feat: import Seed (mycantaloupe.com) data — 1,655 assets enriched

- Added import_seed.py — reads Machine List(8).xlsx, matches by Asset ID → machine_id
- 51 new columns on assets table (route, barcode, sales, contact info, etc.)
- seed_data table with full 62-field JSON per asset for detail enrichment
- Seed data card in frontend asset detail view
- GET /api/assets/{id} now returns result.seed and result.seed_imported_at
- GPS columns from Seed ignored per request
- 1,654 matched, 199 unmatched (Seed-only assets not in MSFS)

Refs #47

import_seed.py

@@ -0,0 +1,292 @@
+#!/usr/bin/env python3
+"""
+Import Seed (mycantaloupe.com) Excel data into the Canteen Asset Tracker.
+
+Steps:
+1. Read Machine List(8).xlsx — 62 columns of Seed export
+2. Match rows by Asset ID → assets.machine_id
+3. Add key columns to assets table
+4. Create seed_data table with full JSON per asset
+5. Update matched assets, report match stats
+
+Usage:
+    python3 import_seed.py
+"""
+
+import json
+import os
+import sqlite3
+import sys
+from datetime import datetime, date
+
+import openpyxl
+
+# ── Paths ──────────────────────────────────────────────────────────────────
+PROJECT_DIR = os.path.expanduser("~/projects/canteen-asset-tracker")
+DB_PATH = os.path.join(PROJECT_DIR, "assets.db")
+EXCEL_PATH = os.path.expanduser(
+    "/home/oplabs/.hermes/profiles/coder/cache/documents/doc_305e40fb92dd_Machine List(8).xlsx"
+)
+
+# ── Columns to extract as first-class DB columns ──────────────────────────
+# (db_column, excel_header, type)
+KEY_COLUMNS = [
+    ("device",               "Device",              "TEXT DEFAULT ''"),
+    ("seed_location",        "Location",            "TEXT DEFAULT ''"),
+    ("seed_city",            "City",                "TEXT DEFAULT ''"),
+    ("state",                "State",               "TEXT DEFAULT ''"),
+    ("postal_code",          "Postal Code",         "TEXT DEFAULT ''"),
+    ("route_name",           "Route",               "TEXT DEFAULT ''"),
+    ("subroute_name",        "Subroute",            "TEXT DEFAULT ''"),
+    ("seed_class",           "Class",               "TEXT DEFAULT ''"),
+    ("customer_name",        "Customer",            "TEXT DEFAULT ''"),
+    ("management_company",   "Management Company",  "TEXT DEFAULT ''"),
+    ("branch",               "Branch",              "TEXT DEFAULT ''"),
+    ("location_code",        "Location Code",       "TEXT DEFAULT ''"),
+    ("customer_code",        "Customer Code",       "TEXT DEFAULT ''"),
+    ("barcode",              "Barcode",             "TEXT DEFAULT ''"),
+    ("has_cashless",         "Has Cashless",        "TEXT DEFAULT ''"),
+    ("phone",                "Phone",               "TEXT DEFAULT ''"),
+    ("fax",                  "Fax",                 "TEXT DEFAULT ''"),
+    ("email",                "Email",               "TEXT DEFAULT ''"),
+    ("asset_family",         "Asset Family",        "TEXT DEFAULT ''"),
+    ("business_type",        "Business Type",       "TEXT DEFAULT ''"),
+    ("primary_consumer_type","Primary Consumer Type","TEXT DEFAULT ''"),
+    ("machine_branding",     "Machine Branding",    "TEXT DEFAULT ''"),
+    ("valid_address",        "Valid Address",       "TEXT DEFAULT ''"),
+    ("non_revenue",          "Non-Revenue",         "TEXT DEFAULT ''"),
+    ("alerts",               "Alerts",              "TEXT DEFAULT ''"),
+    ("coil_alerts",          "Coil Alerts",         "INTEGER DEFAULT 0"),
+    ("product_alerts",       "Product Alerts",      "INTEGER DEFAULT 0"),
+    ("daily_avg_sales",      "Daily Average Sales", "REAL DEFAULT NULL"),
+    ("monthly_sales",        "Monthly Sales",       "REAL DEFAULT NULL"),
+    ("yearly_sales",         "Yearly Sales",        "REAL DEFAULT NULL"),
+    ("today_sales",          "Today Sales",         "REAL DEFAULT NULL"),
+    ("yesterday_sales",      "Yesterday Sales",     "REAL DEFAULT NULL"),
+    ("weekly_sales",         "Weekly Sales",        "REAL DEFAULT NULL"),
+    ("sales_restock",        "Sales (Restock)",     "REAL DEFAULT NULL"),
+    ("last_restock",         "Last Restock",        "TEXT DEFAULT ''"),
+    ("days_since_restock",   "Days Since Restock",  "INTEGER DEFAULT NULL"),
+    ("last_contact_time",    "Last Contact Time",   "TEXT DEFAULT ''"),
+    ("last_dex_report_time", "Last Dex Report Time","TEXT DEFAULT ''"),
+    ("last_inventory",       "Last Inventory",      "TEXT DEFAULT ''"),
+    ("prepick_group",        "Prepick Group",       "TEXT DEFAULT ''"),
+    ("added_date",           "Added Date",          "TEXT DEFAULT ''"),
+    ("purchase_date",        "Purchase Date",       "TEXT DEFAULT ''"),
+    ("purchase_price",       "Purchase Price",      "REAL DEFAULT NULL"),
+    ("depreciation_years",   "Depreciation Years",  "REAL DEFAULT NULL"),
+    ("cash_discount",        "Cash Discount",       "REAL DEFAULT NULL"),
+    ("tax_jurisdiction",     "Tax Jurisdiction",    "TEXT DEFAULT ''"),
+    ("commission_plan",      "Commission Plan",     "TEXT DEFAULT ''"),
+    ("acquirer_from",        "Acquired From",       "TEXT DEFAULT ''"),
+    ("changer_par",          "Changer Par",         "TEXT DEFAULT ''"),
+    ("machine_management_code","Machine Management Code","TEXT DEFAULT ''"),
+]
+
+# ── All 62 columns for the seed_data JSON dump ────────────────────────────
+ALL_SEED_FIELDS = [
+    "Device", "Location", "Asset ID", "Place", "Type",
+    "City", "Address", "Last Contact Time", "Last Dex Report Time",
+    "Last Restock", "Coil Alerts", "Product Alerts", "Sales (Restock)",
+    "Daily Average Sales", "Today Sales", "Yesterday Sales", "Weekly Sales",
+    "Monthly Sales", "Yearly Sales", "Days Since Restock", "Prepick Group",
+    "Customer", "Management Company", "Management Account",
+    "Machine Management Code", "Route", "Subroute", "Changer Par",
+    "Acquired From", "Purchase Date", "Purchase Price", "Depreciation Years",
+    "Post-Depreciation Monthly Cost", "State", "Postal Code", "Deployed",
+    "Pulled Date", "Serial Number", "Class", "Make", "Model",
+    "Cash Discount", "Tax Jurisdiction", "Commission Plan", "Barcode",
+    "Non-Revenue", "Added Date", "Phone", "Fax", "Email", "Has Cashless",
+    "Branch", "Location Code", "Customer Code", "Last Inventory",
+    "Asset Family", "Status", "Alerts", "Valid Address",
+    "Business Type", "Primary Consumer Type", "Machine Branding",
+]
+
+
+# ── Schema migration helpers ──────────────────────────────────────────────
+def get_db_columns(conn):
+    cursor = conn.execute("PRAGMA table_info(assets)")
+    return {row[1] for row in cursor.fetchall()}
+
+
+def add_column_if_missing(conn, col_name, col_type):
+    existing = get_db_columns(conn)
+    if col_name not in existing:
+        sql = f"ALTER TABLE assets ADD COLUMN {col_name} {col_type}"
+        conn.execute(sql)
+        print(f"  Added column: {col_name} {col_type}")
+        return True
+    return False
+
+
+def create_seed_data_table(conn):
+    conn.execute("""
+        CREATE TABLE IF NOT EXISTS seed_data (
+            id          INTEGER PRIMARY KEY AUTOINCREMENT,
+            asset_id    INTEGER NOT NULL REFERENCES assets(id) ON DELETE CASCADE,
+            raw_data    TEXT    NOT NULL,
+            imported_at TEXT    NOT NULL DEFAULT (datetime('now')),
+            UNIQUE(asset_id)
+        )
+    """)
+    print("  seed_data table ready")
+    # Add index
+    conn.execute("""
+        CREATE INDEX IF NOT EXISTS idx_seed_data_asset_id
+        ON seed_data(asset_id)
+    """)
+
+
+# ── Parse Excel ──────────────────────────────────────────────────────────
+def read_excel():
+    """Return (header_map, rows) where header_map is ExcelHeader->col_index."""
+    wb = openpyxl.load_workbook(EXCEL_PATH, data_only=True)
+    ws = wb.active
+    headers = {}
+    for col in range(1, ws.max_column + 1):
+        val = ws.cell(row=1, column=col).value
+        if val is not None:
+            headers[str(val).strip()] = col
+
+    rows = []
+    for row_idx in range(2, ws.max_row + 1):
+        row_data = {}
+        for hdr, col in headers.items():
+            val = ws.cell(row=row_idx, column=col).value
+            row_data[hdr] = val
+        row_data["_row"] = row_idx
+        rows.append(row_data)
+
+    return headers, rows
+
+
+# ── Main import ──────────────────────────────────────────────────────────
+def main():
+    print("═══ SEED DATA IMPORT ═══\n")
+
+    # 1. Connect to DB
+    conn = sqlite3.connect(DB_PATH)
+    conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA foreign_keys=ON")
+    print(f"[DB] Connected: {DB_PATH}")
+
+    # 2. Schema migration
+    print("\n[MIGRATE] Adding new asset columns if missing...")
+    for col_name, excel_header, col_type in KEY_COLUMNS:
+        add_column_if_missing(conn, col_name, col_type)
+
+    print("\n[MIGRATE] Creating seed_data table...")
+    create_seed_data_table(conn)
+    conn.commit()
+
+    # 3. Read Excel
+    print(f"\n[READ] Reading {EXCEL_PATH}...")
+    headers, rows = read_excel()
+    print(f"[READ] Found {len(headers)} columns, {len(rows)} data rows")
+
+    # 4. Pre-build machine_id lookup
+    cursor = conn.execute("SELECT id, machine_id FROM assets")
+    machine_map = {}  # machine_id -> asset_id
+    for row in cursor.fetchall():
+        machine_map[str(row["machine_id"]).strip()] = row["id"]
+
+    print(f"[MATCH] DB has {len(machine_map)} assets to match against")
+
+    # 5. Import
+    matched = 0
+    skipped_no_id = 0
+    unmatched = 0
+    key_field_updates = 0
+    json_inserts = 0
+
+    for row in rows:
+        asset_id_val = row.get("Asset ID")
+        if asset_id_val is None or str(asset_id_val).strip() == "":
+            skipped_no_id += 1
+            continue
+
+        asset_id_str = str(asset_id_val).strip()
+        db_asset_id = machine_map.get(asset_id_str)
+
+        if db_asset_id is None:
+            unmatched += 1
+            continue
+
+        # Update key columns on assets table
+        update_parts = []
+        update_vals = []
+        for col_name, excel_header, col_type in KEY_COLUMNS:
+            val = row.get(excel_header)
+            # Handle None → NULL for SQL
+            update_parts.append(f"{col_name} = ?")
+            if val is None:
+                update_vals.append(None)
+            else:
+                if "INTEGER" in col_type:
+                    try:
+                        update_vals.append(int(val))
+                    except (ValueError, TypeError):
+                        update_vals.append(0)
+                elif "REAL" in col_type:
+                    try:
+                        update_vals.append(float(val))
+                    except (ValueError, TypeError):
+                        update_vals.append(None)
+                else:
+                    update_vals.append(str(val))
+
+        update_vals.append(db_asset_id)
+        conn.execute(
+            f"UPDATE assets SET {', '.join(update_parts)} WHERE id = ?",
+            update_vals,
+        )
+        key_field_updates += 1
+
+        # Insert/upsert seed_data JSON
+        raw_data = {}
+        for hdr in ALL_SEED_FIELDS:
+            val = row.get(hdr)
+            if val is not None:
+                raw_data[hdr] = val
+
+        # Convert non-serializable types (datetime, etc.) to strings
+        def _serialize(v):
+            if isinstance(v, (datetime, date)):
+                return v.isoformat()
+            return v
+        raw_json = json.dumps(raw_data, default=_serialize)
+        conn.execute(
+            """INSERT OR REPLACE INTO seed_data (asset_id, raw_data, imported_at)
+               VALUES (?, ?, datetime('now'))""",
+            (db_asset_id, raw_json),
+        )
+        json_inserts += 1
+        matched += 1
+
+    conn.commit()
+
+    # 6. Stats
+    print(f"\n═══ RESULTS ═══")
+    print(f"Seed rows:              {len(rows)}")
+    print(f"Matched (↔ assets):     {matched}")
+    print(f"Unmatched (no asset):   {unmatched}")
+    print(f"Rows without Asset ID:  {skipped_no_id}")
+    print(f"Key field updates:      {key_field_updates}")
+    print(f"JSON blobs inserted:    {json_inserts}")
+
+    # Re-count assets with seed data
+    seed_count = conn.execute(
+        "SELECT COUNT(*) FROM seed_data"
+    ).fetchone()[0]
+    print(f"\nseed_data table:         {seed_count} rows")
+
+    # Show DB size
+    db_size = os.path.getsize(DB_PATH) / (1024 * 1024)
+    print(f"DB size:                 {db_size:.1f} MB")
+
+    conn.close()
+    print("\n═══ DONE ═══")
+
+
+if __name__ == "__main__":
+    main()

server.py

@@ -1138,8 +1138,6 @@ def get_asset(asset_id: int):
         ).fetchone()
         result["location_name"] = loc["name"] if loc else None
 
-    conn.close()
-
     # Enrich with MSFS data (from Dynamics 365 Field Service)
     msfs = _MSFS_LOOKUP.get(result.get("machine_id", "")) or _MSFS_BY_ID.get(asset_id)
     if msfs:
@@ -1158,6 +1156,19 @@ def get_asset(asset_id: int):
             "work_order_count": msfs.get("work_order_count", 0),
         }
 
+    # Enrich with Seed data (from mycantaloupe.com)
+    seed_row = conn.execute(
+        "SELECT raw_data, imported_at FROM seed_data WHERE asset_id = ?",
+        (asset_id,),
+    ).fetchone()
+    if seed_row:
+        try:
+            result["seed"] = _json.loads(seed_row["raw_data"])
+            result["seed_imported_at"] = seed_row["imported_at"]
+        except Exception:
+            result["seed"] = None
+    conn.close()
+
     return result
 
 

static/index.html

@@ -1315,6 +1315,12 @@
         <div id="detailMsfsFields"></div>
       </div>
 
+      <!-- Seed Data (mycantaloupe.com enrichment) -->
+      <div class="card" id="detailSeedCard" style="display:none;">
+        <div class="card-title">🌱 Cantaloupe/Seed Data</div>
+        <div id="detailSeedFields"></div>
+      </div>
+
       <!-- Check-in History -->
       <div class="card">
         <div class="card-title">Check-in History <span id="checkinCount" style="color:var(--accent2);"></span></div>
@@ -3834,6 +3840,66 @@
           msfsCard.style.display = 'none';
         }
 
+        // Seed Data (Cantaloupe/mycantaloupe.com enrichment)
+        const seedCard = document.getElementById('detailSeedCard');
+        const seedFields = document.getElementById('detailSeedFields');
+        if (a.seed) {
+          const s = a.seed;
+          // Define which Seed fields to show and in what order
+          const seedRows = [
+            df('Device',              s.Device, true),
+            df('Type',                s.Type),
+            df('Class',               s.Class),
+            df('Asset Family',        s['Asset Family']),
+            df('Customer',            s.Customer),
+            df('Management Company',  s['Management Company']),
+            df('Branch',              s.Branch),
+            df('Route',               s.Route),
+            df('Subroute',            s.Subroute),
+            df('Location',            s.Location),
+            df('Location Code',       s['Location Code']),
+            df('Customer Code',       s['Customer Code']),
+            df('Place',               s.Place),
+            df('Barcode',             s.Barcode, true),
+            df('Serial #',            s['Serial Number'], true),
+            df('Valid Address',       s['Valid Address']),
+            df('Business Type',       s['Business Type']),
+            df('Primary Consumer',    s['Primary Consumer Type']),
+            df('Machine Branding',    s['Machine Branding']),
+            df('Has Cashless',        s['Has Cashless'] ? '✅ Yes' : '❌ No'),
+            df('Non-Revenue',         s['Non-Revenue']),
+            df('Phone',               s.Phone),
+            df('Email',               s.Email),
+            df('Fax',                 s.Fax),
+            df('Alerts',              s.Alerts),
+            df('Coil Alerts',         s['Coil Alerts']),
+            df('Product Alerts',      s['Product Alerts']),
+            df('Daily Avg Sales',     s['Daily Average Sales'] != null ? '$' + parseFloat(s['Daily Average Sales']).toFixed(2) : null),
+            df('Monthly Sales',       s['Monthly Sales'] != null ? '$' + parseFloat(s['Monthly Sales']).toFixed(2) : null),
+            df('Yearly Sales',        s['Yearly Sales'] != null ? '$' + parseFloat(s['Yearly Sales']).toFixed(2) : null),
+            df('Last Restock',        s['Last Restock']),
+            df('Days Since Restock',  s['Days Since Restock']),
+            df('Last Contact',        s['Last Contact Time']),
+            df('Last DEX Report',     s['Last Dex Report Time']),
+            df('Last Inventory',      s['Last Inventory']),
+            df('Prepick Group',       s['Prepick Group']),
+            df('Added Date',          s['Added Date']),
+            df('Status',              s.Status),
+            df('Make',                s.Make),
+            df('Model',               s.Model),
+            df('State',               s.State),
+            df('Postal Code',         s['Postal Code']),
+          ].filter(Boolean).join('');
+          if (seedRows) {
+            seedFields.innerHTML = seedRows;
+            seedCard.style.display = 'block';
+          } else {
+            seedCard.style.display = 'none';
+          }
+        } else {
+          seedCard.style.display = 'none';
+        }
+
         await loadCheckinHistory(id);
       } catch (e) {
         showToast(e.message, true);