#!/usr/bin/env python3 """ Delete every artifact Workflow 0's 2026-04-13 15:22-15:38 run created for Rachel Bergeron / NaturallyRachB. Scope — strictly things created by THAT specific W0 run: 1. Drive: Client Portal sheet (trash) 2. Drive: Knowledge Base doc (trash) 3. Drive: Brand Surface Guide HTML (trash) 4. Drive: Products/ folder (trash) 5. Drive: Campaigns/ folder (trash) 6. Drive: Content/Posts/ folder (trash) 7. FLSM Clients sheet row 9 (NaturallyRachB) 8. FLSM Projects sheet row where client=NaturallyRachB AND name="Client Onboarding" 9. FLSM Tasks sheet rows linked to that project 10. EN Onboarding Queue sheet row 2 (our manual insert) 11. Vercel project naturallyrachb-portal (domain detaches automatically) 12. Local file .tmp/onboard_naturallyrachb_2026-04-13.json 13. tools/onboard_scrape.py line 47 (naturallyrachb CLIENT_SHEETS entry) 14. tools/apify_scrape.py line 48 (naturallyrachb CLIENT_SHEETS entry) Usage: python3 .tmp/delete_w0_rachel.py # dry run, lists actions only python3 .tmp/delete_w0_rachel.py --execute # live deletions """ import os, sys, json, time, urllib.request, urllib.parse, urllib.error, pathlib, argparse ROOT = pathlib.Path(__file__).parent.parent for line in (ROOT / ".env").read_text().splitlines(): line = line.strip() if line and not line.startswith("#") and "=" in line: k, _, v = line.partition("=") os.environ.setdefault(k.strip(), v.strip()) GTOKEN_PATH = pathlib.Path.home() / ".config/google-workspace-mcp/profiles/emerson-north/tokens.json" GCREDS_PATH = pathlib.Path.home() / ".config/google-workspace-mcp/profiles/emerson-north/credentials.json" SHEETS = { "clients": "1YzvFkX-aXTZQTKgPYejOuaLzxrligXIDquBeTZqv4Es", "projects": "1EZZafN29DAf95TTn-aS3eiUUB0C4eGq8i8lqu_3Za04", "tasks": "1EVeY-oLF0GjQ2bm42_jbq73SlQzDfRWjOX-X3PCz4ZA", "queue": "1FX0eDt9d322XYcOQRp8b9tXkRrrrHcSWJ9maXEwYk7k", } DRIVE_ITEMS = { "Client Portal sheet": "1AbWVhUIXO9M-3fGW3dHmSk-0LktVwJS87iydSCTaltk", "Knowledge Base doc": "1v37V0HcI6BQ91gJlgnY2a6cV3RA0fWo4KwQdFihoqgQ", "Brand Surface Guide HTML": "1hjjIlzw2M20SX_V6BesdnVsse7EwxGpb", "Products/ folder": "1acGfloNHo3lZUNMDBtZOrmilmKq_nWwM", "Campaigns/ folder": "1tmvTULhfrRqH0fgaZigK9QgLEBpCYUJ_", "Content/Posts/ folder": "17dggwDPPVppPsogTmHHBC-llqS8XWxZj", } VERCEL_PROJECT_ID = "prj_WRptAlKcOjbaAtiURd1CmBnisPUg" VERCEL_PROJECT_NAME = "naturallyrachb-portal" LOCAL_FILE = ROOT / ".tmp/onboard_naturallyrachb_2026-04-13.json" # ── Auth helpers ────────────────────────────────────────────────────────────── def google_token(): t = json.loads(GTOKEN_PATH.read_text()) if t.get("expiry_date", 0) / 1000 > time.time() + 60: return t["access_token"] c = json.loads(GCREDS_PATH.read_text()) w = c.get("web") or c.get("installed", {}) data = urllib.parse.urlencode({ "client_id": w["client_id"], "client_secret": w["client_secret"], "refresh_token": t["refresh_token"], "grant_type": "refresh_token", }).encode() r = json.loads(urllib.request.urlopen(urllib.request.Request( "https://oauth2.googleapis.com/token", data=data, headers={"Content-Type": "application/x-www-form-urlencoded"}), timeout=15).read()) t["access_token"] = r["access_token"] t["expiry_date"] = int((time.time() + r["expires_in"]) * 1000) GTOKEN_PATH.write_text(json.dumps(t, indent=2)) return t["access_token"] def google_req(method, path, body=None, params=None, base="https://www.googleapis.com"): url = f"{base}{path}" if params: url += "?" + urllib.parse.urlencode(params) data = json.dumps(body).encode() if body is not None else None req = urllib.request.Request(url, data=data, method=method, headers={ "Authorization": f"Bearer {google_token()}", "Content-Type": "application/json", "User-Agent": "flsm-w0-cleanup", }) resp = urllib.request.urlopen(req, timeout=30) raw = resp.read() return json.loads(raw) if raw else None def vercel_req(method, path, body=None): url = f"https://api.vercel.com{path}" data = json.dumps(body).encode() if body is not None else None req = urllib.request.Request(url, data=data, method=method, headers={ "Authorization": f"Bearer {os.environ['VERCEL_TOKEN']}", "Content-Type": "application/json", "User-Agent": "flsm-w0-cleanup", }) resp = urllib.request.urlopen(req, timeout=30) raw = resp.read() return json.loads(raw) if raw else None # ── Actions ─────────────────────────────────────────────────────────────────── def trash_drive_item(label, file_id, execute): print(f" DRIVE {label} ({file_id}) -> trash", end="") if not execute: print(" [dry-run]") return try: google_req("PATCH", f"/drive/v3/files/{file_id}", body={"trashed": True}, params={"supportsAllDrives": "true"}) print(" ✓") except urllib.error.HTTPError as e: print(f" ✗ HTTP {e.code}: {e.read().decode()[:120]}") def sheet_find_rows(sheet_id, range_, predicate): """Return (1-indexed) row numbers matching predicate(row).""" rows = google_req("GET", f"/v4/spreadsheets/{sheet_id}/values/{urllib.parse.quote(range_)}", base="https://sheets.googleapis.com").get("values", []) return [(i + 1, r) for i, r in enumerate(rows) if predicate(r)] def sheet_delete_row(sheet_id, sheet_gid, row_num_1indexed, execute): """Use batchUpdate deleteDimension. row_num_1indexed is 1-based (row 1 = header).""" if not execute: print(f" would delete spreadsheet={sheet_id} gid={sheet_gid} row={row_num_1indexed}") return body = {"requests": [{"deleteDimension": {"range": { "sheetId": sheet_gid, "dimension": "ROWS", "startIndex": row_num_1indexed - 1, # 0-based inclusive "endIndex": row_num_1indexed, # 0-based exclusive }}}]} google_req("POST", f"/v4/spreadsheets/{sheet_id}:batchUpdate", body=body, base="https://sheets.googleapis.com") print(f" ✓ deleted row {row_num_1indexed}") def get_first_sheet_gid(sheet_id): meta = google_req("GET", f"/v4/spreadsheets/{sheet_id}", params={"fields": "sheets.properties"}, base="https://sheets.googleapis.com") return meta["sheets"][0]["properties"]["sheetId"] def delete_clients_row(execute): print("SHEETS: FLSM Clients — delete NaturallyRachB row") gid = get_first_sheet_gid(SHEETS["clients"]) matches = sheet_find_rows( SHEETS["clients"], "Sheet1!A1:J50", lambda r: any("NaturallyRachB" in (c or "") for c in r), ) for row_num, row in matches: print(f" found row {row_num}: {row[:4]}") sheet_delete_row(SHEETS["clients"], gid, row_num, execute) if not matches: print(" (none found)") def delete_projects_rows(execute): print("SHEETS: FLSM Projects — delete NaturallyRachB Client Onboarding project(s)") gid = get_first_sheet_gid(SHEETS["projects"]) matches = sheet_find_rows( SHEETS["projects"], "Sheet1!A1:N500", lambda r: any("NaturallyRachB" in (c or "") for c in r), ) for row_num, row in sorted(matches, key=lambda x: -x[0]): print(f" found row {row_num}: {row[:6]}") sheet_delete_row(SHEETS["projects"], gid, row_num, execute) if not matches: print(" (none found)") def delete_tasks_rows(execute): print("SHEETS: FLSM Tasks — delete NaturallyRachB tasks") gid = get_first_sheet_gid(SHEETS["tasks"]) matches = sheet_find_rows( SHEETS["tasks"], "Sheet1!A1:T500", lambda r: any("NaturallyRachB" in (c or "") for c in r), ) for row_num, row in sorted(matches, key=lambda x: -x[0]): print(f" found row {row_num}: {row[:6]}") sheet_delete_row(SHEETS["tasks"], gid, row_num, execute) if not matches: print(" (none found)") def delete_queue_row(execute): print("SHEETS: EN Onboarding Queue — delete NaturallyRachB row") gid = get_first_sheet_gid(SHEETS["queue"]) matches = sheet_find_rows( SHEETS["queue"], "Sheet1!A1:K100", lambda r: any("NaturallyRachB" in (c or "") for c in r), ) for row_num, row in sorted(matches, key=lambda x: -x[0]): print(f" found row {row_num}: {row[:4]}") sheet_delete_row(SHEETS["queue"], gid, row_num, execute) if not matches: print(" (none found)") def delete_drive_items(execute): print("DRIVE: trash 6 items") for label, fid in DRIVE_ITEMS.items(): trash_drive_item(label, fid, execute) def delete_vercel_project(execute): print(f"VERCEL: delete project {VERCEL_PROJECT_NAME} ({VERCEL_PROJECT_ID})", end="") if not execute: print(" [dry-run]") return try: vercel_req("DELETE", f"/v9/projects/{VERCEL_PROJECT_ID}") print(" ✓") except urllib.error.HTTPError as e: print(f" ✗ HTTP {e.code}: {e.read().decode()[:200]}") def delete_local_file(execute): print(f"LOCAL: remove {LOCAL_FILE}", end="") if not LOCAL_FILE.exists(): print(" (not found)") return if not execute: print(" [dry-run]") return LOCAL_FILE.unlink() print(" ✓") def edit_client_sheets_configs(execute): print("EDITS: remove naturallyrachb CLIENT_SHEETS entries") for rel in ("tools/onboard_scrape.py", "tools/apify_scrape.py"): path = ROOT / rel lines = path.read_text().splitlines(keepends=True) kept = [l for l in lines if "naturallyrachb" not in l] removed = len(lines) - len(kept) print(f" {rel}: {removed} line(s) to remove", end="") if removed == 0: print(" (already clean)") continue if not execute: print(" [dry-run]") continue path.write_text("".join(kept)) print(" ✓") # ── Main ────────────────────────────────────────────────────────────────────── def main(): parser = argparse.ArgumentParser() parser.add_argument("--execute", action="store_true", help="Actually perform deletions. Default is dry-run.") args = parser.parse_args() mode = "EXECUTE" if args.execute else "DRY RUN" print(f"=== Workflow 0 Rachel cleanup — {mode} ===\n") delete_drive_items(args.execute); print() delete_clients_row(args.execute); print() delete_projects_rows(args.execute); print() delete_tasks_rows(args.execute); print() delete_queue_row(args.execute); print() delete_vercel_project(args.execute); print() delete_local_file(args.execute); print() edit_client_sheets_configs(args.execute); print() print(f"=== {mode} complete ===") if __name__ == "__main__": main()