeypatch): from alphapulse.news_risk import scheduler,worker session=MagicMock() session.__aenter__=AsyncMock(return_value=session); session.__aexit__=AsyncMock() session.get=AsyncMock(return_value=N(enabled=True,start_at='configured')) job=N(id=7,settings={'request':{'run_mode':'history_only'}}) session.scalar=AsyncMock(side_effect=[job,1,job]) session.scalars=AsyncMock(return_value=N(all=lambda:[])) monkeypatch.setattr(scheduler,'SessionLocal',lambda:session) enqueue=AsyncMock();outlook=AsyncMock() monkeypatch.setattr(worker,'enqueue',enqueue);monkeypatch.setattr(worker,'outlook',outlook) assert asyncio.run(scheduler.candidate(set(),0)) is None enqueue.assert_not_awaited();outlook.assert_not_awaited() @pytest.mark.parametrize('snapshot_state', [None, 'processing', 'done', 'failed']) def test_exclusive_completion_waits_for_reading_and_then_pauses(trading,snapshot_state,monkeypatch): from alphapulse.news_risk.backfill import reconcile from alphapulse.models.risk import ReprocessJob job=N(id=7,state='running',settings={'request':{'run_mode':'history_only'},'configurations':{'outlook':{'rules':{}}}},failures=[]) from alphapulse.news_risk import events monkeypatch.setattr(events,'reading_inputs',AsyncMock(return_value=[])) settings=N(enabled=True) session=MagicMock() session.get=AsyncMock(side_effect=lambda model,*a,**k: job if model is ReprocessJob else settings) session.scalars=AsyncMock(return_value=N(all=lambda:[])) snapshot=None if snapshot_state is None else N(id=9,state=snapshot_state,error='Synthetic',quotes={}) session.scalar=AsyncMock(side_effect=[None,snapshot]) session.commit=AsyncMock() asyncio.run(reconcile(session,job)) if snapshot_state in (None,'processing'): assert job.state=='running' and settings.enabled else: assert job.state==('done' if snapshot_state=='done' else 'failed') assert not settings.enabled def test_expired_exclusive_preview_never_calls_paid_validation(trading,monkeypatch): from fastapi import HTTPException from alphapulse.api import risk from alphapulse.news_risk import backfill from alphapulse.core import db gate=MagicMock();gate.__aenter__=AsyncMock(return_value=gate);gate.__aexit__=AsyncMock(return_value=False) gate.scalar=AsyncMock(return_value=True);gate.commit=AsyncMock();gate.execute=AsyncMock() monkeypatch.setattr(db,'engine',N(connect=lambda:gate)) monkeypatch.setattr(risk,'default_settings',AsyncMock(return_value=N(enabled=False))) monkeypatch.setattr(backfill,'prepare_start',AsyncMock(side_effect=ValueError('预览已过期'))) validate=AsyncMock();monkeypatch.setattr(risk,'validate_enable',validate) with pytest.raises(HTTPException) as error: asyncio.run(risk.reprocess_start(risk.ReprocessStart(preview_id='a'*24,run_mode='history_only'),MagicMock())) assert error.value.status_code==409 validate.assert_not_awaited() gate.execute.assert_awaited_once() def test_ranking_only_skips_synthesis_and_synthesis_reuses_priority(trading,monkeypatch): from alphapulse.news_risk import briefing inputs=[{'id':1,'revision':2,'importance_stars':3,'result':{'summary':'Synthetic'}}] calls=[] async def complete(provider,system,payload,schema): calls.append(payload['task']) reading={'id':1,'revision':2,'priority':70,'reason':'Verified update'} if schema is briefing.Ranked: return schema(reading=[reading],notes='Synthetic'),{} trend={'summary':'Unknown','conditions':'Unknown','counter_evidence':'Unknown','watchpoints':'Unknown'} return schema(summary='Synthetic',market='Unknown',short_term=trend,medium_term=trend, references=[{**reading,'priority':99,'reason':'Changed'}]),{} monkeypatch.setattr(briefing,'complete',complete) provider=N(max_tokens=100,context_window=20000) ranked=asyncio.run(briefing.generate(provider,'rules',inputs,ranking_only=True)) assert calls==['ranking'] result=asyncio.run(briefing.generate(provider,'rules',inputs,rankings=ranked['reading'])) assert calls==['ranking','synthesis'] assert result['synthesis']['references']==ranked['reading'] def test_large_synthesis_compacts_package_notes_in_batches(trading,monkeypatch): import json from alphapulse.news_risk import briefing inputs=[{'id':i,'revision':1,'importance_stars':3,'result':{'summary':'x'*800}} for i in range(3)] rankings=[{'kind':'package','id':i,'revision':1,'priority':50,'reason':'Read'} for i in range(3)] calls=[] def fits(provider,system,payload,schema): return len(json.dumps(payload)) < 1600 async def complete(provider,system,payload,schema): calls.append(payload['task']) if schema is briefing.Notes: return schema(notes='Compacted'),{} trend={'summary':'Unknown','conditions':'Unknown','counter_evidence':'Unknown','watchpoints':'Unknown'} return schema(summary='Synthetic',market='Unknown',short_term=trend,medium_term=trend,references=[]),{} monkeypatch.setattr(briefing,'fits_context',fits);monkeypatch.setattr(briefing,'complete',complete) result=asyncio.run(briefing.generate(N(),'rules',inputs,rankings=rankings)) assert calls==['synthesis_notes']*3+['synthesis'] assert len(result['reading'])==3 @pytest.mark.parametrize('original_start', [None, datetime(2026,11,1,tzinfo=UTC)]) def test_exclusive_start_persists_dispatch_start_and_preserves_existing_boundary(trading,monkeypatch,original_start): from alphapulse.news_risk import backfill,scheduler settings=N(enabled=False,start_at=original_start) session=MagicMock() session.get=AsyncMock(return_value=settings);session.flush=AsyncMock();session.commit=AsyncMock() session.add=lambda job:setattr(job,'id',7) value={'items':[{'id':1,'hash':'current','mode':'review'}],'config':{},'request':{'selection':'range'}} monkeypatch.setattr(backfill,'prepare_start',AsyncMock(return_value=value)) monkeypatch.setattr(backfill.redis,'delete',AsyncMock()) before=datetime.now(UTC) result=asyncio.run(backfill.start(session,'preview','history_only',validated=True)) assert result=={'id':7} and settings.enabled if original_start is None: assert before<=settings.start_at<=datetime.now(UTC) else: assert settings.start_at==original_start session.__aenter__=AsyncMock(return_value=session);session.__aexit__=AsyncMock(return_value=False) job=N(id=7,settings={'request':{'run_mode':'history_only'}}) session.scalar=AsyncMock(side_effect=[job,1,job,None]) session.scalars=AsyncMock(return_value=N(all=lambda:[N(id=1,news_id=1,content_hash='current')])) monkeypatch.setattr(scheduler,'SessionLocal',lambda:session) picked=asyncio.run(scheduler.candidate(set(),0)) assert picked[0]==('backfill',1) @pytest.mark.parametrize('event_state', ['pending','processing','failed']) def test_exclusive_batch_tracks_event_without_package_research(trading,monkeypatch,event_state): from alphapulse.news_risk import backfill from alphapulse.models.risk import ReprocessJob,NewsEvent,RiskSettings config={'request':{'run_mode':'history_only'}} job=N(id=7,state='running',settings=config,failures=[]) event=N(id=9,state=event_state,published_revision=0,error='Synthetic') settings=N(enabled=True) session=MagicMock() session.get=AsyncMock(side_effect=lambda model,*a,**k:{ReprocessJob:job,NewsEvent:event,RiskSettings:settings}[model]) session.scalar=AsyncMock(return_value=None) session.scalars=AsyncMock(side_effect=[N(all=lambda:[]),N(all=lambda:[N(kind='events',object_id=9,revision=1)])]) session.commit=AsyncMock() enroll=AsyncMock();monkeypatch.setattr(backfill,'target',enroll) asyncio.run(backfill.reconcile(session,job)) enroll.assert_not_awaited() assert job.state==('failed' if event_state=='failed' else 'running') assert settings.enabled == (event_state!='failed') def test_exclusive_batch_finishes_after_event_dependency_is_published(trading,monkeypatch): from alphapulse.news_risk import backfill,events from alphapulse.models.risk import ReprocessJob,NewsEvent,NewsSummary,RiskSettings,EventMember config={'request':{'run_mode':'history_only'},'configurations':{'outlook':{'rules':{}}}} job=N(id=7,state='running',settings=config,failures=[]) event=N(id=9,state='done',published_revision=1) dependency=N(id=2,state='done',revision=2,published_revision=2,replacement_ids=[]) targets=[N(kind='events',object_id=9,revision=1),N(kind='analysis',object_id=2,revision=2)] settings=N(enabled=True) session=MagicMock() session.get=AsyncMock(side_effect=lambda model,*a,**k:{ ReprocessJob:job,NewsEvent:event,NewsSummary:dependency,RiskSettings:settings,EventMember:None}[model]) session.scalar=AsyncMock(side_effect=[None,N(id=3,state='done',quotes={})]) session.scalars=AsyncMock(side_effect=[N(all=lambda:[]),N(all=lambda:targets),N(all=lambda:[])]) session.commit=AsyncMock() monkeypatch.setattr(events,'reading_inputs',AsyncMock(return_value=[])) asyncio.run(backfill.reconcile(session,job)) assert job.state=='done' and not settings.enabled @pytest.mark.parametrize('failed_stage', ['grouping','events',None]) @pytest.mark.parametrize('prepare_only', [True,False]) def test_exclusive_outlook_never_admits_failed_batch_results(trading,monkeypatch,failed_stage,prepare_only): from alphapulse.news_risk import worker,events,reprocess from alphapulse.models.risk import ReprocessJob,ReprocessItem,NewsSummary,NewsEvent job=N(id=7,state='running',position=0,items=[],settings={'request':{'run_mode':'history_only'}}) failed_model={'grouping':ReprocessItem,'analysis':NewsSummary,'events':NewsEvent}.get(failed_stage) session=MagicMock() session.__aenter__=AsyncMock(return_value=session);session.__aexit__=AsyncMock(return_value=False) session.get=AsyncMock(return_value=N(enabled=True));session.commit=AsyncMock() async def scalar(query): model=query.column_descriptions[0]['entity'] if model is ReprocessJob: return job if model is failed_model: # Emulate filtering a stored failed row, without storage or model I/O. return 1 if any(isinstance(value,list) and 'failed' in value for value in query.compile().params.values()) else None return None session.scalar=AsyncMock(side_effect=scalar) inputs=[{'id':1,'kind':'package','revision':1,'importance_stars':3,'category':'company','result':{'summary':'Previous successful result'}}] monkeypatch.setattr(worker,'SessionLocal',lambda:session) monkeypatch.setattr(events,'reading_inputs',AsyncMock(return_value=inputs)) configuration=AsyncMock(return_value=(N(model='advanced'),'rules',{})) monkeypatch.setattr(reprocess,'frozen_configuration',configuration) generate=AsyncMock(return_value={'reading':[],'synthesis':None,'usage':[]}) monkeypatch.setattr(worker.briefing,'generate',generate) ready=asyncio.run(worker.outlook(prepare_only=prepare_only)) if failed_stage: assert ready is None configuration.assert_not_awaited();generate.assert_not_awaited();session.add.assert_not_called() elif prepare_only: assert ready is True generate.assert_not_awaited() else: assert generate.await_count==2 assert session.add.call_args.args[0].state=='done' @pytest.mark.parametrize('case', ['valid','wrong_date','wrong_text','wrong_quote','extra_evidence']) def test_event_plan_binds_date_precision_text_and_its_original_quote(trading,case): from alphapulse.news_risk.events import EventResult,validate_timeline def point(day): return dict(occurred_at=None,time_precision='unknown',planned_at=f'2026-11-{day}T00:00:00Z', planned_precision='day',time_text=f'11月{day}日',reported_at=None,description='Plan',verification='partial', evidence_refs=[{'article_id':1,'quote':f'计划11月{day}日开始'}]) first,second=point('10'),point('20') submitted={**first,'package_id':1,'package_revision':1} if case=='wrong_date': submitted={**second,'planned_at':first['planned_at'],'package_id':1,'package_revision':1} if case=='wrong_text': submitted['time_text']=second['time_text'] if case=='wrong_quote': submitted['evidence_refs']=second['evidence_refs'] if case=='extra_evidence': submitted['evidence_refs']=first['evidence_refs']+second['evidence_refs'] result=EventResult(title='Synthetic',summary='Synthetic',category='company',importance_stars=3,risk_stars=0, uncertainty='Unknown',opinions='Unknown',counter_evidence='Unknown',watchpoints='Unknown',timeline_points=[submitted]) packages=[{'id':1,'revision':1,'result':{'timeline_points':[first,second]}}] if case in ('valid','extra_evidence'): validate_timeline(result,packages) else: with pytest.raises(ValueError,match='已核验计划'): validate_timeline(result,packages)