Add lamp_station.py: barcode-driven measurement workflow

Interactive loop around lamp_export.py: scan an EAN (checksum
validated, optional for barcode-less lamps), resolve it against
previous lamps / a local cache / upcitemdb.com, confirm
identification, record the packaging's advertised values, measure
per the published procedure, and commit the bundle to the
comparison-data repo with a device page stub for the web repo.

Every lamp is keyed by an internal ID (L0001, L0002, ...) so one EAN
can cover several versions (daylight/warm white variants) and
unbranded lamps work. lamp_export.py passes optional ean, variant,
and rated (advertised values) fields through into metrics.json.

lamp_export.py

@@ -172,9 +172,19 @@ def write_bundle(reading, out_dir, meta, n_readings, supply=None):
         for b in tm30["bins"]:
             w.writerow({k: (f"{v:.6g}" if isinstance(v, float) else v) for k, v in b.items()})
 
-    # metrics.json — grouped scalars plus identification.
-    metrics = {
-        "name": meta["name"],
+    # metrics.json — grouped scalars plus identification. ean/variant are set
+    # by lamp_station.py when one barcode covers several versions of a lamp
+    # (e.g. daylight and warm white sharing box art and EAN).
+    metrics = {"name": meta["name"]}
+    if meta.get("ean"):
+        metrics["ean"] = meta["ean"]
+    if meta.get("variant"):
+        metrics["variant"] = meta["variant"]
+    if meta.get("rated"):
+        # Advertised values from the packaging, keyed like their measured
+        # counterparts so consumers can pair them (truth-in-advertising rows).
+        metrics["rated"] = meta["rated"]
+    metrics |= {
         "manufacturer": meta["manufacturer"],
         "model": meta["model"],
         "notes": meta["notes"],