csv-parser: add _apply_mapping helper

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

tests/test_llm_csv_parser.py

@@ -152,3 +152,71 @@ def test_validate_mapping_non_numeric_qty_raises():
     mapping = {"ticker_col": "Symbol", "qty_col": "Description"}
     with pytest.raises(LLMParseError, match="numeric"):
         _validate_mapping(mapping, headers, first_row)
+
+
+def test_apply_mapping_builds_parsed_pie():
+    from app.services.csv_import import ParsedPie, ParsedPosition
+    from app.services.llm_csv_parser import _apply_mapping
+
+    headers = ["Symbol", "Quantity", "Avg Price", "Currency", "Description"]
+    data_rows = [
+        ["AAPL", "100", "150.25", "USD", "Apple Inc"],
+        ["MSFT", "50", "310.00", "USD", "Microsoft Corp"],
+    ]
+    mapping = {
+        "ticker_col": "Symbol",
+        "qty_col": "Quantity",
+        "cost_col": "Avg Price",
+        "currency_col": "Currency",
+        "name_col": "Description",
+    }
+
+    pie = _apply_mapping(headers, data_rows, mapping)
+
+    assert isinstance(pie, ParsedPie)
+    assert len(pie.positions) == 2
+    p0 = pie.positions[0]
+    assert isinstance(p0, ParsedPosition)
+    assert p0.slice == "AAPL"
+    assert p0.name == "Apple Inc"
+    assert p0.quantity == 100.0
+    assert p0.invested_value == pytest.approx(15025.0)
+    # invested = qty * avg_cost = 100 * 150.25 = 15025
+    assert pie.invested == pytest.approx(15025.0 + 50 * 310.00)
+
+
+def test_apply_mapping_handles_missing_optional_columns():
+    from app.services.llm_csv_parser import _apply_mapping
+
+    headers = ["Symbol", "Quantity"]
+    data_rows = [["AAPL", "100"]]
+    mapping = {
+        "ticker_col": "Symbol",
+        "qty_col": "Quantity",
+        "cost_col": None,
+        "currency_col": None,
+        "name_col": None,
+    }
+
+    pie = _apply_mapping(headers, data_rows, mapping)
+    p = pie.positions[0]
+    assert p.slice == "AAPL"
+    assert p.quantity == 100.0
+    assert p.invested_value is None
+    assert p.name == "AAPL"  # falls back to ticker when name_col absent
+
+
+def test_apply_mapping_skips_blank_and_unparseable_rows():
+    from app.services.llm_csv_parser import _apply_mapping
+
+    headers = ["Symbol", "Quantity"]
+    data_rows = [
+        ["AAPL", "100"],
+        ["", ""],                   # blank
+        ["MSFT", "not-a-number"],   # bad qty
+        ["NVDA", "40"],
+    ]
+    mapping = {"ticker_col": "Symbol", "qty_col": "Quantity"}
+
+    pie = _apply_mapping(headers, data_rows, mapping)
+    assert [p.slice for p in pie.positions] == ["AAPL", "NVDA"]