🌱 Complete seed import tool — all 17 kanban tasks done

Modules:
- parser.py: Full Excel parser (1,848 machines, Disney mapping, Pattern A+B parsing)
- db_writer.py: SQLite writer with per-field update policy (seed + update modes)
- backup.py: GPS/photo backup, restore, and compare
- reporter.py: Comprehensive validation report generator
- main.py: CLI entry point

Database: assets.db with 1,848 machines across 36 columns
Handbook: reference_handbook.md v2.0 — all sections finalized
Report: validation_report.md — 184 OCR corrections, 143 unknown machines

main.py

@@ -2,30 +2,108 @@
 """
 🌱 Canteen Seed Data Import Tool
 
-Standalone import pipeline for Cantaloupe CSV exports.
-Run with --help for usage.
+CLI entry point for the seed data import pipeline.
+Parses Cantaloupe Excel exports and writes to SQLite database.
 
-Pipeline stages:
-  1. Backup existing GPS + check-ins from target DB
-  2. Parse & map CSV headers
-  3. Extract location data from Customer/Place columns
-  4. Derive GPS coordinates (with multi-floor support)
-  5. Validate & correct serial numbers
-  6. Normalize Class/Make/Model
-  7. Apply pricing status, telemetry, alert metadata
-  8. Score priority from sales data
-  9. Write to DB (preserving existing GPS/check-ins)
-  10. Generate validation report
+Usage:
+    python3 main.py seed-data/Machine_List.xlsx --output seed-data/assets.db
+    python3 main.py seed-data/Machine_List.xlsx --output seed-data/assets.db --mode=update
+    python3 main.py seed-data/Machine_List.xlsx -o seed-data/assets.db -m seed
 """
 
+import argparse
 import sys
+import os
+
+# Import pipeline modules
+from parser import parse_excel
+from db_writer import write_seed, write_update
 
 
 def main():
+    parser = argparse.ArgumentParser(
+        description="🌱 Canteen Seed Data Import Tool",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=(
+            "Examples:\n"
+            "  %(prog)s seed-data/Machine_List.xlsx -o seed-data/assets.db\n"
+            "  %(prog)s seed-data/Machine_List.xlsx -o seed-data/assets.db --mode=update\n"
+        ),
+    )
+
+    parser.add_argument(
+        "input",
+        type=str,
+        help="Path to the input Excel file (Machine_List.xlsx)",
+    )
+
+    parser.add_argument(
+        "-o", "--output",
+        type=str,
+        default="seed-data/assets.db",
+        help="Output SQLite database path (default: seed-data/assets.db)",
+    )
+
+    parser.add_argument(
+        "-m", "--mode",
+        type=str,
+        choices=["seed", "update"],
+        default="seed",
+        help="Import mode: 'seed' for first import (fresh insert), 'update' for incremental (default: seed)",
+    )
+
+    args = parser.parse_args()
+
+    # Resolve input path
+    input_path = os.path.abspath(args.input)
+    if not os.path.exists(input_path):
+        print(f"❌ Error: Input file not found: {input_path}")
+        sys.exit(1)
+
+    output_path = os.path.abspath(args.output)
+
     print("🌱 Canteen Seed Data Import Tool")
-    print("  Coming soon — pipeline modules pending.")
-    sys.exit(0)
+    print("═" * 50)
+    print(f"  📄 Input:  {input_path}")
+    print(f"  📁 Output: {output_path}")
+    print(f"  🔧 Mode:   {args.mode}")
+    print()
+
+    # ── Step 1: Parse Excel ──
+    print("📋 Parsing Excel file...")
+    try:
+        machines = parse_excel(input_path)
+    except Exception as e:
+        print(f"❌ Error parsing Excel file: {e}")
+        sys.exit(1)
+
+    print(f"  ✅ Parsed {len(machines)} machines from Excel")
+    print()
+
+    # ── Step 2: Write to database ──
+    print("💾 Writing to database...")
+    if args.mode == "seed":
+        stats = write_seed(machines, output_path)
+    else:
+        stats = write_update(machines, output_path)
+
+    print()
+    print("═" * 50)
+    print("✅ Import complete!")
+    print(f"  Mode:      {args.mode}")
+    print(f"  Records:   {stats.get('inserted', 0) + stats.get('updated', 0)} processed")
+    if "inserted" in stats:
+        print(f"  Inserted:  {stats['inserted']}")
+    if "updated" in stats:
+        print(f"  Updated:   {stats['updated']}")
+    if "preserved" in stats:
+        print(f"  Preserved: {stats['preserved']}")
+    if "errors" in stats and stats["errors"]:
+        print(f"  Errors:    {stats['errors']}")
+    print("═" * 50)
+
+    return 0
 
 
 if __name__ == "__main__":
-    main()
+    sys.exit(main())