simon
c72a5ed13a
- system.yaml 新增 llm_scenes（translation / daily_report，含用途/方法/模型要求说明） - load_llm_config(scene=...) 场景覆盖；日报摘要 temperature 0.3 硬编码 → 配置 - M3 去重：唯一篇记录 source_ids（跨源重复合并，首个来源为 source_id） - source_ids 经翻译透传至 events，日报事件 source 多来源拼接展示（≤3 个） - 已部署 pi5：merge 实证 10 源合并；日报 report_id=224 正常入库
202 lines
8.1 KiB
Python
202 lines
8.1 KiB
Python
"""日报结构化入库：模型 + _build_report_data 组装（纯逻辑，不连 DB）。"""
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from __future__ import annotations
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import json
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from collections import Counter
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from datetime import date, datetime
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import pytest
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from pydantic import ValidationError
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from report_db.models import EventRow, ReportData
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from scheduler.reporter import _build_report_data
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# --------------------------------------------------------------------------- #
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# 模型默认值
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# --------------------------------------------------------------------------- #
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class TestEventRow:
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def test_minimal(self) -> None:
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ev = EventRow(section="intl", rank=1, title="标题")
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assert ev.importance is None
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assert ev.sentiment is None
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def test_full(self) -> None:
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ev = EventRow(
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section="intl", rank=2, importance=4, event_type="地缘政治",
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title="t", summary="s", sentiment="negative", source="InvestingLive",
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url="https://x.com/1",
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)
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assert ev.sentiment == "negative"
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def test_missing_title_raises(self) -> None:
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with pytest.raises(ValidationError):
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EventRow(section="intl", rank=1) # type: ignore[call-arg]
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class TestReportData:
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def test_defaults(self) -> None:
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r = ReportData(
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report_date=date(2026, 8, 4),
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report_type="intl",
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generated_at=datetime(2026, 8, 4, 8, 0),
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)
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assert r.file_name == ""
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assert r.stats == {}
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assert r.events == []
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def test_with_events(self) -> None:
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r = ReportData(
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report_date=date(2026, 8, 4),
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report_type="intl",
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generated_at=datetime(2026, 8, 4, 8, 0),
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ai_summary="摘要",
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events=[EventRow(section="intl", rank=1, title="t")],
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)
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assert len(r.events) == 1
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# --------------------------------------------------------------------------- #
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# _build_report_data（intl 结构）
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# --------------------------------------------------------------------------- #
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def _fake_high_event(title_zh: str, importance: int, *,
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event_type: str = "其他", sentiment: str = "neutral",
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summary_zh: str = "摘要", source_id: str = "investinglive",
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url: str = "https://investinglive.com/news/1") -> dict:
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"""构造 _dedup_events 之后的事件结构（含 article 属性）。"""
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return {
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"importance": importance,
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"sentiment": sentiment,
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"summary_zh": summary_zh,
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"event_type": event_type,
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"stock_codes": [],
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"article": {
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"title": f"EN {title_zh}",
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"title_zh": title_zh,
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"url": url,
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"source_id": source_id,
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},
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}
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class TestBuildReportData:
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def test_sections_and_ranks(self) -> None:
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now = datetime(2026, 8, 4, 8, 0, 0)
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high = [
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_fake_high_event("新闻A", 5),
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_fake_high_event("新闻B", 4),
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_fake_high_event("新闻C", 3),
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]
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r = _build_report_data(
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now, {"raw_total": 100, "proc": 90}, high,
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Counter(), Counter(), Counter(), Counter(), "AI摘要",
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)
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assert r.report_date == date(2026, 8, 4)
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assert r.report_type == "intl"
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assert r.file_name == ""
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assert r.ai_summary == "AI摘要"
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assert [(e.section, e.rank) for e in r.events] == [
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("intl", 1), ("intl", 2), ("intl", 3),
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]
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def test_field_mapping(self) -> None:
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now = datetime(2026, 8, 4, 8, 0, 0)
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high = [_fake_high_event("英伟达财报超预期", 5, event_type="公司财报",
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sentiment="positive", summary_zh="营收超预期",
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source_id="investinglive",
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url="https://investinglive.com/news/42")]
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r = _build_report_data(now, {}, high, Counter(), Counter(), Counter(),
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Counter(), "")
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ev = r.events[0]
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assert ev.title == "英伟达财报超预期" # title_zh 优先
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assert ev.importance == 5
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assert ev.event_type == "公司财报"
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assert ev.summary == "营收超预期"
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assert ev.sentiment == "positive"
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assert ev.url == "https://investinglive.com/news/42"
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assert ev.source == "InvestingLive" # 域名 → 源展示名
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def test_source_fallback_without_url(self) -> None:
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now = datetime(2026, 8, 4, 8, 0, 0)
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ev = _fake_high_event("无URL事件", 4, url="")
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r = _build_report_data(now, {}, [ev], Counter(), Counter(), Counter(),
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Counter(), "")
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assert r.events[0].url is None
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# url 为空时回退 source_id → sources.yaml 展示名
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assert r.events[0].source == "InvestingLive"
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def test_stats_snapshot(self) -> None:
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now = datetime(2026, 8, 4, 8, 0, 0)
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high = [
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_fake_high_event("A", 5, event_type="宏观", sentiment="positive"),
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_fake_high_event("B", 4, event_type="宏观", sentiment="negative"),
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]
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r = _build_report_data(
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now,
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{"raw_total": 120, "proc": 100, "deduped": 90,
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"emb_count": 80, "qdrant_count": 75},
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high,
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Counter({"positive": 1, "negative": 1}),
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Counter({5: 1, 4: 1}),
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Counter({"宏观": 2}),
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Counter({"investinglive": 2}),
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"摘要",
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)
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# stats 可 JSON 序列化（入库时 json.dumps）
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json.dumps(r.stats, ensure_ascii=False)
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assert r.stats["pipeline"]["raw_total"] == 120
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assert r.stats["sentiment"] == {"positive": 1, "negative": 1}
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assert r.stats["importance"] == [
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{"importance": 4, "count": 1}, {"importance": 5, "count": 1},
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]
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assert r.stats["event_types"] == [{"event_type": "宏观", "count": 2}]
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assert r.stats["source_dist"] == [{"source": "InvestingLive", "count": 2}]
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def test_title_truncated(self) -> None:
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now = datetime(2026, 8, 4, 8, 0, 0)
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ev = _fake_high_event("长" * 600, 4)
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r = _build_report_data(now, {}, [ev], Counter(), Counter(), Counter(),
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Counter(), "")
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assert len(r.events[0].title) == 512
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def test_empty_events(self) -> None:
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now = datetime(2026, 8, 4, 8, 0, 0)
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r = _build_report_data(now, {}, [], Counter(), Counter(), Counter(),
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Counter(), "")
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assert r.events == []
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assert r.ai_summary is None
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def test_question_mark_sentiment_normalized(self) -> None:
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now = datetime(2026, 8, 4, 8, 0, 0)
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ev = _fake_high_event("未分类情绪", 4, sentiment="?")
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r = _build_report_data(now, {}, [ev], Counter(), Counter(), Counter(),
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Counter(), "")
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# "?" 不写入 DB，留 None
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assert r.events[0].sentiment is None
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def test_multi_source_label(self) -> None:
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"""去重合并后的多来源 → source 拼接展示（Reuters, CNBC）。"""
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now = datetime(2026, 8, 4, 8, 0, 0)
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ev = _fake_high_event("多来源事件", 5, source_id="reuters",
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url="https://reuters.com/news/9")
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# 模拟 M3 去重合并：source_ids 含两个来源
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ev["article"]["source_ids"] = ["reuters", "cnbc"]
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r = _build_report_data(now, {}, [ev], Counter(), Counter(), Counter(),
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Counter(), "")
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assert r.events[0].source == "Reuters, CNBC"
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assert r.events[0].url == "https://reuters.com/news/9"
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def test_single_source_falls_back(self) -> None:
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"""source_ids 为空/单一时回退单源逻辑（不拼接）。"""
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now = datetime(2026, 8, 4, 8, 0, 0)
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ev = _fake_high_event("单来源事件", 4, source_id="investinglive",
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url="https://investinglive.com/news/3")
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ev["article"]["source_ids"] = ["investinglive"]
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r = _build_report_data(now, {}, [ev], Counter(), Counter(), Counter(),
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Counter(), "")
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assert r.events[0].source == "InvestingLive"
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