Test: export.build_kml coordinate invariants (regression for coord-less KML)

Five new checks in test_pipeline.py guard against places_map.kml being
generated without <Point><coordinates> elements when geocoded rows exist:
build_kml writes coords, omits Point for ungeocoded rows, correct pinned
count in mixed batches, full export→import round-trip, and export.run()
end-to-end via a temp CSV.

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

tests/test_pipeline.py

@@ -334,6 +334,100 @@ https://www.instagram.com/p/ABC123/]]></description>
     check("KML import: flat Placemark name",           flat_rows[0]["name"] == "Mystery Place")
 
 
+# ── export.build_kml ─────────────────────────────────────────────────────────
+
+def _row(**overrides) -> dict:
+    """Minimal valid row dict for export tests."""
+    base = {
+        "name": "Ichiran", "city": "Tokyo", "state": "Tokyo", "country": "Japan",
+        "address": "UNKNOWN", "category": "Restaurant", "cuisine": "Ramen",
+        "price_range": "$$", "highlight": "Best ramen", "occasion": "UNKNOWN",
+        "lat": "35.6595000", "lng": "139.7005000", "creator": "ramenking",
+        "saved_at": "2024-03-15", "instagram_url": "https://instagram.com/p/abc",
+        "status": "unvisited",
+    }
+    base.update(overrides)
+    return base
+
+
+def test_build_kml_writes_coordinates():
+    from pipeline import export as export_mod
+    kml = export_mod.build_kml([_row()])
+    check("build_kml: <Point> present for geocoded row",      "<Point>" in kml)
+    check("build_kml: <coordinates> tag present",             "<coordinates>" in kml)
+    check("build_kml: lng,lat,alt order correct",             "139.7005000,35.6595000,0" in kml)
+
+
+def test_build_kml_omits_point_for_no_coords():
+    from pipeline import export as export_mod
+    kml = export_mod.build_kml([_row(lat="", lng="")])
+    check("build_kml: no <Point> for ungeocoded row",         "<Point>" not in kml)
+    check("build_kml: no <coordinates> for ungeocoded row",   "<coordinates>" not in kml)
+
+
+def test_build_kml_mixed_pinned_count():
+    """Only geocoded rows emit <Point>; ungeocoded rows are included but pin-free."""
+    from pipeline import export as export_mod
+    rows = [
+        _row(name="Geocoded"),
+        _row(name="Not Geocoded", lat="", lng=""),
+        _row(name="Also Geocoded", lat="34.6937", lng="135.5023"),
+    ]
+    kml = export_mod.build_kml(rows)
+    import xml.etree.ElementTree as ET
+    root = ET.fromstring(kml)
+    ns = "http://www.opengis.net/kml/2.2"
+    coords = root.findall(f".//{{{ns}}}coordinates")
+    placemarks = root.findall(f".//{{{ns}}}Placemark")
+    check("build_kml: 3 placemarks total",                    len(placemarks) == 3)
+    check("build_kml: exactly 2 <coordinates> for 2 geocoded rows", len(coords) == 2)
+
+
+def test_build_kml_coordinates_roundtrip():
+    """export.build_kml → _parse_import_kml preserves lat/lng exactly."""
+    from pipeline import export as export_mod
+    from web.app import _parse_import_kml
+    rows_in = [
+        _row(name="Ichiran"),
+        _row(name="No Coord Cafe", lat="", lng=""),
+    ]
+    kml_bytes = export_mod.build_kml(rows_in).encode("utf-8")
+    rows_out = _parse_import_kml(kml_bytes)
+    geocoded = [r for r in rows_out if r.get("lat") and r.get("lng")]
+    check("roundtrip: 1 geocoded row survives",               len(geocoded) == 1)
+    check("roundtrip: lat preserved",                         geocoded[0]["lat"] == "35.6595000")
+    check("roundtrip: lng preserved",                         geocoded[0]["lng"] == "139.7005000")
+    check("roundtrip: name preserved",                        geocoded[0]["name"] == "Ichiran")
+    check("roundtrip: total row count unchanged",             len(rows_out) == 2)
+
+
+def test_export_run_writes_coordinates():
+    """export.run() reads a CSV with geocoded rows and writes <Point> elements."""
+    import csv as _csv, tempfile, xml.etree.ElementTree as ET
+    from pipeline import export as export_mod
+    from pipeline.extract import FIELDNAMES
+
+    rows = [_row(name="Ichiran"), _row(name="No Coord", lat="", lng="")]
+
+    with tempfile.TemporaryDirectory() as d:
+        csv_path = f"{d}/places_full.csv"
+        kml_path = f"{d}/places_map.kml"
+        with open(csv_path, "w", newline="", encoding="utf-8") as f:
+            w = _csv.DictWriter(f, fieldnames=FIELDNAMES)
+            w.writeheader()
+            w.writerows(rows)
+
+        export_mod.run(csv_path, kml_path)
+
+        kml_content = open(kml_path, encoding="utf-8").read()
+        root = ET.fromstring(kml_content)
+        ns = "http://www.opengis.net/kml/2.2"
+        coords = root.findall(f".//{{{ns}}}coordinates")
+        check("export.run: KML file written",                  len(kml_content) > 0)
+        check("export.run: exactly 1 <coordinates> for 1 geocoded row", len(coords) == 1)
+        check("export.run: coordinate value correct",          "139.7005" in (coords[0].text or ""))
+
+
 # ── FOOD_CATEGORIES sync invariant ────────────────────────────────────────────
 
 def test_food_categories_sync():
@@ -674,6 +768,11 @@ test_parse_response()
 test_parse_responses_dedup()
 test_parse_import_csv()
 test_parse_import_kml()
+test_build_kml_writes_coordinates()
+test_build_kml_omits_point_for_no_coords()
+test_build_kml_mixed_pinned_count()
+test_build_kml_coordinates_roundtrip()
+test_export_run_writes_coordinates()
 test_food_categories_sync()
 test_parse_batch_response_none_guard()
 test_parse_batch_response_empty_string()