174 lines
5.9 KiB
Python
174 lines
5.9 KiB
Python
"""Tests for sector and market rollup aggregation.
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Tests the pure rollup logic (no DB required).
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Requirements: 6.3, 6.4, 6.5
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"""
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from datetime import datetime, timezone
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from services.aggregation.rollups import (
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CompanyTrendRow,
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rollup_trends,
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_build_rollup_disagreement,
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_derive_rollup_direction,
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)
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from services.shared.schemas import TrendDirection, TrendWindow
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NOW = datetime(2026, 4, 11, 12, 0, 0, tzinfo=timezone.utc)
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def _make_trend(
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ticker: str = "AAPL",
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sector: str = "Technology",
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window: str = "7d",
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direction: str = "bullish",
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strength: float = 0.6,
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confidence: float = 0.8,
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contradiction: float = 0.1,
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catalysts: list[str] | None = None,
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risks: list[str] | None = None,
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supporting: list[str] | None = None,
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opposing: list[str] | None = None,
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) -> CompanyTrendRow:
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return CompanyTrendRow(
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entity_id=ticker,
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sector=sector,
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window=window,
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trend_direction=direction,
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trend_strength=strength,
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confidence=confidence,
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contradiction_score=contradiction,
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dominant_catalysts=catalysts or ["earnings"],
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material_risks=risks or [],
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top_supporting_evidence=supporting or ["doc-1"],
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top_opposing_evidence=opposing or [],
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)
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# ---------------------------------------------------------------------------
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# rollup_trends
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# ---------------------------------------------------------------------------
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def test_rollup_empty():
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summary = rollup_trends([], "sector", "Technology", "7d", NOW)
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assert summary.entity_type == "sector"
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assert summary.entity_id == "Technology"
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assert summary.trend_direction == TrendDirection.NEUTRAL
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assert summary.trend_strength == 0.0
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assert summary.confidence == 0.0
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def test_rollup_single_bullish():
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trends = [_make_trend("AAPL", direction="bullish", strength=0.7, confidence=0.9)]
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summary = rollup_trends(trends, "sector", "Technology", "7d", NOW)
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assert summary.trend_direction == TrendDirection.BULLISH
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assert summary.trend_strength > 0
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assert summary.confidence > 0
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assert summary.window == TrendWindow.SEVEN_DAY
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def test_rollup_mixed_directions():
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trends = [
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_make_trend("AAPL", direction="bullish", strength=0.6, confidence=0.8),
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_make_trend("MSFT", direction="bearish", strength=0.6, confidence=0.8),
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]
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summary = rollup_trends(trends, "sector", "Technology", "7d", NOW)
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# Equal and opposite → neutral or mixed
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assert summary.trend_direction in (TrendDirection.NEUTRAL, TrendDirection.MIXED)
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def test_rollup_confidence_weighted():
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"""Higher-confidence company should dominate the rollup direction."""
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trends = [
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_make_trend("AAPL", direction="bullish", strength=0.8, confidence=0.95),
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_make_trend("MSFT", direction="bearish", strength=0.3, confidence=0.2),
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]
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summary = rollup_trends(trends, "sector", "Technology", "7d", NOW)
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assert summary.trend_direction == TrendDirection.BULLISH
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def test_rollup_catalysts_aggregated():
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trends = [
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_make_trend("AAPL", catalysts=["earnings", "product"], confidence=0.8),
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_make_trend("MSFT", catalysts=["product", "macro"], confidence=0.6),
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]
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summary = rollup_trends(trends, "sector", "Technology", "7d", NOW)
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# "product" appears in both → should be top catalyst
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assert "product" in summary.dominant_catalysts
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def test_rollup_risks_deduplicated():
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trends = [
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_make_trend("AAPL", risks=["regulatory risk", "supply chain"], confidence=0.8),
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_make_trend("MSFT", risks=["Regulatory Risk", "tariffs"], confidence=0.6),
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]
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summary = rollup_trends(trends, "sector", "Technology", "7d", NOW)
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risk_lower = [r.lower() for r in summary.material_risks]
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assert risk_lower.count("regulatory risk") == 1
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def test_rollup_evidence_collected():
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trends = [
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_make_trend("AAPL", supporting=["doc-1", "doc-2"], opposing=["doc-3"]),
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_make_trend("MSFT", supporting=["doc-4"], opposing=["doc-5"]),
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]
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summary = rollup_trends(trends, "market", "all", "7d", NOW)
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assert "doc-1" in summary.top_supporting_evidence
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assert "doc-4" in summary.top_supporting_evidence
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assert "doc-3" in summary.top_opposing_evidence
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def test_rollup_market_entity_type():
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trends = [_make_trend("AAPL"), _make_trend("JPM", sector="Financials")]
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summary = rollup_trends(trends, "market", "all", "7d", NOW)
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assert summary.entity_type == "market"
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assert summary.entity_id == "all"
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# ---------------------------------------------------------------------------
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# _derive_rollup_direction
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# ---------------------------------------------------------------------------
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def test_derive_direction_bullish():
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assert _derive_rollup_direction(0.5, 0.0) == TrendDirection.BULLISH
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def test_derive_direction_bearish():
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assert _derive_rollup_direction(-0.5, 0.0) == TrendDirection.BEARISH
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def test_derive_direction_neutral():
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assert _derive_rollup_direction(0.05, 0.0) == TrendDirection.NEUTRAL
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def test_derive_direction_mixed_high_contradiction():
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assert _derive_rollup_direction(0.1, 0.2) == TrendDirection.MIXED
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# ---------------------------------------------------------------------------
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# _build_rollup_disagreement
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# ---------------------------------------------------------------------------
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def test_disagreement_no_conflict():
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trends = [
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_make_trend("AAPL", direction="bullish"),
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_make_trend("MSFT", direction="bullish"),
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]
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details = _build_rollup_disagreement(trends, "Technology")
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assert details == []
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def test_disagreement_with_conflict():
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trends = [
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_make_trend("AAPL", direction="bullish", confidence=0.8),
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_make_trend("MSFT", direction="bearish", confidence=0.7),
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]
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details = _build_rollup_disagreement(trends, "Technology")
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assert len(details) == 1
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assert details[0].dimension == "company_direction"
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assert "AAPL" in details[0].positive_doc_ids
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assert "MSFT" in details[0].negative_doc_ids
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