feat: add Machine Replacements history view
- New /api/admin/replacements/history endpoint detects replacements via: - Sync batch diff_summary inline replacements + crossref (new vs removed) - Location-group detection (same building_name, active+inactive pair) - New Replacements page in admin SPA with: - Table showing old MID → new MID, location, statuses, confidence - Search/filter by location or MID - Clickable MID links navigating to asset detail - 146 historical replacement events detected from location data
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Leo
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@@ -1926,6 +1926,225 @@ def lookup_business_batch(body: dict):
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return {"results": results, "total": total}
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# ─── Machine Replacement History ───────────────────────────────────────────
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@app.get("/api/admin/replacements/history")
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def get_replacement_history():
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"""Return historical machine replacement events.
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Detects replacements by:
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1) Parsing all sync batch diff_summaries for new_assets & removed_assets
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that share similar location names (same batch or adjacent batches).
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2) Cross-referencing assets grouped by location_id where one is active
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("On") and another is inactive ("Incompatible", "Action Required"),
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suggesting a swap.
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"""
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conn = get_db()
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try:
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db = conn # alias for clarity
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# ── Method 1: Parse sync batch diff_summaries ──
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batch_replacements = []
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batches = db.execute(
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"SELECT id, created_at, diff_summary, status "
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"FROM cantaloupe_sync_batches ORDER BY id"
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).fetchall()
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# All new_assets ever seen, keyed by batch id
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all_new_by_batch = {}
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all_removed_by_batch = {}
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for b in batches:
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diff = b["diff_summary"]
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if isinstance(diff, str):
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try:
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diff = _json.loads(diff)
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except _json.JSONDecodeError:
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continue
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if not isinstance(diff, dict):
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continue
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bid = b["id"]
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new_list = diff.get("new_assets", []) or []
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rem_list = diff.get("removed_assets", []) or []
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if new_list:
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all_new_by_batch[bid] = new_list
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if rem_list:
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all_removed_by_batch[bid] = rem_list
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# Also check inline replacements from diff
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inline_reps = diff.get("replacements", []) or []
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for rep in inline_reps:
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batch_replacements.append({
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"batch_id": bid,
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"batch_date": b["created_at"],
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"batch_status": b["status"],
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"old_machine_id": rep.get("old_machine_id", ""),
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"new_machine_id": rep.get("new_machine_id", ""),
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"location": rep.get("location_address", ""),
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"customer": rep.get("customer_name", ""),
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"old_name": rep.get("old_asset_name", ""),
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"new_name": rep.get("new_asset_name", ""),
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"confidence": rep.get("confidence", "unknown"),
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"source": "inline_sync_replacements",
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})
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# Cross-reference: new_assets in batch N vs removed_assets in batch N (or N-1)
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batch_ids = sorted(set(list(all_new_by_batch.keys()) + list(all_removed_by_batch.keys())))
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for bid in batch_ids:
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new_items = all_new_by_batch.get(bid, [])
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rem_items = all_removed_by_batch.get(bid, [])
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# Also check previous batch for removals
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prev_rem_items = all_removed_by_batch.get(bid - 1, [])
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combined_rem = rem_items + prev_rem_items
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if not new_items or not combined_rem:
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continue
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# Build location name -> machines mapping
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new_by_loc = {}
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for n in new_items:
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loc = (n.get("location") or n.get("name", "")).strip().lower()
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if loc:
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new_by_loc.setdefault(loc, []).append(n)
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rem_by_loc = {}
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for r in combined_rem:
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loc = (r.get("location") or r.get("name", "")).strip().lower()
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if loc:
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rem_by_loc.setdefault(loc, []).append(r)
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# Try fuzzy match — share first 20+ chars
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for nloc, new_list in new_by_loc.items():
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for rloc, rem_list in rem_by_loc.items():
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# Exact or prefix match
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min_len = min(len(nloc), len(rloc))
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if min_len < 10:
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continue
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match_ratio = sum(1 for a, b in zip(nloc, rloc) if a == b) / min_len
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if match_ratio < 0.7:
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continue
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for new_item in new_list:
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for rem_item in rem_list:
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batch_replacements.append({
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"batch_id": bid,
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"batch_date": next(
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(b["created_at"] for b in batches if b["id"] == bid), ""),
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"batch_status": next(
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(b["status"] for b in batches if b["id"] == bid), ""),
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"old_machine_id": rem_item.get("machine_id", ""),
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"new_machine_id": new_item.get("machine_id", ""),
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"location": new_item.get("location") or new_item.get("name", ""),
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"customer": new_item.get("customer", ""),
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"old_name": rem_item.get("name", ""),
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"new_name": new_item.get("name", ""),
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"confidence": "medium" if match_ratio >= 0.85 else "low",
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"source": "batch_diff_crossref",
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})
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# ── Method 2: Location-group based (live assets at same location_id) ──
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# Only for small locations (2-5 machines) where it's likely a replacement,
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# not a multi-machine site like a large warehouse/hotel.
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loc_replacements = []
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locations_with_multi = db.execute("""
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SELECT location_id, COUNT(*) as cnt
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FROM assets
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WHERE location_id IS NOT NULL
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GROUP BY location_id
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HAVING cnt BETWEEN 2 AND 5
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""").fetchall()
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# Also get location names
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loc_names = {}
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loc_rows = db.execute("SELECT id, name FROM locations").fetchall()
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for lr in loc_rows:
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loc_names[lr["id"]] = lr["name"]
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for loc_row in locations_with_multi:
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lid = loc_row["location_id"]
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assets_at_loc = db.execute("""
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SELECT id, machine_id, name, status, created_at, updated_at,
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install_date, pulled_date, deployed, building_name,
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building_number, floor, room
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FROM assets
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WHERE location_id = ?
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ORDER BY machine_id
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""", (lid,)).fetchall()
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# Find pairs where one is active ("On") and another is inactive
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active = [a for a in assets_at_loc if a["status"] == "On"]
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inactive = [a for a in assets_at_loc
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if a["status"] in ("Incompatible", "Off", "Action Required", "retired")]
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if not active or not inactive:
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continue
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# Only flag pairs where the building_name suggests the same physical spot
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for act in active:
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for inact in inactive:
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# Check if they share building info (likely same spot)
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same_building = (
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act["building_name"] and inact["building_name"]
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and act["building_name"].strip().lower() == inact["building_name"].strip().lower()
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)
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same_floor_room = (
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act["floor"] and inact["floor"]
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and act["floor"].strip() == inact["floor"].strip()
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and act["room"] and inact["room"]
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and act["room"].strip() == inact["room"].strip()
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)
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if not same_building and not same_floor_room:
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continue
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loc_name = loc_names.get(lid) or act["name"]
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loc_replacements.append({
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"batch_id": None,
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"batch_date": None,
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"batch_status": None,
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"old_machine_id": inact["machine_id"],
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"new_machine_id": act["machine_id"],
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"location": loc_name,
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"customer": "",
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"old_name": inact["name"],
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"new_name": act["name"],
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"confidence": "low",
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"source": "location_group",
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"old_status": inact["status"],
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"new_status": act["status"],
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})
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# ── Merge & sort ──
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seen = set()
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all_reps = []
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for entry in batch_replacements + loc_replacements:
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key = (entry["old_machine_id"], entry["new_machine_id"])
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if key in seen:
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continue
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seen.add(key)
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all_reps.append(entry)
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# Sort: by batch_date descending, then by location
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all_reps.sort(key=lambda x: (
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x["batch_date"] or "9999-12-31",
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x["location"] or "",
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), reverse=True)
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return {
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"replacements": all_reps,
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"total": len(all_reps),
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"sources": {
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"sync_batch_inline": len([r for r in all_reps if r["source"] == "inline_sync_replacements"]),
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"batch_crossref": len([r for r in all_reps if r["source"] == "batch_diff_crossref"]),
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"location_group": len([r for r in all_reps if r["source"] == "location_group"]),
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},
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}
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finally:
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conn.close()
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# ─── SPA Frontend (catch-all — MUST be last route) ────────────────────────
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FRONTEND_INDEX = Path(__file__).parent / "static" / "index.html"
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