Initial commit with translated description

tests/test_summarize.py

@@ -0,0 +1,345 @@
+"""Tests for summarize helpers."""
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent.parent / "scripts"))
+
+from datetime import datetime
+
+import summarize
+from summarize import (
+    MoverContext,
+    SectorCluster,
+    WatchpointsData,
+    build_watchpoints_data,
+    classify_move_type,
+    detect_sector_clusters,
+    format_watchpoints,
+    get_index_change,
+    match_headline_to_symbol,
+)
+
+
+class FixedDateTime(datetime):
+    @classmethod
+    def now(cls, tz=None):
+        return cls(2026, 1, 1, 15, 0)
+
+
+def test_generate_briefing_auto_time_evening(capsys, monkeypatch):
+    def fake_market_news(*_args, **_kwargs):
+        return {
+            "headlines": [
+                {"source": "CNBC", "title": "Headline one", "link": "https://example.com/1"},
+                {"source": "Yahoo", "title": "Headline two", "link": "https://example.com/2"},
+                {"source": "CNBC", "title": "Headline three", "link": "https://example.com/3"},
+            ],
+            "markets": {
+                "us": {
+                    "name": "US Markets",
+                    "indices": {
+                        "^GSPC": {"name": "S&P 500", "data": {"price": 100, "change_percent": 1.0}},
+                    },
+                }
+            },
+        }
+
+    def fake_summary(*_args, **_kwargs):
+        return "OK"
+
+    monkeypatch.setattr(summarize, "get_market_news", fake_market_news)
+    monkeypatch.setattr(summarize, "get_portfolio_news", lambda *_a, **_k: None)
+    monkeypatch.setattr(summarize, "summarize_with_claude", fake_summary)
+    monkeypatch.setattr(summarize, "datetime", FixedDateTime)
+
+    args = type(
+        "Args",
+        (),
+        {
+            "lang": "de",
+            "style": "briefing",
+            "time": None,
+            "model": "claude",
+            "json": False,
+            "research": False,
+            "deadline": None,
+            "fast": False,
+            "llm": False,
+            "debug": False,
+        },
+    )()
+
+    summarize.generate_briefing(args)
+    stdout = capsys.readouterr().out
+    assert "Börsen Abend-Briefing" in stdout
+
+
+# --- Tests for watchpoints feature (Issue #92) ---
+
+
+class TestGetIndexChange:
+    def test_extracts_sp500_change(self):
+        market_data = {
+            "markets": {
+                "us": {
+                    "indices": {
+                        "^GSPC": {"data": {"change_percent": -1.5}}
+                    }
+                }
+            }
+        }
+        assert get_index_change(market_data) == -1.5
+
+    def test_returns_zero_on_missing_data(self):
+        assert get_index_change({}) == 0.0
+        assert get_index_change({"markets": {}}) == 0.0
+        assert get_index_change({"markets": {"us": {}}}) == 0.0
+
+
+class TestMatchHeadlineToSymbol:
+    def test_exact_symbol_match_dollar(self):
+        headlines = [{"title": "Breaking: $NVDA surges on AI demand"}]
+        result = match_headline_to_symbol("NVDA", "NVIDIA Corporation", headlines)
+        assert result is not None
+        assert "NVDA" in result["title"]
+
+    def test_exact_symbol_match_parens(self):
+        headlines = [{"title": "Tesla (TSLA) reports record deliveries"}]
+        result = match_headline_to_symbol("TSLA", "Tesla Inc", headlines)
+        assert result is not None
+
+    def test_exact_symbol_match_word_boundary(self):
+        headlines = [{"title": "AAPL announces new product line"}]
+        result = match_headline_to_symbol("AAPL", "Apple Inc", headlines)
+        assert result is not None
+
+    def test_company_name_match(self):
+        headlines = [{"title": "Apple announces record iPhone sales"}]
+        result = match_headline_to_symbol("AAPL", "Apple Inc", headlines)
+        assert result is not None
+
+    def test_no_match_returns_none(self):
+        headlines = [{"title": "Fed raises interest rates"}]
+        result = match_headline_to_symbol("NVDA", "NVIDIA Corporation", headlines)
+        assert result is None
+
+    def test_avoids_partial_symbol_match(self):
+        # "APP" should not match "application"
+        headlines = [{"title": "New application launches today"}]
+        result = match_headline_to_symbol("APP", "AppLovin Corp", headlines)
+        assert result is None
+
+    def test_empty_headlines(self):
+        result = match_headline_to_symbol("NVDA", "NVIDIA", [])
+        assert result is None
+
+
+class TestDetectSectorClusters:
+    def test_detects_cluster_three_stocks_same_direction(self):
+        movers = [
+            {"symbol": "NVDA", "change_pct": -5.0},
+            {"symbol": "AMD", "change_pct": -4.0},
+            {"symbol": "INTC", "change_pct": -3.0},
+        ]
+        portfolio_meta = {
+            "NVDA": {"category": "Tech"},
+            "AMD": {"category": "Tech"},
+            "INTC": {"category": "Tech"},
+        }
+        clusters = detect_sector_clusters(movers, portfolio_meta)
+        assert len(clusters) == 1
+        assert clusters[0].category == "Tech"
+        assert clusters[0].direction == "down"
+        assert len(clusters[0].stocks) == 3
+
+    def test_no_cluster_if_less_than_three(self):
+        movers = [
+            {"symbol": "NVDA", "change_pct": -5.0},
+            {"symbol": "AMD", "change_pct": -4.0},
+        ]
+        portfolio_meta = {
+            "NVDA": {"category": "Tech"},
+            "AMD": {"category": "Tech"},
+        }
+        clusters = detect_sector_clusters(movers, portfolio_meta)
+        assert len(clusters) == 0
+
+    def test_no_cluster_if_mixed_direction(self):
+        movers = [
+            {"symbol": "NVDA", "change_pct": 5.0},
+            {"symbol": "AMD", "change_pct": -4.0},
+            {"symbol": "INTC", "change_pct": 3.0},
+        ]
+        portfolio_meta = {
+            "NVDA": {"category": "Tech"},
+            "AMD": {"category": "Tech"},
+            "INTC": {"category": "Tech"},
+        }
+        clusters = detect_sector_clusters(movers, portfolio_meta)
+        assert len(clusters) == 0
+
+
+class TestClassifyMoveType:
+    def test_earnings_with_keyword(self):
+        headline = {"title": "Company beats Q3 earnings expectations"}
+        result = classify_move_type(headline, False, 5.0, 0.1)
+        assert result == "earnings"
+
+    def test_sector_cluster(self):
+        result = classify_move_type(None, True, -3.0, -0.5)
+        assert result == "sector"
+
+    def test_market_wide(self):
+        result = classify_move_type(None, False, -2.0, -2.0)
+        assert result == "market_wide"
+
+    def test_company_specific_with_headline(self):
+        headline = {"title": "Company announces acquisition"}
+        result = classify_move_type(headline, False, 3.0, 0.1)
+        assert result == "company_specific"
+
+    def test_company_specific_large_move_no_headline(self):
+        result = classify_move_type(None, False, 8.0, 0.1)
+        assert result == "company_specific"
+
+    def test_unknown_small_move_no_context(self):
+        result = classify_move_type(None, False, 1.5, 0.2)
+        assert result == "unknown"
+
+
+class TestFormatWatchpoints:
+    def test_formats_sector_cluster(self):
+        cluster = SectorCluster(
+            category="Tech",
+            stocks=[
+                MoverContext("NVDA", -5.0, 100.0, "Tech", None, "sector", None),
+                MoverContext("AMD", -4.0, 80.0, "Tech", None, "sector", None),
+                MoverContext("INTC", -3.0, 30.0, "Tech", None, "sector", None),
+            ],
+            avg_change=-4.0,
+            direction="down",
+            vs_index=-3.5,
+        )
+        data = WatchpointsData(
+            movers=[],
+            sector_clusters=[cluster],
+            index_change=-0.5,
+            market_wide=False,
+        )
+        result = format_watchpoints(data, "en", {})
+        assert "Tech" in result
+        assert "-4.0%" in result
+        assert "vs Index" in result
+
+    def test_formats_individual_mover_with_headline(self):
+        mover = MoverContext(
+            symbol="NVDA",
+            change_pct=5.0,
+            price=100.0,
+            category="Tech",
+            matched_headline={"title": "NVIDIA reports record revenue"},
+            move_type="company_specific",
+            vs_index=4.5,
+        )
+        data = WatchpointsData(
+            movers=[mover],
+            sector_clusters=[],
+            index_change=0.5,
+            market_wide=False,
+        )
+        result = format_watchpoints(data, "en", {})
+        assert "NVDA" in result
+        assert "+5.0%" in result
+        assert "record revenue" in result
+
+    def test_formats_market_wide_move_english(self):
+        data = WatchpointsData(
+            movers=[],
+            sector_clusters=[],
+            index_change=-2.0,
+            market_wide=True,
+        )
+        result = format_watchpoints(data, "en", {})
+        assert "Market-wide move" in result
+        assert "S&P 500 fell 2.0%" in result
+
+    def test_formats_market_wide_move_german(self):
+        data = WatchpointsData(
+            movers=[],
+            sector_clusters=[],
+            index_change=2.5,
+            market_wide=True,
+        )
+        result = format_watchpoints(data, "de", {})
+        assert "Breite Marktbewegung" in result
+        assert "stieg 2.5%" in result
+
+    def test_uses_label_fallbacks(self):
+        mover = MoverContext(
+            symbol="XYZ",
+            change_pct=1.5,
+            price=50.0,
+            category="Other",
+            matched_headline=None,
+            move_type="unknown",
+            vs_index=1.0,
+        )
+        data = WatchpointsData(
+            movers=[mover],
+            sector_clusters=[],
+            index_change=0.5,
+            market_wide=False,
+        )
+        labels = {"no_catalyst": " -- no news"}
+        result = format_watchpoints(data, "en", labels)
+        assert "XYZ" in result
+        assert "no news" in result
+
+
+class TestBuildWatchpointsData:
+    def test_builds_complete_data_structure(self):
+        movers = [
+            {"symbol": "NVDA", "change_pct": -5.0, "price": 100.0},
+            {"symbol": "AMD", "change_pct": -4.0, "price": 80.0},
+            {"symbol": "INTC", "change_pct": -3.0, "price": 30.0},
+            {"symbol": "AAPL", "change_pct": 2.0, "price": 150.0},
+        ]
+        headlines = [
+            {"title": "NVIDIA reports weak guidance"},
+            {"title": "Apple announces new product"},
+        ]
+        portfolio_meta = {
+            "NVDA": {"category": "Tech", "name": "NVIDIA Corporation"},
+            "AMD": {"category": "Tech", "name": "Advanced Micro Devices"},
+            "INTC": {"category": "Tech", "name": "Intel Corporation"},
+            "AAPL": {"category": "Tech", "name": "Apple Inc"},
+        }
+        index_change = -0.5
+
+        result = build_watchpoints_data(movers, headlines, portfolio_meta, index_change)
+
+        # Should detect Tech sector cluster (3 losers)
+        assert len(result.sector_clusters) == 1
+        assert result.sector_clusters[0].category == "Tech"
+        assert result.sector_clusters[0].direction == "down"
+
+        # All movers should be present
+        assert len(result.movers) == 4
+
+        # NVDA should have matched headline
+        nvda_mover = next(m for m in result.movers if m.symbol == "NVDA")
+        assert nvda_mover.matched_headline is not None
+        assert "guidance" in nvda_mover.matched_headline["title"]
+
+        # vs_index should be calculated
+        assert nvda_mover.vs_index == -5.0 - (-0.5)  # -4.5
+
+    def test_handles_empty_movers(self):
+        result = build_watchpoints_data([], [], {}, 0.0)
+        assert result.movers == []
+        assert result.sector_clusters == []
+        assert result.market_wide is False
+
+    def test_detects_market_wide_move(self):
+        result = build_watchpoints_data([], [], {}, -2.0)
+        assert result.market_wide is True