sync: Auto-sync from ACG-M-L5090 at 2026-03-10 19:11:00

Synced files:
- Quote wizard frontend (all components, hooks, types, config)
- API updates (config, models, routers, schemas, services)
- Client work (bg-builders, gurushow)
- Scripts (BGB Lesley termination, CIPP, Datto, migration)
- Temp files (Bardach contacts, VWP investigation, misc)
- Credentials and session logs
- Email service, PHP API, session logs

Machine: ACG-M-L5090
Timestamp: 2026-03-10 19:11:00

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

temp/bardach_dedup_step4_delete_batch.py

@@ -0,0 +1,151 @@
+#!/usr/bin/env python3
+"""Step 4: Delete duplicate contacts in batches.
+Usage: python bardach_dedup_step4_delete_batch.py [start_offset]
+Processes 500 deletes per run. Saves progress."""
+
+import json
+import subprocess
+import sys
+import time
+import os
+
+TENANT_ID = "dd4a82e8-85a3-44ac-8800-07945ab4d95f"
+CLIENT_ID = "fabb3421-8b34-484b-bc17-e46de9703418"
+CLIENT_SECRET = "~QJ8Q~NyQSs4OcGqHZyPrA2CVnq9KBfKiimntbMO"
+SCOPE = "https://graph.microsoft.com/.default"
+USER = "barbara@bardach.net"
+PLAN_FILE = "D:/ClaudeTools/temp/bardach_dedup_plan.json"
+PROGRESS_FILE = "D:/ClaudeTools/temp/bardach_dedup_delete_progress.json"
+RESULTS_FILE = "D:/ClaudeTools/temp/bardach_dedup_delete_results.json"
+BATCH_SIZE = 500
+
+
+def get_token():
+    url = f"https://login.microsoftonline.com/{TENANT_ID}/oauth2/v2.0/token"
+    result = subprocess.run(
+        ["curl", "-s", "-X", "POST", url,
+         "-H", "Content-Type: application/x-www-form-urlencoded",
+         "-d", f"client_id={CLIENT_ID}&scope={SCOPE}&client_secret={CLIENT_SECRET}&grant_type=client_credentials"],
+        capture_output=True, text=True
+    )
+    data = json.loads(result.stdout)
+    if "access_token" not in data:
+        print(f"[ERROR] Failed to get token: {data}", flush=True)
+        sys.exit(1)
+    return data["access_token"]
+
+
+def delete_contact(token, contact_id):
+    url = f"https://graph.microsoft.com/v1.0/users/{USER}/contacts/{contact_id}"
+    result = subprocess.run(
+        ["curl", "-s", "-X", "DELETE", url,
+         "-H", f"Authorization: Bearer {token}",
+         "-w", "%{http_code}"],
+        capture_output=True, text=True
+    )
+    output = result.stdout.strip()
+    try:
+        status_code = int(output[-3:])
+    except (ValueError, IndexError):
+        status_code = 0
+    return status_code
+
+
+def load_progress():
+    if os.path.exists(PROGRESS_FILE):
+        with open(PROGRESS_FILE, "r", encoding="utf-8") as f:
+            return json.load(f)
+    return {"completed_index": 0, "successes": 0, "failures": []}
+
+
+def save_progress(progress):
+    with open(PROGRESS_FILE, "w", encoding="utf-8") as f:
+        json.dump(progress, f, indent=2, ensure_ascii=False)
+
+
+def main():
+    start_offset = int(sys.argv[1]) if len(sys.argv) > 1 else None
+
+    with open(PLAN_FILE, "r", encoding="utf-8") as f:
+        plan_data = json.load(f)
+
+    all_deletes = []
+    for entry in plan_data["plan"]:
+        for did in entry["delete_ids"]:
+            all_deletes.append({"id": did, "display_name": entry["display_name"]})
+
+    total = len(all_deletes)
+
+    progress = load_progress()
+    start = start_offset if start_offset is not None else progress["completed_index"]
+    end = min(start + BATCH_SIZE, total)
+
+    print(f"DELETE BATCH: {start}-{end} of {total} (batch size {BATCH_SIZE})", flush=True)
+
+    if start >= total:
+        print(f"[OK] All {total} deletes already processed!", flush=True)
+        print(f"  Successes: {progress['successes']}", flush=True)
+        print(f"  Failures: {len(progress['failures'])}", flush=True)
+        # Save final results
+        with open(RESULTS_FILE, "w", encoding="utf-8") as f:
+            json.dump({
+                "total_attempted": total,
+                "successes": progress["successes"],
+                "failures": len(progress["failures"]),
+                "failure_details": progress["failures"]
+            }, f, indent=2, ensure_ascii=False)
+        return
+
+    token = get_token()
+    print("[OK] Token acquired", flush=True)
+
+    successes = progress["successes"]
+    failures = list(progress["failures"])
+    batch_start_time = time.time()
+
+    for i in range(start, end):
+        item = all_deletes[i]
+        status_code = delete_contact(token, item["id"])
+
+        if status_code == 204 or status_code == 200:
+            successes += 1
+        elif status_code == 404:
+            # Already deleted (maybe from previous run)
+            successes += 1
+        else:
+            failures.append({"display_name": item["display_name"], "id": item["id"], "status": status_code})
+
+        if (i - start + 1) % 100 == 0:
+            elapsed = time.time() - batch_start_time
+            rate = (i - start + 1) / elapsed if elapsed > 0 else 0
+            print(f"  {i + 1}/{total} | Batch: {i - start + 1}/{end - start} | OK: {successes} | Fail: {len(failures)} | {rate:.1f}/sec", flush=True)
+
+        if (i - start + 1) % 50 == 0:
+            time.sleep(0.3)
+
+    # Save progress
+    progress = {"completed_index": end, "successes": successes, "failures": failures}
+    save_progress(progress)
+
+    elapsed = time.time() - batch_start_time
+    print(f"\nBatch complete: {start}-{end} in {elapsed:.0f}s", flush=True)
+    print(f"  Total successes so far: {successes}", flush=True)
+    print(f"  Total failures so far: {len(failures)}", flush=True)
+    print(f"  Next batch starts at: {end}", flush=True)
+
+    if end < total:
+        print(f"  Remaining: {total - end}", flush=True)
+    else:
+        print(f"[OK] ALL DELETES COMPLETE!", flush=True)
+        with open(RESULTS_FILE, "w", encoding="utf-8") as f:
+            json.dump({
+                "total_attempted": total,
+                "successes": successes,
+                "failures": len(failures),
+                "failure_details": failures
+            }, f, indent=2, ensure_ascii=False)
+        print(f"[OK] Results saved to {RESULTS_FILE}", flush=True)
+
+
+if __name__ == "__main__":
+    main()