lotto-lab: DB 스키마 확장 — purchase_history ALTER + strategy 테이블 추가

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/tests/test_purchase_manager.py

@@ -0,0 +1,69 @@
+# backend/tests/test_purchase_manager.py
+import sys, os
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "app"))
+
+import sqlite3
+import pytest
+from unittest.mock import patch, MagicMock
+
+# ":memory:" 공유 커넥션 — 각 테스트에서 독립적으로 생성
+def _make_mem_conn():
+    conn = sqlite3.connect(":memory:")
+    conn.row_factory = sqlite3.Row
+    return conn
+
+
+def test_purchase_history_has_new_columns():
+    """purchase_history 테이블에 신규 컬럼이 존재하는지 검증"""
+    import db
+    mem = _make_mem_conn()
+    with patch("db._conn", return_value=mem):
+        db.init_db()
+
+    cols = {r["name"] for r in mem.execute("PRAGMA table_info(purchase_history)").fetchall()}
+    assert "numbers" in cols
+    assert "is_real" in cols
+    assert "source_strategy" in cols
+    assert "source_detail" in cols
+    assert "checked" in cols
+    assert "results" in cols
+    assert "total_prize" in cols
+    # 기존 컬럼도 유지
+    assert "draw_no" in cols
+    assert "amount" in cols
+    assert "sets" in cols
+    assert "prize" in cols
+    assert "note" in cols
+    mem.close()
+
+
+def test_strategy_performance_table_exists():
+    """strategy_performance 테이블이 생성되는지 검증"""
+    import db
+    mem = _make_mem_conn()
+    with patch("db._conn", return_value=mem):
+        db.init_db()
+
+    cols = {r["name"] for r in mem.execute("PRAGMA table_info(strategy_performance)").fetchall()}
+    assert "strategy" in cols
+    assert "draw_no" in cols
+    assert "sets_count" in cols
+    assert "total_correct" in cols
+    assert "avg_score" in cols
+    mem.close()
+
+
+def test_strategy_weights_table_exists():
+    """strategy_weights 테이블이 생성되고 초기값이 있는지 검증"""
+    import db
+    mem = _make_mem_conn()
+    with patch("db._conn", return_value=mem):
+        db.init_db()
+
+    rows = mem.execute("SELECT * FROM strategy_weights ORDER BY strategy").fetchall()
+    strategies = {r["strategy"] for r in rows}
+    assert strategies == {"combined", "simulation", "heatmap", "manual", "custom"}
+    # 가중치 합이 1.0
+    total_weight = sum(r["weight"] for r in rows)
+    assert abs(total_weight - 1.0) < 0.01
+    mem.close()