From b845eece0f05389252509ae60d7bcbfc2d8519b0 Mon Sep 17 00:00:00 2001
From: Abdelkouddous LHACHIMI <abdel.lhachimi@gmail.com>
Date: Fri, 27 Mar 2026 23:59:16 +0100
Subject: [PATCH] Initial Implementation

---
 Endolife - Demandes 20261603.xlsx             |  Bin 0 -> 12040 bytes
 Endolife_Reporting - 261303.xlsx              |  Bin 0 -> 449894 bytes
 config/DO_Dashboard_Config.xlsx               |  Bin 0 -> 81027 bytes
 config/Endobest_Dashboard_Config.xlsx         |  Bin 79106 -> 0 bytes
 config/do_dashboard_extended_template.xlsx    |  Bin 0 -> 41864 bytes
 ... => do_dashboard_monitoring_template.xlsx} |  Bin
 config/eb_dashboard_extended_template.xlsx    |  Bin 41198 -> 0 bytes
 do_dashboard.bat                              |    4 +
 do_dashboard.py                               | 1475 ++++++++++++
 do_dashboard_check_only-exe.bat               |    3 +
 do_dashboard_check_only.bat                   |    4 +
 do_dashboard_check_only_debug-exe.bat         |    3 +
 do_dashboard_check_only_debug.bat             |    4 +
 do_dashboard_constants.py                     |  135 ++
 do_dashboard_debug-exe.bat                    |    3 +
 do_dashboard_debug.bat                        |    4 +
 do_dashboard_excel_export.py                  | 2094 +++++++++++++++++
 do_dashboard_excel_only-exe.bat               |    3 +
 do_dashboard_excel_only.bat                   |    4 +
 do_dashboard_quality_checks.py                |  786 +++++++
 do_dashboard_utils.py                         |  221 ++
 21 files changed, 4743 insertions(+)
 create mode 100644 Endolife - Demandes 20261603.xlsx
 create mode 100644 Endolife_Reporting - 261303.xlsx
 create mode 100644 config/DO_Dashboard_Config.xlsx
 delete mode 100644 config/Endobest_Dashboard_Config.xlsx
 create mode 100644 config/do_dashboard_extended_template.xlsx
 rename config/{eb_dashboard_monitoring_template.xlsx => do_dashboard_monitoring_template.xlsx} (100%)
 delete mode 100644 config/eb_dashboard_extended_template.xlsx
 create mode 100644 do_dashboard.bat
 create mode 100644 do_dashboard.py
 create mode 100644 do_dashboard_check_only-exe.bat
 create mode 100644 do_dashboard_check_only.bat
 create mode 100644 do_dashboard_check_only_debug-exe.bat
 create mode 100644 do_dashboard_check_only_debug.bat
 create mode 100644 do_dashboard_constants.py
 create mode 100644 do_dashboard_debug-exe.bat
 create mode 100644 do_dashboard_debug.bat
 create mode 100644 do_dashboard_excel_export.py
 create mode 100644 do_dashboard_excel_only-exe.bat
 create mode 100644 do_dashboard_excel_only.bat
 create mode 100644 do_dashboard_quality_checks.py
 create mode 100644 do_dashboard_utils.py

diff --git a/Endolife - Demandes 20261603.xlsx b/Endolife - Demandes 20261603.xlsx
new file mode 100644
index 0000000000000000000000000000000000000000..312bacb87bd96259aee173786d1e790993fc7f0a
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diff --git a/config/Endobest_Dashboard_Config.xlsx b/config/Endobest_Dashboard_Config.xlsx
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diff --git a/config/eb_dashboard_monitoring_template.xlsx b/config/do_dashboard_monitoring_template.xlsx
similarity index 100%
rename from config/eb_dashboard_monitoring_template.xlsx
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diff --git a/config/eb_dashboard_extended_template.xlsx b/config/eb_dashboard_extended_template.xlsx
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diff --git a/do_dashboard.bat b/do_dashboard.bat
new file mode 100644
index 0000000..79e59ec
--- /dev/null
+++ b/do_dashboard.bat
@@ -0,0 +1,4 @@
+@echo off
+call C:\PythonProjects\.rcvenv\Scripts\activate.bat
+python do_dashboard.py %*
+
diff --git a/do_dashboard.py b/do_dashboard.py
new file mode 100644
index 0000000..f39542d
--- /dev/null
+++ b/do_dashboard.py
@@ -0,0 +1,1475 @@
+
+# DO (Diagnostic Order) Dashboard Generator
+# This script automates the collection and processing of diagnostic order requests from the Ziwig GDD platform.
+# It authenticates with Ziwig's IAM and GDD APIs to gather all worklist requests, their details, and
+# associated professional (prescriber/requester) information. The script generates a comprehensive JSON
+# report containing all request data, with 100% configurable fields defined in an Excel configuration file.
+# All fields are externalized and can be configured without any code modification. The configuration
+# supports multiple data sources, custom functions for business logic, field dependencies and conditions,
+# value transformations, and multi-line field definitions for complex calculations. Organization counters
+# are computed directly from request details (no separate statistics API). It employs multithreading with
+# configurable worker pools to parallelize request processing across the thread pool, significantly reducing
+# execution time. Results are exported as structured JSON files for easy integration with downstream analytics
+# tools. Built-in quality assurance includes comprehensive non-regression testing with configurable
+# Warning/Critical thresholds, and user confirmation prompts when critical issues are detected. Excel export
+# functionality enables generation of configurable Excel workbooks with data filtering, sorting, value
+# replacement, and formula recalculation. Key features include automatic token refresh handling, retry
+# mechanisms for transient API failures, progress tracking with real-time visual feedback, and support for
+# complex data extraction using JSON path expressions.
+import json
+import logging
+import msvcrt
+import os
+import re
+import sys
+import threading
+import traceback
+from collections import defaultdict
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from datetime import timedelta, datetime
+from time import perf_counter, sleep
+import functools
+
+import httpx
+import openpyxl
+import questionary
+from tqdm import tqdm
+from rich.console import Console
+
+# Import centralized constants (SINGLE SOURCE OF TRUTH)
+from do_dashboard_constants import (
+    REQUESTS_FILE_NAME,
+    ORGANIZATIONS_FILE_NAME,
+    OLD_FILE_SUFFIX,
+    DASHBOARD_CONFIG_FILE_NAME,
+    REQUESTS_MAPPING_TABLE_NAME,
+    ORGANIZATIONS_MAPPING_TABLE_NAME,
+    ORG_CENTER_MAPPING_FILE_NAME,
+    ORG_CENTER_MAPPING_TABLE_NAME,
+    DEFAULT_USER_NAME,
+    DEFAULT_PASSWORD,
+    IAM_URL,
+    GDD_URL,
+    GDD_APP_ID,
+    ERROR_MAX_RETRY,
+    WAIT_BEFORE_RETRY,
+    WAIT_BEFORE_NEW_BATCH_OF_RETRIES,
+    MAX_BATCHS_OF_RETRIES,
+    MAX_THREADS,
+    DO_FILTERS,
+    DO_WORKLIST_PAGE_SIZE,
+    BAR_N_FMT_WIDTH,
+    BAR_TOTAL_FMT_WIDTH,
+    BAR_TIME_WIDTH,
+    BAR_RATE_WIDTH,
+    LOG_FILE_NAME,
+    API_TIMEOUT,
+    API_AUTH_LOGIN_ENDPOINT,
+    API_AUTH_CONFIG_TOKEN_ENDPOINT,
+    API_AUTH_REFRESH_TOKEN_ENDPOINT,
+    API_DO_WORKLIST_ENDPOINT,
+    API_DO_REQUEST_DETAIL_ENDPOINT,
+    API_DO_PROFESSIONALS_ENDPOINT
+)
+
+# Import refactored modules
+from do_dashboard_utils import (
+    get_nested_value,
+    get_httpx_client,
+    clear_httpx_client,
+    get_thread_position,
+    get_config_path,
+    thread_local_storage,
+    run_with_context
+)
+from do_dashboard_quality_checks import (
+    backup_output_files,
+    run_quality_checks,
+    run_check_only_mode,
+    set_dependencies as quality_set_dependencies,
+    enable_debug_mode
+)
+from do_dashboard_excel_export import (
+    prepare_excel_export,
+    export_excel_only,
+    run_normal_mode_export,
+    set_dependencies as excel_set_dependencies
+)
+
+logging.basicConfig(level=logging.WARNING, format='%(asctime)s - %(levelname)s - %(message)s', filename=LOG_FILE_NAME,
+                    filemode='w')
+
+
+# ============================================================================
+# BLOCK 1: CONFIGURATION & BASE INFRASTRUCTURE
+# ============================================================================
+
+# NOTE: All constants are imported from do_dashboard_constants.py (SINGLE SOURCE OF TRUTH)
+
+# --- Global Variables ---
+access_token = ""
+refresh_token = ""
+threads_list = []
+_token_refresh_lock = threading.Lock()
+on_retry_exhausted = "ask"  # "ask" | "ignore" | "abort" — set at startup
+_stored_username = ""       # Credentials stored at login for automatic re-login
+_stored_password = ""
+_threads_list_lock = threading.Lock()
+global_pbar = None
+_global_pbar_lock = threading.Lock()
+_user_interaction_lock = threading.Lock()
+
+# Global variables (mutable, set at runtime - not constants)
+requests_mapping_config = []
+organizations_mapping_config = []
+excel_export_config = None
+excel_export_enabled = False
+
+subtasks_thread_pool = ThreadPoolExecutor(40)
+httpx_clients = {}
+console = Console()
+
+# Share global variables with utility modules (required for thread-safe operations)
+import do_dashboard_utils
+do_dashboard_utils.httpx_clients = httpx_clients
+do_dashboard_utils.threads_list = threads_list
+do_dashboard_utils._threads_list_lock = _threads_list_lock
+
+# Inject console instance to modules
+quality_set_dependencies(console)
+excel_set_dependencies(console)
+
+# Detect and enable debug mode if --debug flag is present (and remove it from argv)
+if "--debug" in sys.argv:
+    sys.argv.remove("--debug")
+    enable_debug_mode()
+
+# --- Progress Bar Configuration ---
+custom_bar_format = ("{l_bar}{bar}"
+                     f" {{n_fmt:>{BAR_N_FMT_WIDTH}}}/{{total_fmt:<{BAR_TOTAL_FMT_WIDTH}}} "
+                     f"[{{elapsed:<{BAR_TIME_WIDTH}}}<{{remaining:>{BAR_TIME_WIDTH}}}, "
+                     f"{{rate_fmt:>{BAR_RATE_WIDTH}}}]{{postfix}}")
+
+
+# ============================================================================
+# BLOCK 2: DECORATORS & RESILIENCE
+# ============================================================================
+
+def new_token():
+    """Refresh access token using the refresh token"""
+    global access_token, refresh_token
+    with _token_refresh_lock:
+        for attempt in range(ERROR_MAX_RETRY):
+            try:
+                client = get_httpx_client()
+                client.base_url = GDD_URL
+                response = client.post(API_AUTH_REFRESH_TOKEN_ENDPOINT,
+                                       headers={"Authorization": f"Bearer {access_token}"},
+                                       json={"refresh_token": refresh_token}, timeout=20)
+                response.raise_for_status()
+                access_token = response.json()["access_token"]
+                refresh_token = response.json()["refresh_token"]
+                return
+            except httpx.RequestError as exc:
+                logging.warning(f"Refresh Token Error (Attempt {attempt + 1}) : {exc}")
+                clear_httpx_client()
+            except httpx.HTTPStatusError as exc:
+                logging.warning(
+                    f"Refresh Token Error (Attempt {attempt + 1}) : {exc.response.status_code} for Url {exc.request.url}")
+                clear_httpx_client()
+            finally:
+                if attempt < ERROR_MAX_RETRY - 1:
+                    sleep(WAIT_BEFORE_RETRY)
+        # Refresh token exhausted — attempt full re-login with stored credentials
+        logging.warning("Refresh token exhausted. Attempting re-login with stored credentials.")
+        _do_login(_stored_username, _stored_password)
+        logging.info("Re-login successful. New tokens acquired.")
+
+
+def api_call_with_retry(func):
+    """Decorator for API calls with automatic retry and token refresh on 401 errors"""
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        func_name = func.__name__
+        total_attempts = 0
+        batch_count = 1
+
+        while True:
+            for attempt in range(ERROR_MAX_RETRY):
+                total_attempts += 1
+                try:
+                    return func(*args, **kwargs)
+                except (httpx.RequestError, httpx.HTTPStatusError) as exc:
+                    logging.warning(f"Error in {func_name} (Attempt {total_attempts}): {exc}")
+
+                    clear_httpx_client()
+
+                    if isinstance(exc, httpx.HTTPStatusError) and exc.response.status_code == 401:
+                        logging.info(f"Token expired for {func_name}. Refreshing token.")
+                        try:
+                            new_token()
+                        except (httpx.RequestError, httpx.HTTPStatusError) as token_exc:
+                            logging.warning(f"Token refresh/re-login failed for {func_name}: {token_exc}")
+
+                    if attempt < ERROR_MAX_RETRY - 1:
+                        sleep(WAIT_BEFORE_RETRY)
+                    else:
+                        if batch_count < MAX_BATCHS_OF_RETRIES:
+                            logging.warning(f"Batch {batch_count}/{MAX_BATCHS_OF_RETRIES} failed for {func_name}. "
+                                            f"Waiting {WAIT_BEFORE_NEW_BATCH_OF_RETRIES}s before automatic retry batch.")
+                            batch_count += 1
+                            sleep(WAIT_BEFORE_NEW_BATCH_OF_RETRIES)
+                            break
+                        else:
+                            with _user_interaction_lock:
+                                if on_retry_exhausted == "ignore":
+                                    ctx = getattr(thread_local_storage, "current_request_context", {"id": "Unknown"})
+                                    logging.warning(f"[AUTO-IGNORE] Skipping {func_name} for Request {ctx['id']}. Error: {exc}")
+                                    return None
+
+                                elif on_retry_exhausted == "abort":
+                                    logging.critical(f"[AUTO-ABORT] Stopping script after persistent error in {func_name}. Error: {exc}")
+                                    raise httpx.RequestError(message=f"Persistent error in {func_name} (auto-aborted)")
+
+                                else:  # "ask" — display error then interactive prompt
+                                    console.print(f"\n[bold red]Persistent error in {func_name} after {batch_count} batches ({total_attempts} attempts).[/bold red]")
+                                    console.print(f"[red]Exception: {exc}[/red]")
+
+                                    choice = questionary.select(
+                                        f"What would you like to do for {func_name}?",
+                                        choices=[
+                                            "Retry (try another batch of retries)",
+                                            "Ignore (return None and continue)",
+                                            "Stop script (critical error)"
+                                        ]
+                                    ).ask()
+
+                                    if choice == "Retry (try another batch of retries)":
+                                        logging.info(f"User chose to retry {func_name}. Restarting batch sequence.")
+                                        batch_count = 1
+                                        break
+                                    elif choice == "Ignore (return None and continue)":
+                                        ctx = getattr(thread_local_storage, "current_request_context", {"id": "Unknown"})
+                                        logging.warning(f"[IGNORE] User opted to skip {func_name} for Request {ctx['id']}. Error: {exc}")
+                                        return None
+                                    else:
+                                        logging.critical(f"User chose to stop script after persistent error in {func_name}.")
+                                        raise httpx.RequestError(message=f"Persistent error in {func_name} (stopped by user)")
+
+    return wrapper
+
+
+# ============================================================================
+# BLOCK 3: AUTHENTICATION
+# ============================================================================
+
+def _do_login(username, password):
+    """Performs the two-step authentication (IAM → GDD) with the given credentials.
+    Updates global access_token and refresh_token on success.
+    Raises httpx.RequestError or httpx.HTTPStatusError on failure.
+    Must NOT acquire _token_refresh_lock (caller's responsibility).
+    """
+    global access_token, refresh_token
+
+    # Step 1: IAM login
+    client = get_httpx_client()
+    client.base_url = IAM_URL
+    response = client.post(API_AUTH_LOGIN_ENDPOINT,
+                           json={"username": username, "password": password},
+                           timeout=20)
+    response.raise_for_status()
+    master_token = response.json()["access_token"]
+    user_id = response.json()["userId"]
+
+    # Step 2: GDD config-token
+    client = get_httpx_client()
+    client.base_url = GDD_URL
+    response = client.post(API_AUTH_CONFIG_TOKEN_ENDPOINT,
+                           headers={"Authorization": f"Bearer {master_token}"},
+                           json={"userId": user_id, "clientId": GDD_APP_ID,
+                                 "userAgent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/137.0.0.0 Safari/537.36"},
+                           timeout=20)
+    response.raise_for_status()
+    access_token = response.json()["access_token"]
+    refresh_token = response.json()["refresh_token"]
+
+
+def login():
+    global _stored_username, _stored_password
+
+    user_name = (questionary.text("login :", default=DEFAULT_USER_NAME).ask())
+    password = (questionary.password("password :", default=DEFAULT_PASSWORD).ask())
+    if not (user_name and password):
+        return "Exit"
+
+    try:
+        _do_login(user_name, password)
+    except httpx.RequestError as exc:
+        print(f"Login Error : {exc}")
+        logging.warning(f"Login Error : {exc}")
+        return "Error"
+    except httpx.HTTPStatusError as exc:
+        print(f"Login Error : {exc.response.status_code} for Url {exc.request.url}")
+        logging.warning(f"Login Error : {exc.response.status_code} for Url {exc.request.url}")
+        return "Error"
+
+    _stored_username = user_name
+    _stored_password = password
+    print()
+    print("Login Success")
+    return "Success"
+
+
+# ============================================================================
+# BLOCK 3B: STARTUP PARAMETERS & FILE UTILITIES
+# ============================================================================
+
+def ask_on_retry_exhausted():
+    """Asks the user what to do when all API retry batches are exhausted."""
+    global on_retry_exhausted
+    choice = questionary.select(
+        "On retry exhausted :",
+        choices=[
+            "Ask (interactive prompt)",
+            "Ignore (return None and continue)",
+            "Abort (stop script)"
+        ]
+    ).ask()
+
+    if choice is None or choice == "Ask (interactive prompt)":
+        on_retry_exhausted = "ask"
+    elif choice == "Ignore (return None and continue)":
+        on_retry_exhausted = "ignore"
+    else:
+        on_retry_exhausted = "abort"
+
+
+def wait_for_scheduled_launch():
+    """Asks the user when to start the processing and waits if needed.
+    Options: Immediately / In X minutes / At HH:MM
+    """
+    choice = questionary.select(
+        "When to start processing ?",
+        choices=["Immediately", "In X minutes", "At HH:MM"]
+    ).ask()
+
+    if choice is None or choice == "Immediately":
+        return
+
+    if choice == "In X minutes":
+        minutes_str = questionary.text(
+            "Number of minutes :",
+            validate=lambda x: x.isdigit() and int(x) > 0
+        ).ask()
+        if not minutes_str:
+            return
+        target_time = datetime.now() + timedelta(minutes=int(minutes_str))
+
+    else:  # "At HH:MM"
+        time_str = questionary.text(
+            "Start time (HH:MM) :",
+            validate=lambda x: bool(re.match(r'^\d{2}:\d{2}$', x)) and
+                               0 <= int(x.split(':')[0]) <= 23 and
+                               0 <= int(x.split(':')[1]) <= 59
+        ).ask()
+        if not time_str:
+            return
+        now = datetime.now()
+        h, m = int(time_str.split(':')[0]), int(time_str.split(':')[1])
+        target_time = now.replace(hour=h, minute=m, second=0, microsecond=0)
+        if target_time <= now:
+            console.print("[yellow]⚠ Specified time is already past. Starting immediately.[/yellow]")
+            return
+
+    print()
+    try:
+        while True:
+            remaining = target_time - datetime.now()
+            if remaining.total_seconds() <= 0:
+                break
+            total_secs = int(remaining.total_seconds())
+            h = total_secs // 3600
+            m = (total_secs % 3600) // 60
+            s = total_secs % 60
+            target_str = target_time.strftime('%H:%M:%S')
+            print(f"\r  Starting in {h:02d}:{m:02d}:{s:02d}... (at {target_str}) — Ctrl+C to cancel  ",
+                  end="", flush=True)
+            sleep(1)
+            while msvcrt.kbhit():
+                msvcrt.getwch()
+        print()
+        console.print("[green]✓ Starting processing.[/green]")
+    except KeyboardInterrupt:
+        print()
+        console.print("[bold red]Launch cancelled by user.[/bold red]")
+        raise SystemExit(0)
+
+
+def load_json_file(filename):
+    """Load a JSON file from disk. Returns parsed data or None on error."""
+    if os.path.exists(filename):
+        try:
+            with open(filename, 'r', encoding='utf-8') as f:
+                return json.load(f)
+        except Exception as e:
+            logging.warning(f"Could not load JSON file '{filename}': {e}")
+            console.print(f"[yellow]⚠ Warning: Could not load JSON file '{filename}': {e}[/yellow]")
+    return None
+
+
+# ============================================================================
+# BLOCK 4: CONFIGURATION LOADING
+# ============================================================================
+
+def load_requests_mapping_config():
+    """Loads and validates the requests mapping configuration from the Excel file."""
+    global requests_mapping_config
+    config_path = os.path.join(get_config_path(), DASHBOARD_CONFIG_FILE_NAME)
+
+    try:
+        workbook = openpyxl.load_workbook(config_path, data_only=True)
+    except FileNotFoundError:
+        error_msg = f"Error: Configuration file not found at: {config_path}"
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    if REQUESTS_MAPPING_TABLE_NAME not in workbook.sheetnames:
+        error_msg = f"Error: Sheet '{REQUESTS_MAPPING_TABLE_NAME}' not found in the configuration file."
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    sheet = workbook[REQUESTS_MAPPING_TABLE_NAME]
+    headers = [cell.value for cell in sheet[1]]
+
+    temp_config = []
+
+    for row_index, row in enumerate(sheet.iter_rows(min_row=2, values_only=True), start=2):
+        field_config = dict(zip(headers, row))
+
+        if field_config.get("source_name") == "Not Specified":
+            continue
+
+        field_name = field_config.get("field_name")
+        if not field_name or not isinstance(field_name, str):
+            error_msg = f"Error in config file, row {row_index}: 'field_name' is mandatory."
+            logging.critical(error_msg)
+            console.print(f"[bold red]{error_msg}[/bold red]")
+            raise Exception(error_msg)
+        field_config["field_name"] = re.sub(r'\s*\([^)]*\)$', '', field_name).strip()
+
+        # Parse source_id prefix
+        source_id_raw = field_config.get("source_id", "")
+        if source_id_raw and isinstance(source_id_raw, str):
+            if source_id_raw.startswith("q_id="):
+                field_config["source_type"] = "q_id"
+                field_config["source_value"] = source_id_raw[5:]
+            elif source_id_raw.startswith("q_name="):
+                field_config["source_type"] = "q_name"
+                field_config["source_value"] = source_id_raw[7:]
+            elif source_id_raw.startswith("q_category="):
+                field_config["source_type"] = "q_category"
+                field_config["source_value"] = source_id_raw[11:]
+            elif source_id_raw == "record":
+                field_config["source_type"] = "record"
+                field_config["source_value"] = None
+            elif source_id_raw == "request":
+                field_config["source_type"] = "request"
+                field_config["source_value"] = None
+            else:
+                field_config["source_type"] = None
+                field_config["source_value"] = source_id_raw
+        else:
+            field_config["source_type"] = None
+            field_config["source_value"] = None
+
+        for json_field in ["field_path", "field_condition", "true_if_any", "value_labels"]:
+            value = field_config.get(json_field)
+            if value:
+                if not isinstance(value, str):
+                    error_msg = f"Error in config file, row {row_index}, field '{json_field}': Invalid value, must be a JSON string."
+                    logging.critical(error_msg)
+                    console.print(f"[bold red]{error_msg}[/bold red]")
+                    raise Exception(error_msg)
+                try:
+                    field_config[json_field] = json.loads(value)
+                except json.JSONDecodeError:
+                    error_msg = f"Error in config file, row {row_index}, field '{json_field}': Invalid JSON format."
+                    logging.critical(error_msg)
+                    console.print(f"[bold red]{error_msg}[/bold red]")
+                    raise Exception(error_msg)
+            else:
+                field_config[json_field] = None
+
+        if not field_config.get("field_path"):
+            error_msg = f"Error in config file, row {row_index}: 'field_path' is mandatory when a field is specified."
+            logging.critical(error_msg)
+            console.print(f"[bold red]{error_msg}[/bold red]")
+            raise Exception(error_msg)
+
+        temp_config.append(field_config)
+
+    requests_mapping_config = temp_config
+    console.print(f"Loaded {len(requests_mapping_config)} fields from requests mapping configuration.", style="green")
+
+
+def load_organizations_mapping_config():
+    """Loads and validates the organizations mapping configuration from the Excel file."""
+    global organizations_mapping_config
+    config_path = os.path.join(get_config_path(), DASHBOARD_CONFIG_FILE_NAME)
+
+    try:
+        workbook = openpyxl.load_workbook(config_path, data_only=True)
+    except FileNotFoundError:
+        error_msg = f"Error: Configuration file not found at: {config_path}"
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    if ORGANIZATIONS_MAPPING_TABLE_NAME not in workbook.sheetnames:
+        logging.info(f"Sheet '{ORGANIZATIONS_MAPPING_TABLE_NAME}' not found. Organizations mapping is optional.")
+        organizations_mapping_config = []
+        return
+
+    sheet = workbook[ORGANIZATIONS_MAPPING_TABLE_NAME]
+    headers = [cell.value for cell in sheet[1]]
+    headers_filtered = [h for h in headers if h is not None]
+
+    mapping_config = []
+    try:
+        for row in sheet.iter_rows(min_row=2, values_only=True):
+            if all(cell is None for cell in row):
+                break
+            row_filtered = row[:len(headers_filtered)]
+            config_dict = dict(zip(headers_filtered, row_filtered))
+            mapping_config.append(config_dict)
+    except Exception as e:
+        error_msg = f"Error parsing organizations mapping: {e}"
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+    finally:
+        workbook.close()
+
+    organizations_mapping_config = mapping_config
+    if mapping_config:
+        console.print(f"Loaded {len(organizations_mapping_config)} organizations from organizations mapping configuration.", style="green")
+    else:
+        console.print("No organizations mapping found (this is optional).", style="yellow")
+
+
+def load_do_filters_config():
+    """
+    Loads the DO filters from the Named Range 'DO_Filters' in the config Excel file.
+    The Named Range contains a JSON string representing the filters object for the worklist API.
+
+    Returns:
+        dict: Filters object (e.g. {"status": "all-admin", "study": "ENDOLIFE"})
+
+    Raises:
+        Exception: If the Named Range is not found or the value is not valid JSON.
+    """
+    config_path = os.path.join(get_config_path(), DASHBOARD_CONFIG_FILE_NAME)
+
+    try:
+        workbook = openpyxl.load_workbook(config_path, data_only=True)
+    except FileNotFoundError:
+        error_msg = f"Error: Configuration file not found at: {config_path}"
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    if DO_FILTERS not in workbook.defined_names:
+        error_msg = f"Error: Named range '{DO_FILTERS}' not found in configuration file."
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    try:
+        named_range = workbook.defined_names[DO_FILTERS]
+        destinations = list(named_range.destinations)
+        if not destinations:
+            raise ValueError("Named range has no destinations")
+        sheet_name, cell_ref = destinations[0]
+        # Remove absolute reference markers ($) for cell access
+        cell_ref_clean = cell_ref.replace('$', '')
+        sheet = workbook[sheet_name]
+        cell_value = sheet[cell_ref_clean].value
+    except Exception as e:
+        error_msg = f"Error reading Named Range '{DO_FILTERS}': {e}"
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+    finally:
+        workbook.close()
+
+    if not cell_value or not isinstance(cell_value, str):
+        error_msg = f"Error: Named range '{DO_FILTERS}' is empty or not a string."
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    try:
+        filters = json.loads(cell_value)
+    except json.JSONDecodeError as e:
+        error_msg = f"Error: Named range '{DO_FILTERS}' does not contain valid JSON: {e}"
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    console.print(f"Loaded DO filters: {filters}", style="green")
+    return filters
+
+
+# ============================================================================
+# BLOCK 5: DATA SEARCH & EXTRACTION
+# ============================================================================
+
+def get_value_from_request(output_request, key):
+    """Helper to find a key in the nested output_request structure (groups → fields)."""
+    for group in output_request.values():
+        if isinstance(group, dict) and key in group:
+            return group[key]
+    return None
+
+
+# ============================================================================
+# BLOCK 6: CUSTOM FUNCTIONS & FIELD PROCESSING
+# ============================================================================
+
+def _execute_custom_function(function_name, args, output_request):
+    """Executes a custom function for a calculated field."""
+    if function_name == "search_in_fields_using_regex":
+        if not args or len(args) < 2:
+            return "$$$$ Argument Error: search_in_fields_using_regex requires at least 2 arguments"
+
+        regex_pattern = args[0]
+        field_names = args[1:]
+
+        field_values = []
+        all_undefined = True
+
+        for field_name in field_names:
+            value = get_value_from_request(output_request, field_name)
+            field_values.append(value)
+            if value is not None and value != "undefined":
+                all_undefined = False
+
+        if all_undefined:
+            return "undefined"
+
+        try:
+            for value in field_values:
+                if isinstance(value, str) and re.search(regex_pattern, value, re.IGNORECASE):
+                    return True
+        except re.error as e:
+            return f"$$$$ Regex Error: {e}"
+
+        return False
+
+    elif function_name == "extract_parentheses_content":
+        if not args or len(args) != 1:
+            return "$$$$ Argument Error: extract_parentheses_content requires 1 argument"
+
+        field_name = args[0]
+        value = get_value_from_request(output_request, field_name)
+
+        if value is None or value == "undefined":
+            return "undefined"
+
+        match = re.search(r'\((.*?)\)', str(value))
+        return match.group(1) if match else "undefined"
+
+    elif function_name == "append_terminated_suffix":
+        if not args or len(args) != 2:
+            return "$$$$ Argument Error: append_terminated_suffix requires 2 arguments"
+
+        status = get_value_from_request(output_request, args[0])
+        is_terminated = get_value_from_request(output_request, args[1])
+
+        if status is None or status == "undefined":
+            return "undefined"
+
+        if not isinstance(is_terminated, bool) or not is_terminated:
+            return status
+
+        return f"{status} - AP"
+
+    elif function_name == "if_then_else":
+        if not args or len(args) < 4:
+            return "$$$$ Argument Error: if_then_else requires at least 4 arguments"
+
+        operator = args[0]
+
+        def resolve_value(arg):
+            if isinstance(arg, bool):
+                return arg
+            if isinstance(arg, (int, float)):
+                return arg
+            if isinstance(arg, str) and arg.startswith("$"):
+                return arg[1:]
+            return get_value_from_request(output_request, arg)
+
+        if operator == "is_true":
+            if len(args) != 4:
+                return "$$$$ Argument Error: is_true requires 4 arguments"
+            value = resolve_value(args[1])
+            if value is None or value == "undefined":
+                return "undefined"
+            condition = (value is True)
+            result_if_true = resolve_value(args[2])
+            result_if_false = resolve_value(args[3])
+
+        elif operator == "is_false":
+            if len(args) != 4:
+                return "$$$$ Argument Error: is_false requires 4 arguments"
+            value = resolve_value(args[1])
+            if value is None or value == "undefined":
+                return "undefined"
+            condition = (value is False)
+            result_if_true = resolve_value(args[2])
+            result_if_false = resolve_value(args[3])
+
+        elif operator == "all_true":
+            if len(args) != 4:
+                return "$$$$ Argument Error: all_true requires 4 arguments"
+            fields_arg = args[1]
+            if not isinstance(fields_arg, list):
+                return "$$$$ Argument Error: all_true requires arg1 to be a list of field names"
+
+            conditions = []
+            for field_name in fields_arg:
+                field_value = get_value_from_request(output_request, field_name)
+                if field_value is None or field_value == "undefined":
+                    return "undefined"
+                conditions.append(field_value)
+
+            condition = all(conditions)
+            result_if_true = resolve_value(args[2])
+            result_if_false = resolve_value(args[3])
+
+        elif operator == "is_defined":
+            if len(args) != 4:
+                return "$$$$ Argument Error: is_defined requires 4 arguments"
+            value = resolve_value(args[1])
+            condition = (value is not None and value != "undefined")
+            result_if_true = resolve_value(args[2])
+            result_if_false = resolve_value(args[3])
+
+        elif operator == "is_undefined":
+            if len(args) != 4:
+                return "$$$$ Argument Error: is_undefined requires 4 arguments"
+            value = resolve_value(args[1])
+            condition = (value is None or value == "undefined")
+            result_if_true = resolve_value(args[2])
+            result_if_false = resolve_value(args[3])
+
+        elif operator == "all_defined":
+            if len(args) != 4:
+                return "$$$$ Argument Error: all_defined requires 4 arguments"
+            fields_arg = args[1]
+            if not isinstance(fields_arg, list):
+                return "$$$$ Argument Error: all_defined requires arg1 to be a list of field names"
+
+            for field_name in fields_arg:
+                field_value = get_value_from_request(output_request, field_name)
+                if field_value is None or field_value == "undefined":
+                    condition = False
+                    break
+            else:
+                condition = True
+
+            result_if_true = resolve_value(args[2])
+            result_if_false = resolve_value(args[3])
+
+        elif operator == "==":
+            if len(args) != 5:
+                return "$$$$ Argument Error: == requires 5 arguments"
+            value1 = resolve_value(args[1])
+            value2 = resolve_value(args[2])
+
+            if value1 is None or value1 == "undefined" or value2 is None or value2 == "undefined":
+                return "undefined"
+
+            condition = (value1 == value2)
+            result_if_true = resolve_value(args[3])
+            result_if_false = resolve_value(args[4])
+
+        elif operator == "!=":
+            if len(args) != 5:
+                return "$$$$ Argument Error: != requires 5 arguments"
+            value1 = resolve_value(args[1])
+            value2 = resolve_value(args[2])
+
+            if value1 is None or value1 == "undefined" or value2 is None or value2 == "undefined":
+                return "undefined"
+
+            condition = (value1 != value2)
+            result_if_true = resolve_value(args[3])
+            result_if_false = resolve_value(args[4])
+
+        else:
+            return f"$$$$ Unknown Operator: {operator}"
+
+        return result_if_true if condition else result_if_false
+
+    elif function_name == "extract_value_from_array":
+        # Args: [array_field_name, key_path, search_value, value_path]
+        #   array_field_name : name of an already-computed field in output_request containing the array
+        #   key_path         : relative path (list) to the key attribute within each array item
+        #   search_value     : JSON value to match against (string, number, bool, object...)
+        #   value_path       : relative path (list) to the value to extract from the matched item
+        if not args or len(args) != 4:
+            return "$$$$ Argument Error: extract_value_from_array requires 4 arguments"
+
+        array_field_name, key_path, search_value, value_path = args
+
+        if not isinstance(key_path, list):
+            return "$$$$ Argument Error: extract_value_from_array key_path (arg2) must be a list"
+        if not isinstance(value_path, list):
+            return "$$$$ Argument Error: extract_value_from_array value_path (arg4) must be a list"
+
+        array = get_value_from_request(output_request, array_field_name)
+
+        if array is None or array == "undefined":
+            return "undefined"
+        if not isinstance(array, list):
+            return "$$$$ Format Error : Array expected"
+
+        for item in array:
+            if get_nested_value(item, key_path) == search_value:
+                return get_nested_value(item, value_path, default="undefined")
+
+        return "undefined"
+
+    return f"$$$$ Unknown Custom Function: {function_name}"
+
+
+def process_requests_mapping(output_request, request_data):
+    """Processes and adds the requests mapping fields to the output request dictionary."""
+    for field in requests_mapping_config:
+        field_name = field["field_name"]
+        field_group = field.get("field_group", "Extended_Fields")
+        final_value = "undefined"
+
+        # Check condition
+        condition_field_name = field.get("field_condition")
+        if condition_field_name:
+            condition_value = get_value_from_request(output_request, condition_field_name)
+
+            if condition_value is None or condition_value == "undefined":
+                final_value = "undefined"
+            elif not isinstance(condition_value, bool):
+                final_value = "$$$$ Condition Field Error"
+            elif not condition_value:
+                final_value = "N/A"
+
+        # If condition allows, process the field
+        if final_value == "undefined":
+            source_name = field.get("source_name")
+            source_type = field.get("source_type")
+            field_path = field.get("field_path")
+
+            # Get raw value from appropriate source
+            if source_name == "Calculated":
+                function_name = field.get("source_id")
+                args = field_path
+                final_value = _execute_custom_function(function_name, args, output_request)
+            elif source_type == "request":
+                final_value = get_nested_value(request_data, field_path, default="undefined")
+            else:
+                # source types not used in DO (q_id, q_name, q_category, record, etc.)
+                # return undefined to allow future extensibility
+                final_value = "undefined"
+
+            # If the source data itself is missing, log a warning but continue
+            if final_value == "$$$$ No Data":
+                request_id = request_data.get("id", "Unknown") if isinstance(request_data, dict) else "Unknown"
+                logging.warning(f"No '{source_type}' data source found for Request {request_id} (Field: {field_name})")
+                final_value = "undefined"
+
+            # Post-processing: Apply true_if_any and value_labels transformations
+            if final_value not in ["undefined", "$$$$ No Data"]:
+                check_values = field.get("true_if_any")
+                if check_values:
+                    raw_value_set = set(final_value if isinstance(final_value, list) else [final_value])
+                    check_values_set = set(check_values if isinstance(check_values, list) else [check_values])
+                    final_value = not raw_value_set.isdisjoint(check_values_set)
+
+                value_labels = field.get("value_labels")
+                if value_labels and final_value not in ["$$$$ Format Error : Array expected"]:
+                    found = False
+                    for label_map in value_labels:
+                        if label_map.get("value") == final_value:
+                            final_value = get_nested_value(label_map, ["text", "fr"], default=f"$$$$ Value Error : {final_value}")
+                            found = True
+                            break
+                    if not found:
+                        final_value = f"$$$$ Value Error : {final_value}"
+
+        # Post-processing: If the value is a list, join it with a pipe
+        if isinstance(final_value, list):
+            final_value = "|".join(map(str, final_value))
+
+        # Post-processing: Format score dictionaries
+        if isinstance(final_value, dict) and 'total' in final_value and 'max' in final_value:
+            final_value = f"{final_value['total']}/{final_value['max']}"
+
+        # Post-processing: Apply field template
+        field_template = field.get("field_template")
+        if field_template and final_value not in ["undefined", "N/A"] and isinstance(final_value, (str, int, float, bool)):
+            final_value = field_template.replace("$value", str(final_value))
+
+        if field_group not in output_request:
+            output_request[field_group] = {}
+        output_request[field_group][field_name] = final_value
+
+
+# ============================================================================
+# BLOCK 7: BUSINESS API CALLS
+# ============================================================================
+
+@api_call_with_retry
+def get_worklist_page(filters, page, page_size):
+    """Fetches one page of the diagnostic order worklist."""
+    client = get_httpx_client()
+    client.base_url = GDD_URL
+    response = client.post(
+        API_DO_WORKLIST_ENDPOINT,
+        headers={"Authorization": f"Bearer {access_token}"},
+        json={
+            "lang": "fr-FR",
+            "filters": filters,
+            "limit": page_size,
+            "page": page,
+            "sort": []
+        },
+        timeout=API_TIMEOUT
+    )
+    response.raise_for_status()
+    return response.json()
+
+
+@api_call_with_retry
+def get_request_detail_by_id(request_id):
+    """Fetches the full validation detail for a single request."""
+    client = get_httpx_client()
+    client.base_url = GDD_URL
+    response = client.get(
+        f"{API_DO_REQUEST_DETAIL_ENDPOINT}/{request_id}/validation",
+        headers={"Authorization": f"Bearer {access_token}"},
+        timeout=API_TIMEOUT
+    )
+    response.raise_for_status()
+    return response.json()
+
+
+@api_call_with_retry
+def get_professionals(ids):
+    """
+    Fetches professional display names for a list of IDs (prescriber / requester).
+    IDs are deduplicated before the call. Results are matched by ID for robustness.
+
+    Returns:
+        dict: {professional_id: display_name}
+    """
+    if not ids:
+        return {}
+    client = get_httpx_client()
+    client.base_url = GDD_URL
+    response = client.post(
+        API_DO_PROFESSIONALS_ENDPOINT,
+        headers={"Authorization": f"Bearer {access_token}"},
+        json={"ids": ids},
+        timeout=API_TIMEOUT
+    )
+    response.raise_for_status()
+    data = response.json().get("data", [])
+
+    result = {}
+    for pro in data:
+        pro_id = get_nested_value(pro, ["metadata", "id"])
+        display = pro.get("display")
+        if pro_id:
+            result[pro_id] = display
+    return result
+
+
+# ============================================================================
+# BLOCK 7b: ORGANIZATION CENTER MAPPING
+# ============================================================================
+
+def load_organization_center_mapping():
+    """
+    Loads organization ↔ center mapping from Excel file in script directory.
+
+    Returns:
+        dict: {organization_name_normalized: center_name} or {} if error/skip
+    """
+    mapping_file = ORG_CENTER_MAPPING_FILE_NAME
+
+    if not os.path.exists(mapping_file):
+        console.print(f"[yellow]⚠ Mapping file not found at: {mapping_file}. Skipping center mapping.[/yellow]")
+        return {}
+
+    try:
+        workbook = openpyxl.load_workbook(mapping_file)
+    except Exception as e:
+        console.print(f"[yellow]⚠ Error loading mapping file: {e}. Skipping center mapping.[/yellow]")
+        logging.warning(f"Error loading mapping file: {e}")
+        return {}
+
+    if ORG_CENTER_MAPPING_TABLE_NAME not in workbook.sheetnames:
+        console.print(f"[yellow]⚠ Sheet '{ORG_CENTER_MAPPING_TABLE_NAME}' not found in mapping file. Skipping center mapping.[/yellow]")
+        return {}
+
+    sheet = workbook[ORG_CENTER_MAPPING_TABLE_NAME]
+    headers = [cell.value for cell in sheet[1]]
+
+    if "Organization_Name" not in headers or "Center_Name" not in headers:
+        console.print(f"[yellow]⚠ Required columns 'Organization_Name' or 'Center_Name' not found in mapping file. Skipping center mapping.[/yellow]")
+        return {}
+
+    mapping_rows = []
+    try:
+        for row in sheet.iter_rows(min_row=2, values_only=True):
+            if all(cell is None for cell in row):
+                continue
+            row_dict = dict(zip(headers, row))
+            org_name = row_dict.get("Organization_Name")
+            center_name = row_dict.get("Center_Name")
+            if org_name and center_name:
+                mapping_rows.append({"Organization_Name": org_name, "Center_Name": center_name})
+    except Exception as e:
+        console.print(f"[yellow]⚠ Error reading mapping file rows: {e}. Skipping center mapping.[/yellow]")
+        logging.warning(f"Error reading mapping file rows: {e}")
+        return {}
+
+    # Validate: check for duplicates on normalized versions
+    org_names_normalized = {}
+    center_names_normalized = {}
+
+    for row in mapping_rows:
+        org_name_raw = row["Organization_Name"]
+        center_name_raw = row["Center_Name"]
+
+        org_normalized = org_name_raw.strip().lower() if isinstance(org_name_raw, str) else str(org_name_raw).strip().lower()
+        center_normalized = center_name_raw.strip().lower() if isinstance(center_name_raw, str) else str(center_name_raw).strip().lower()
+
+        if org_normalized in org_names_normalized:
+            console.print(f"[yellow]⚠ Duplicate found in Organization_Name: '{org_name_raw}'. Skipping center mapping.[/yellow]")
+            return {}
+
+        if center_normalized in center_names_normalized:
+            console.print(f"[yellow]⚠ Duplicate found in Center_Name: '{center_name_raw}'. Skipping center mapping.[/yellow]")
+            return {}
+
+        org_names_normalized[org_normalized] = org_name_raw
+        center_names_normalized[center_normalized] = center_name_raw
+
+    # Build mapping dict
+    mapping_dict = {}
+    for row in mapping_rows:
+        org_name_raw = row["Organization_Name"]
+        center_name_raw = row["Center_Name"]
+        org_normalized = org_name_raw.strip().lower() if isinstance(org_name_raw, str) else str(org_name_raw).strip().lower()
+        center_clean = center_name_raw.strip() if isinstance(center_name_raw, str) else str(center_name_raw).strip()
+        mapping_dict[org_normalized] = center_clean
+
+    return mapping_dict
+
+
+# ============================================================================
+# BLOCK 8: REQUEST PROCESSING
+# ============================================================================
+
+def _process_single_request(worklist_request, mapping_dict):
+    """
+    Processes a single request from the worklist:
+    1. Fetches full request detail
+    2. Fetches prescriber and requester names (deduplicated single API call)
+    3. Injects enrichment data (names, identity fields, center name, status override)
+    4. Applies requests mapping to produce the output object
+
+    Args:
+        worklist_request: Request object from the worklist (root-level fields available)
+        mapping_dict: Organization → center name mapping dict
+
+    Returns:
+        Tuple of (output_request, request_meta) where request_meta contains
+        raw fields needed for organization building and sorting.
+    """
+    request_id = worklist_request.get("id")
+
+    # Set thread-local context for detailed error logging in decorators
+    ctx = {"id": request_id}
+    thread_local_storage.current_request_context = ctx
+
+    # --- 1. Fetch request detail ---
+    request_detail = get_request_detail_by_id(request_id)
+    if request_detail is None:
+        request_detail = {}
+
+    # --- 2. Fetch professional names (prescriber + requester, deduplicated) ---
+    prescriber_id = worklist_request.get("prescriber")
+    requester_id = worklist_request.get("requester")
+
+    # Deduplicate IDs before API call
+    unique_ids = list({pid for pid in [prescriber_id, requester_id] if pid})
+    professionals = get_professionals(unique_ids) if unique_ids else {}
+
+    # Inject professional names (None if not found)
+    request_detail["prescriberName"] = professionals.get(prescriber_id) if prescriber_id else None
+    request_detail["requesterName"] = professionals.get(requester_id) if requester_id else None
+
+    # --- 3. Inject patient identity fields from worklist ---
+    identity = worklist_request.get("identity") or {}
+    request_detail["lastname"] = identity.get("lastname")
+    request_detail["firstname"] = identity.get("firstname")
+    request_detail["birthday"] = identity.get("birthday")
+
+    # --- 4. Status override: diagnostic_status takes precedence if defined ---
+    diagnostic_status = request_detail.get("diagnostic_status")
+    if diagnostic_status is not None and diagnostic_status != "":
+        request_detail["status"] = diagnostic_status
+
+    # --- 5. Center mapping: inject Center_Name from labeledOrganization ---
+    labeled_org = worklist_request.get("labeledOrganization")
+    if labeled_org:
+        org_normalized = labeled_org.strip().lower()
+        request_detail["Center_Name"] = mapping_dict.get(org_normalized, labeled_org)
+    else:
+        request_detail["Center_Name"] = None
+
+    # Also inject organization and labeledOrganization for mapping access
+    request_detail["organization"] = worklist_request.get("organization")
+    request_detail["labeledOrganization"] = labeled_org
+
+    # --- 6. Apply requests mapping to produce output object ---
+    output_request = {}
+    process_requests_mapping(output_request, request_detail)
+
+    # --- 7. Build meta for organization building and sorting ---
+    request_meta = {
+        "org_id": worklist_request.get("organization"),
+        "org_name": labeled_org,
+        "center_name": request_detail.get("Center_Name"),
+        "status": request_detail.get("status"),
+        "diagnostic_result": request_detail.get("diagnostic_result"),
+        "lastname": request_detail.get("lastname"),
+        "firstname": request_detail.get("firstname"),
+        "id": request_id
+    }
+
+    return output_request, request_meta
+
+
+# ============================================================================
+# BLOCK 9: ORGANIZATIONS BUILDING
+# ============================================================================
+
+def build_organizations(request_metas):
+    """
+    Builds the organizations summary list from collected request metadata.
+
+    Each organization entry contains the organization identity and counters
+    derived from the status and diagnostic_result of its requests.
+
+    Args:
+        request_metas: List of request_meta dicts (from _process_single_request)
+
+    Returns:
+        List of organization dicts, sorted by center_name then id
+    """
+    org_map = {}
+
+    for meta in request_metas:
+        org_id = meta.get("org_id")
+        if not org_id:
+            continue
+
+        if org_id not in org_map:
+            org_map[org_id] = {
+                "id": org_id,
+                "name": meta.get("org_name"),
+                "center_name": meta.get("center_name"),
+                "total_count": 0,
+                "sent_count": 0,          # status == "active"
+                "accepted_count": 0,       # status == "accepted"
+                "rejected_count": 0,       # status == "rejected"
+                "sequencing_count": 0,     # status == "waiting"
+                "ai_count": 0,             # status == "in progress"
+                "result_available_count": 0,  # status == "finished"
+                "report_available_count": 0,  # status == "signed"
+                "positive_count": 0,          # diagnostic_result == "POSITIVE"
+                "negative_count": 0,          # diagnostic_result == "NEGATIVE"
+                "uninterpretable_count": 0    # diagnostic_result == "UNINTERPRETABLE"
+            }
+
+        org = org_map[org_id]
+        org["total_count"] += 1
+
+        status = meta.get("status")
+        if status == "active":
+            org["sent_count"] += 1
+        elif status == "accepted":
+            org["accepted_count"] += 1
+        elif status == "rejected":
+            org["rejected_count"] += 1
+        elif status == "waiting":
+            org["sequencing_count"] += 1
+        elif status == "in progress":
+            org["ai_count"] += 1
+        elif status == "finished":
+            org["result_available_count"] += 1
+        elif status == "signed":
+            org["report_available_count"] += 1
+
+        diagnostic_result = meta.get("diagnostic_result")
+        if diagnostic_result == "POSITIVE":
+            org["positive_count"] += 1
+        elif diagnostic_result == "NEGATIVE":
+            org["negative_count"] += 1
+        elif diagnostic_result == "UNINTERPRETABLE":
+            org["uninterpretable_count"] += 1
+
+    organizations = list(org_map.values())
+    organizations.sort(key=lambda o: (o.get("center_name") or "", o.get("id") or ""))
+    return organizations
+
+
+# ============================================================================
+# BLOCK 10: MAIN EXECUTION
+# ============================================================================
+
+def main():
+    global global_pbar, excel_export_config, excel_export_enabled
+
+    # --- Check for CLI Check_Only mode ---
+    check_only_mode = "--check-only" in sys.argv
+
+    if check_only_mode:
+        run_check_only_mode(sys.argv)
+        return
+
+    # --- Check for CLI Excel_Only mode ---
+    excel_only_mode = "--excel-only" in sys.argv
+
+    if excel_only_mode:
+        print()
+        load_requests_mapping_config()
+        load_organizations_mapping_config()
+
+        export_excel_only(sys.argv, REQUESTS_FILE_NAME, ORGANIZATIONS_FILE_NAME,
+                         requests_mapping_config, organizations_mapping_config)
+        return
+
+    # === NORMAL MODE: Full data collection ===
+
+    print()
+    login_status = login()
+
+    while login_status == "Error":
+        login_status = login()
+    if login_status == "Exit":
+        return
+
+    print()
+    number_of_threads = int((questionary.text("Number of threads :", default="12",
+                                              validate=lambda x: x.isdigit() and 0 < int(x) <= MAX_THREADS).ask()))
+
+    print()
+    ask_on_retry_exhausted()
+
+    print()
+    wait_for_scheduled_launch()
+
+    print()
+    load_requests_mapping_config()
+    load_organizations_mapping_config()
+
+    # Load DO filters from config
+    print()
+    do_filters = load_do_filters_config()
+
+    # Load and validate Excel export configuration
+    print()
+    console.print("[bold cyan]Loading Excel export configuration...[/bold cyan]")
+
+    excel_export_config, has_config_critical, _ = \
+        prepare_excel_export(requests_mapping_config, organizations_mapping_config)
+
+    if has_config_critical:
+        print()
+        answer = questionary.confirm(
+            "⚠ Critical configuration errors detected. Continue anyway?",
+            default=False
+        ).ask()
+        if not answer:
+            console.print("[bold red]Aborted by user[/bold red]")
+            return
+        else:
+            excel_export_enabled = False
+    else:
+        excel_export_enabled = True if excel_export_config else False
+
+    # Load center mapping
+    print()
+    print("Loading organization center mapping...")
+    mapping_dict = load_organization_center_mapping()
+
+    # === FETCH WORKLIST (paginated) ===
+    print()
+    start_time = perf_counter()
+
+    with console.status("[bold green]Fetching worklist (page 1)...", spinner="dots"):
+        first_page = get_worklist_page(do_filters, 1, DO_WORKLIST_PAGE_SIZE)
+
+    metadata = first_page.get("metadata", {})
+    total_requests = metadata.get("total", 0)
+    total_pages = metadata.get("pages", 1)
+
+    print(f"{total_requests} requests across {total_pages} pages...")
+    print()
+
+    # === SUBMIT ALL REQUESTS TO THREAD POOL AS PAGES ARRIVE ===
+    all_futures = []
+
+    with ThreadPoolExecutor(max_workers=number_of_threads) as thread_pool:
+
+        # Progress bar 1: page fetching
+        with tqdm(total=total_pages, unit="page",
+                  desc=f"{'Fetching pages':<52}",
+                  position=0, leave=True,
+                  bar_format=custom_bar_format) as pages_pbar:
+
+            # Submit first page requests
+            for worklist_request in first_page.get("data", []):
+                f = thread_pool.submit(run_with_context, _process_single_request,
+                                       {"id": worklist_request.get("id")},
+                                       worklist_request, mapping_dict)
+                all_futures.append(f)
+            pages_pbar.update(1)
+
+            # Fetch and submit remaining pages
+            for page_num in range(2, total_pages + 1):
+                page_data = get_worklist_page(do_filters, page_num, DO_WORKLIST_PAGE_SIZE)
+                for worklist_request in page_data.get("data", []):
+                    f = thread_pool.submit(run_with_context, _process_single_request,
+                                           {"id": worklist_request.get("id")},
+                                           worklist_request, mapping_dict)
+                    all_futures.append(f)
+                pages_pbar.update(1)
+
+        print()
+
+        # Progress bar 2: request processing
+        all_results = []  # list of (output_request, request_meta)
+
+        with tqdm(total=total_requests, unit="req.",
+                  desc=f"{'Processing requests':<52}",
+                  position=0, leave=True,
+                  bar_format=custom_bar_format) as processing_pbar:
+
+            global_pbar = processing_pbar
+
+            for future in as_completed(all_futures):
+                try:
+                    result = future.result()
+                    all_results.append(result)
+                except Exception as exc:
+                    logging.critical(f"Critical exception in request worker: {exc}", exc_info=True)
+                    print(f"\nCRITICAL ERROR in request processing thread:")
+                    print(f"Exception: {exc}")
+                    traceback.print_exc()
+                    thread_pool.shutdown(wait=False, cancel_futures=True)
+                    raise
+                finally:
+                    with _global_pbar_lock:
+                        if global_pbar:
+                            global_pbar.update(1)
+
+    # === SORT RESULTS ===
+    print()
+    print()
+    print("Sorting results...")
+
+    all_results.sort(key=lambda x: (
+        x[1].get("lastname") or "",
+        x[1].get("firstname") or "",
+        x[1].get("id") or ""
+    ))
+
+    output_requests = [r[0] for r in all_results]
+    request_metas = [r[1] for r in all_results]
+
+    # === BUILD ORGANIZATIONS ===
+    print("Building organizations summary...")
+    organizations_list = build_organizations(request_metas)
+
+    try:
+        # === QUALITY CHECKS ===
+        print()
+        has_regression_critical = run_quality_checks(
+            current_requests=output_requests,
+            old_requests_filename=REQUESTS_FILE_NAME
+        )
+
+        # === CHECK FOR CRITICAL ISSUES AND ASK USER CONFIRMATION ===
+        if has_regression_critical:
+            print()
+            console.print("[bold red]⚠ CRITICAL issues detected in quality checks![/bold red]")
+            confirm_write = questionary.confirm(
+                "Do you want to write the results anyway?",
+                default=True
+            ).ask()
+
+            if not confirm_write:
+                console.print("[yellow]✗ Output writing cancelled by user. Files were not modified.[/yellow]")
+                console.print("[yellow]  You can re-run the script to try again.[/yellow]")
+                print()
+                print(f"Elapsed time : {str(timedelta(seconds=perf_counter() - start_time))}")
+                return
+
+        # === BACKUP OLD FILES ===
+        backup_output_files()
+
+        # === WRITE NEW FILES ===
+        print("Writing files...")
+
+        with open(REQUESTS_FILE_NAME, 'w', encoding='utf-8') as f_json:
+            json.dump(output_requests, f_json, indent=4, ensure_ascii=False)
+        with open(ORGANIZATIONS_FILE_NAME, 'w', encoding='utf-8') as f_json:
+            json.dump(organizations_list, f_json, indent=4, ensure_ascii=False)
+
+        console.print("[green]✓ Data saved to JSON files[/green]")
+        print()
+
+        # === EXCEL EXPORT === (temporarily disabled for JSON generation testing)
+        # run_normal_mode_export(excel_export_enabled, excel_export_config,
+        #                       requests_mapping_config, organizations_mapping_config)
+
+    except IOError as io_err:
+        logging.critical(f"Error while writing JSON file : {io_err}")
+        print(f"Error while writing JSON file : {io_err}")
+    except Exception as exc:
+        logging.critical(f"Error during final processing : {exc}")
+        print(f"Error during final processing : {exc}")
+
+    print()
+    print(f"Elapsed time : {str(timedelta(seconds=perf_counter() - start_time))}")
+
+
+if __name__ == '__main__':
+
+    try:
+        main()
+    except Exception as e:
+        logging.critical(f"Script terminated prematurely due to an exception: {e}", exc_info=True)
+        print(f"Script stopped due to an error : {e}")
+    finally:
+        if 'subtasks_thread_pool' in globals() and subtasks_thread_pool:
+            subtasks_thread_pool.shutdown(wait=False, cancel_futures=True)
+        print('\n')
+        input("Press Enter to exit...")
diff --git a/do_dashboard_check_only-exe.bat b/do_dashboard_check_only-exe.bat
new file mode 100644
index 0000000..d11833c
--- /dev/null
+++ b/do_dashboard_check_only-exe.bat
@@ -0,0 +1,3 @@
+@echo off
+do_dashboard.exe --check-only %*
+
diff --git a/do_dashboard_check_only.bat b/do_dashboard_check_only.bat
new file mode 100644
index 0000000..a0d15f2
--- /dev/null
+++ b/do_dashboard_check_only.bat
@@ -0,0 +1,4 @@
+@echo off
+call C:\PythonProjects\.rcvenv\Scripts\activate.bat
+python do_dashboard.py --check-only %*
+
diff --git a/do_dashboard_check_only_debug-exe.bat b/do_dashboard_check_only_debug-exe.bat
new file mode 100644
index 0000000..1a49332
--- /dev/null
+++ b/do_dashboard_check_only_debug-exe.bat
@@ -0,0 +1,3 @@
+@echo off
+do_dashboard.exe --check-only --debug %*
+
diff --git a/do_dashboard_check_only_debug.bat b/do_dashboard_check_only_debug.bat
new file mode 100644
index 0000000..e21b536
--- /dev/null
+++ b/do_dashboard_check_only_debug.bat
@@ -0,0 +1,4 @@
+@echo off
+call C:\PythonProjects\.rcvenv\Scripts\activate.bat
+python do_dashboard.py --check-only --debug %*
+
diff --git a/do_dashboard_constants.py b/do_dashboard_constants.py
new file mode 100644
index 0000000..c245a98
--- /dev/null
+++ b/do_dashboard_constants.py
@@ -0,0 +1,135 @@
+"""
+DO Dashboard - Centralized Constants Module
+
+This module defines ALL constants used across the DO (Diagnostic Order) Dashboard application.
+It serves as the single source of truth for all configuration values.
+
+All other modules MUST import constants from this module, NOT define them locally.
+
+Structure:
+- File names & paths
+- Table names (Excel sheets)
+- API endpoints
+- Authentication credentials
+- Threading & retry parameters
+- DO filters config
+- UI formatting constants
+"""
+
+# ============================================================================
+# FILE NAMES & PATHS
+# ============================================================================
+
+REQUESTS_FILE_NAME = "do_requests.json"
+ORGANIZATIONS_FILE_NAME = "do_organizations.json"
+OLD_FILE_SUFFIX = "_old"
+CONFIG_FOLDER_NAME = "config"
+
+# ============================================================================
+# EXCEL CONFIGURATION FILES
+# ============================================================================
+
+DASHBOARD_CONFIG_FILE_NAME = "DO_Dashboard_Config.xlsx"
+ORG_CENTER_MAPPING_FILE_NAME = "do_org_center_mapping.xlsx"
+
+# ============================================================================
+# TABLE NAMES (Excel sheets in DASHBOARD_CONFIG_FILE_NAME)
+# ============================================================================
+
+REQUESTS_MAPPING_TABLE_NAME = "Requests_Mapping"
+ORGANIZATIONS_MAPPING_TABLE_NAME = "Organizations_Mapping"
+EXCEL_WORKBOOKS_TABLE_NAME = "Excel_Workbooks"
+EXCEL_SHEETS_TABLE_NAME = "Excel_Sheets"
+REGRESSION_CHECK_TABLE_NAME = "Regression_Check"
+ORG_CENTER_MAPPING_TABLE_NAME = "Org_Center_Mapping"
+
+# ============================================================================
+# DO FILTERS CONFIGURATION
+# ============================================================================
+
+# Named range in DASHBOARD_CONFIG_FILE_NAME containing the JSON filters object
+# for the worklist API call (e.g. {"status": "all-admin", "study": "ENDOLIFE"})
+DO_FILTERS = "DO_Filters"
+
+# Number of requests per page for worklist pagination
+DO_WORKLIST_PAGE_SIZE = 50
+
+# ============================================================================
+# API ENDPOINTS & AUTHENTICATION
+# ============================================================================
+
+IAM_URL = "https://api-auth.ziwig-connect.com"
+GDD_URL = "https://api-lab.ziwig-connect.com"
+GDD_APP_ID = "4f5ac063-6a22-4e2c-bda5-b50c0dddab79"
+
+DEFAULT_USER_NAME = "ziwig-invest2@yopmail.com"
+DEFAULT_PASSWORD = "pbrrA765$bP3beiuyuiyhiuy!agxagx"
+
+# ============================================================================
+# API ENDPOINTS
+# ============================================================================
+
+# Authentication endpoints
+API_AUTH_LOGIN_ENDPOINT = "/api/auth/ziwig-pro/login"
+API_AUTH_CONFIG_TOKEN_ENDPOINT = "/api/auth/config-token"
+API_AUTH_REFRESH_TOKEN_ENDPOINT = "/api/auth/refreshToken"
+
+# GDD (Diagnostic Order) endpoints
+API_DO_WORKLIST_ENDPOINT = "/api/requests/worklist-filter"
+API_DO_REQUEST_DETAIL_ENDPOINT = "/api/requests"          # + /{id}/validation
+API_DO_PROFESSIONALS_ENDPOINT = "/api/entity-manager/meta/modele_fr/data/nodes/pro/nodes"
+
+# ============================================================================
+# THREADING & RETRY PARAMETERS
+# ============================================================================
+
+ERROR_MAX_RETRY = 10
+WAIT_BEFORE_RETRY = 1
+WAIT_BEFORE_NEW_BATCH_OF_RETRIES = 20
+MAX_BATCHS_OF_RETRIES = 3
+MAX_THREADS = 40
+
+# Excel operation retry parameters (for handling transient xlwings/Excel failures)
+EXCEL_COM_MAX_RETRIES = 3
+EXCEL_COM_RETRY_DELAY = 0.5
+
+# ============================================================================
+# LOGGING CONFIGURATION
+# ============================================================================
+
+LOG_FILE_NAME = "dashboard.log"
+
+# ============================================================================
+# API CONFIGURATION
+# ============================================================================
+
+API_TIMEOUT = 60  # seconds - timeout for all API calls
+
+# ============================================================================
+# EXCEL EXPORT CONFIGURATION
+# ============================================================================
+
+# Output file conflict handling actions
+OUTPUT_ACTION_OVERWRITE = "Overwrite"
+OUTPUT_ACTION_INCREMENT = "Increment"
+OUTPUT_ACTION_BACKUP = "Backup"
+OUTPUT_ACTIONS = [OUTPUT_ACTION_OVERWRITE, OUTPUT_ACTION_INCREMENT, OUTPUT_ACTION_BACKUP]
+
+# Excel export data source types
+SOURCE_TYPE_REQUESTS = "Requests"
+SOURCE_TYPE_ORGANIZATIONS = "Organizations"
+SOURCE_TYPE_VARIABLE = "Variable"
+SOURCE_TYPES = [SOURCE_TYPE_REQUESTS, SOURCE_TYPE_ORGANIZATIONS, SOURCE_TYPE_VARIABLE]
+
+# Excel export target types (for data filling)
+TARGET_TYPE_TABLE = "Table"             # Excel structured table (ListObject) - has headers, supports Resize()
+TARGET_TYPE_NAMED_RANGE = "NamedRange"  # Simple named range - no headers, resize via Name.RefersTo
+
+# ============================================================================
+# UI FORMATTING (Progress bars)
+# ============================================================================
+
+BAR_N_FMT_WIDTH = 4
+BAR_TOTAL_FMT_WIDTH = 4
+BAR_TIME_WIDTH = 8
+BAR_RATE_WIDTH = 10
diff --git a/do_dashboard_debug-exe.bat b/do_dashboard_debug-exe.bat
new file mode 100644
index 0000000..d73da04
--- /dev/null
+++ b/do_dashboard_debug-exe.bat
@@ -0,0 +1,3 @@
+@echo off
+do_dashboard.exe --debug %*
+
diff --git a/do_dashboard_debug.bat b/do_dashboard_debug.bat
new file mode 100644
index 0000000..f695341
--- /dev/null
+++ b/do_dashboard_debug.bat
@@ -0,0 +1,4 @@
+@echo off
+call C:\PythonProjects\.rcvenv\Scripts\activate.bat
+python do_dashboard.py --debug %*
+
diff --git a/do_dashboard_excel_export.py b/do_dashboard_excel_export.py
new file mode 100644
index 0000000..3e76578
--- /dev/null
+++ b/do_dashboard_excel_export.py
@@ -0,0 +1,2094 @@
+"""
+DO Dashboard - Excel Export Module
+
+This module handles generation of Excel workbooks from Requests and Organizations data.
+Fully configurable via external Excel configuration file (DO_Dashboard_Config.xlsx).
+
+Features:
+- Config-driven workbook generation (no code changes needed)
+- Support for Variable templates and Table data fills
+- Configurable filtering, sorting, and value replacement
+- xlwings-based data processing with automatic formula recalculation
+- Robust error handling and logging
+"""
+
+import functools
+import json
+import logging
+import os
+import re
+import shutil
+import tempfile
+import traceback
+import zipfile
+from datetime import datetime, timedelta, timezone
+from time import perf_counter
+from zoneinfo import ZoneInfo
+
+import openpyxl
+from openpyxl.utils import get_column_letter
+from rich.console import Console
+
+try:
+    import xlwings as xw
+except ImportError:
+    xw = None
+
+from do_dashboard_utils import get_nested_value, get_config_path
+from do_dashboard_constants import (
+    REQUESTS_FILE_NAME,
+    ORGANIZATIONS_FILE_NAME,
+    DASHBOARD_CONFIG_FILE_NAME,
+    EXCEL_WORKBOOKS_TABLE_NAME,
+    EXCEL_SHEETS_TABLE_NAME,
+    OUTPUT_ACTION_OVERWRITE,
+    OUTPUT_ACTION_INCREMENT,
+    OUTPUT_ACTION_BACKUP,
+    OUTPUT_ACTIONS,
+    SOURCE_TYPE_REQUESTS,
+    SOURCE_TYPE_ORGANIZATIONS,
+    SOURCE_TYPE_VARIABLE,
+    SOURCE_TYPES,
+    TARGET_TYPE_TABLE,
+    TARGET_TYPE_NAMED_RANGE,
+    EXCEL_COM_MAX_RETRIES,
+    EXCEL_COM_RETRY_DELAY
+)
+
+# ============================================================================
+# CONSTANTS
+# ============================================================================
+
+EXCEL_OUTPUT_FOLDER = os.getcwd()  # Current working directory
+
+# ============================================================================
+# MODULE DEPENDENCIES (injected from main module)
+# ============================================================================
+
+console = None
+
+# NOTE: Constants imported from do_dashboard_constants.py (SINGLE SOURCE OF TRUTH):
+# Configuration Files:
+# - REQUESTS_FILE_NAME, ORGANIZATIONS_FILE_NAME, DASHBOARD_CONFIG_FILE_NAME
+# - EXCEL_WORKBOOKS_TABLE_NAME, EXCEL_SHEETS_TABLE_NAME
+# Output Handling:
+# - OUTPUT_ACTION_OVERWRITE, OUTPUT_ACTION_INCREMENT, OUTPUT_ACTION_BACKUP, OUTPUT_ACTIONS
+# Data Sources:
+# - SOURCE_TYPE_REQUESTS, SOURCE_TYPE_ORGANIZATIONS, SOURCE_TYPE_VARIABLE, SOURCE_TYPES
+#
+# NOTE: Mapping table names (INCLUSIONS_MAPPING_TABLE_NAME, ORGANIZATIONS_MAPPING_TABLE_NAME)
+# are defined in constants but loaded/used in main script (do_dashboard.py)
+
+
+def set_dependencies(console_instance):
+    """
+    Inject console instance from main module.
+
+    Args:
+        console_instance: Rich Console instance for formatted output
+
+    Note:
+        File and table names are imported directly from do_dashboard_constants.py
+        (SINGLE SOURCE OF TRUTH)
+    """
+    global console
+    console = console_instance
+
+
+# ============================================================================
+# PUBLIC FUNCTIONS
+# ============================================================================
+
+def load_excel_export_config(console_instance=None):
+    """
+    Load and validate Excel export configuration from config file.
+
+    Args:
+        console_instance: Optional Rich Console instance
+
+    Returns:
+        Tuple of (excel_workbooks_config, excel_sheets_config, has_error, error_messages)
+        - excel_workbooks_config: List of workbook definitions
+        - excel_sheets_config: List of sheet fill definitions
+        - has_error: Boolean flag if critical errors found
+        - error_messages: List of error message strings
+    """
+    global console
+    if console_instance:
+        console = console_instance
+
+    config_path = os.path.join(get_config_path(), DASHBOARD_CONFIG_FILE_NAME)
+    error_messages = []
+
+    try:
+        workbook = openpyxl.load_workbook(config_path)
+    except FileNotFoundError:
+        error_msg = f"Error: Configuration file not found at: {config_path}"
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        return None, None, True, [error_msg]
+
+    # Load Excel_Workbooks sheet
+    if EXCEL_WORKBOOKS_TABLE_NAME not in workbook.sheetnames:
+        error_msg = f"Error: Sheet '{EXCEL_WORKBOOKS_TABLE_NAME}' not found in configuration file."
+        error_messages.append(error_msg)
+        return None, None, True, error_messages
+
+    excel_workbooks_sheet = workbook[EXCEL_WORKBOOKS_TABLE_NAME]
+    excel_workbooks_config = []
+
+    try:
+        headers = [cell.value for cell in excel_workbooks_sheet[1]]
+        for row_index, row in enumerate(excel_workbooks_sheet.iter_rows(min_row=2, values_only=True), start=2):
+            if all(cell is None for cell in row):
+                continue  # Skip empty rows
+
+            workbook_config = dict(zip(headers, row))
+
+            # Validate required fields
+            if not workbook_config.get("workbook_id"):
+                error_msg = f"Row {row_index}: 'workbook_id' is mandatory"
+                error_messages.append(error_msg)
+                continue
+
+            if not workbook_config.get("workbook_template_name"):
+                error_msg = f"Row {row_index}: 'workbook_template_name' is mandatory"
+                error_messages.append(error_msg)
+                continue
+
+            if not workbook_config.get("output_file_name_template"):
+                error_msg = f"Row {row_index}: 'output_file_name_template' is mandatory"
+                error_messages.append(error_msg)
+                continue
+
+            if_output_exists = workbook_config.get("if_output_exists", OUTPUT_ACTION_OVERWRITE)
+            if if_output_exists not in OUTPUT_ACTIONS:
+                error_msg = f"Row {row_index}: 'if_output_exists' must be one of {OUTPUT_ACTIONS}"
+                error_messages.append(error_msg)
+                continue
+
+            excel_workbooks_config.append(workbook_config)
+    except Exception as e:
+        error_msg = f"Error loading Excel_Workbooks sheet: {e}"
+        error_messages.append(error_msg)
+        return None, None, True, error_messages
+
+    # Load Excel_Sheets sheet
+    if EXCEL_SHEETS_TABLE_NAME not in workbook.sheetnames:
+        error_msg = f"Error: Sheet '{EXCEL_SHEETS_TABLE_NAME}' not found in configuration file."
+        error_messages.append(error_msg)
+        return excel_workbooks_config, None, True, error_messages
+
+    excel_sheets_sheet = workbook[EXCEL_SHEETS_TABLE_NAME]
+    excel_sheets_config = []
+
+    try:
+        headers = [cell.value for cell in excel_sheets_sheet[1]]
+        for row_index, row in enumerate(excel_sheets_sheet.iter_rows(min_row=2, values_only=True), start=2):
+            if all(cell is None for cell in row):
+                continue
+
+            sheet_config = dict(zip(headers, row))
+
+            # Validate required fields
+            if not sheet_config.get("workbook_id"):
+                continue  # Skip rows without workbook_id
+
+            if not sheet_config.get("source_type"):
+                error_msg = f"Row {row_index}: 'source_type' is mandatory"
+                error_messages.append(error_msg)
+                continue
+
+            source_type = sheet_config["source_type"]
+            if source_type not in SOURCE_TYPES:
+                error_msg = f"Row {row_index}: 'source_type' must be one of {SOURCE_TYPES}"
+                error_messages.append(error_msg)
+                continue
+
+            if not sheet_config.get("source"):
+                error_msg = f"Row {row_index}: 'source' is mandatory"
+                error_messages.append(error_msg)
+                continue
+
+            if not sheet_config.get("target_name"):
+                error_msg = f"Row {row_index}: 'target_name' is mandatory"
+                error_messages.append(error_msg)
+                continue
+
+            # Parse JSON fields
+            has_json_error = False
+            for json_field in ["filter_condition", "sort_keys", "value_replacement"]:
+                value = sheet_config.get(json_field)
+                if value:
+                    if isinstance(value, str):
+                        try:
+                            sheet_config[json_field] = json.loads(value)
+                        except json.JSONDecodeError:
+                            error_msg = f"Row {row_index}, field '{json_field}': Invalid JSON format"
+                            error_messages.append(error_msg)
+                            has_json_error = True
+                            break  # ← Skip this row entirely
+                    # else: value is already parsed (dict/list), keep as-is
+                else:
+                    # Empty/None value - leave as None or empty
+                    sheet_config[json_field] = None
+
+            if not has_json_error:
+                excel_sheets_config.append(sheet_config)
+    except Exception as e:
+        error_msg = f"Error loading Excel_Sheets sheet: {e}"
+        error_messages.append(error_msg)
+        return excel_workbooks_config, excel_sheets_config, True, error_messages
+
+    workbook.close()
+
+    has_error = len(error_messages) > 0
+    return excel_workbooks_config, excel_sheets_config, has_error, error_messages
+
+
+def validate_excel_config(excel_config, console_instance, requests_mapping_config=None, organizations_mapping_config=None):
+    """
+    Validate Excel export configuration against templates.
+
+    Args:
+        excel_config: Tuple of (workbooks_config, sheets_config) from load_excel_export_config()
+        console_instance: Rich Console instance
+        requests_mapping_config: Loaded requests mapping config (optional, for future use)
+        organizations_mapping_config: Loaded organizations mapping config (optional, for future use)
+
+    Returns:
+        Tuple of (has_critical_error, error_messages)
+    """
+    global console
+    if console_instance:
+        console = console_instance
+
+    if not excel_config or not excel_config[0] or not excel_config[1]:
+        return False, []  # No config to validate
+
+    excel_workbooks_config, excel_sheets_config = excel_config[0], excel_config[1]
+    error_messages = []
+
+    # Validate each workbook
+    for workbook_config in excel_workbooks_config:
+        workbook_id = workbook_config.get("workbook_id")
+        template_name = workbook_config.get("workbook_template_name")
+
+        # Check template exists
+        template_path = os.path.join(get_config_path(), template_name)
+        if not os.path.exists(template_path):
+            error_msg = f"Template '{template_name}' (workbook_id: {workbook_id}) not found in config/"
+            error_messages.append(error_msg)
+            continue
+
+        # Check template is valid Excel
+        try:
+            template_wb = openpyxl.load_workbook(template_path)
+        except Exception as e:
+            error_msg = f"Template '{template_name}' (workbook_id: {workbook_id}) is not a valid Excel file: {e}"
+            error_messages.append(error_msg)
+            continue
+
+        # Validate sheets for this workbook
+        workbook_sheets = [s for s in excel_sheets_config if s.get("workbook_id") == workbook_id]
+
+        for sheet_config in workbook_sheets:
+            target_name = sheet_config.get("target_name")
+            source_type = sheet_config.get("source_type")
+
+            # Find the target in the template (check both named ranges AND tables)
+            target_found = False
+            if target_name in template_wb.defined_names:
+                target_found = True
+            else:
+                # Check if it's a table in any sheet
+                for sheet in template_wb.sheetnames:
+                    sheet_obj = template_wb[sheet]
+                    if hasattr(sheet_obj, 'tables') and target_name in sheet_obj.tables:
+                        target_found = True
+                        break
+
+            # If target was found, validate based on source type
+            if target_found:
+                # For Variable sources, ensure it's a single cell
+                if source_type == SOURCE_TYPE_VARIABLE:
+                    # Check if the defined name references a single cell
+                    # NOTE: We still use openpyxl here because template_wb is already open from config loading
+                    table_dims = _get_named_range_dimensions(template_wb, target_name)
+                    if table_dims:
+                        _, _, height, width = table_dims
+                        if height != 1 or width != 1:
+                            error_msg = f"Target '{target_name}' (template: {template_name}) for Variable source must reference a single cell (found {height}x{width})"
+                            error_messages.append(error_msg)
+
+                # For Table sources (Requests/Organizations), validate dimensions
+                elif source_type in [SOURCE_TYPE_REQUESTS, SOURCE_TYPE_ORGANIZATIONS]:
+                    # Get the dimensions of the named range
+                    # NOTE: We still use openpyxl here because template_wb is already open from config loading
+                    table_dims = _get_named_range_dimensions(template_wb, target_name)
+                    if table_dims:
+                        _, _, height, width = table_dims
+
+                        # CRITICAL: Table height MUST be exactly 1 (template row only)
+                        if height != 1:
+                            error_msg = f"Target '{target_name}' (template: {template_name}, source_type: {source_type}) must have height=1 (found height={height}). " \
+                                       f"Template row must be a single row."
+                            error_messages.append(error_msg)
+
+                        # CRITICAL: Table width must be >= max(mapping_indices)
+                        # Get the mapping column to validate indices
+                        source = sheet_config.get("source")
+                        if source:
+                            mapping_config = requests_mapping_config if source_type == SOURCE_TYPE_REQUESTS else organizations_mapping_config
+                            if mapping_config:
+                                column_mapping = _get_column_mapping(mapping_config, source, source_type)
+                                if column_mapping:
+                                    max_col_index = max(column_mapping.keys())  # 0-based index
+                                    if max_col_index >= width:
+                                        error_msg = f"Target '{target_name}' (template: {template_name}) width={width} is insufficient. " \
+                                                   f"Maximum column index from mapping is {max_col_index} (0-based). " \
+                                                   f"Width must be > {max_col_index}."
+                                        error_messages.append(error_msg)
+            else:
+                error_msg = f"Named range '{target_name}' (template: {template_name}, workbook_id: {workbook_id}) not found in template"
+                error_messages.append(error_msg)
+
+        template_wb.close()
+
+    return len(error_messages) > 0, error_messages
+
+
+def export_to_excel(requests_data, organizations_data, excel_config,
+                   requests_mapping_config=None, organizations_mapping_config=None):
+    """
+    Main export function - orchestrates Excel workbook generation.
+
+    Args:
+        requests_data: List of request dictionaries
+        organizations_data: List of organization dictionaries
+        excel_config: Tuple of (workbooks_config, sheets_config)
+        requests_mapping_config: Requests field mapping configuration
+        organizations_mapping_config: Organizations field mapping configuration
+
+    Returns:
+        Tuple of (success, error_count)
+
+    Note:
+        Uses global console instance (injected from main script)
+    """
+    if not excel_config or not excel_config[0] or not excel_config[1]:
+        console.print("[yellow]⚠ No Excel export configuration found, skipping[/yellow]")
+        return True, 0
+
+    excel_workbooks_config, excel_sheets_config = excel_config[0], excel_config[1]
+
+    # Prepare template variables
+    template_vars = _prepare_template_variables()
+
+    error_count = 0
+    success_count = 0
+
+    # Track overall export duration
+    export_start_time = perf_counter()
+
+    # Process each workbook
+    for workbook_config in excel_workbooks_config:
+        try:
+            workbook_id = workbook_config.get("workbook_id")
+            template_name = workbook_config.get("workbook_template_name")
+            output_template = workbook_config.get("output_file_name_template")
+            if_output_exists = workbook_config.get("if_output_exists", OUTPUT_ACTION_OVERWRITE)
+
+            # Resolve output filename
+            try:
+                output_filename = output_template.format(**template_vars)
+            except KeyError as e:
+                console.print(f"[bold red]✗ Unknown variable in template: {e}[/bold red]")
+                error_count += 1
+                continue
+
+            output_path = os.path.join(EXCEL_OUTPUT_FOLDER, output_filename)
+
+            # Log workbook processing start
+            logging.info(f"Processing workbook: {workbook_id} (template: {template_name}, output: {output_filename})")
+
+            # PHASE PRÉPARATION: Handle existing file according to action
+            output_path = _handle_output_exists(output_path, if_output_exists)
+
+            # XLWINGS PHASE: Open template, fill, save as output
+            template_path = os.path.join(get_config_path(), template_name)
+
+            # Track workbook processing duration with spinning status
+            workbook_start_time = perf_counter()
+
+            try:
+                if xw is None:
+                    raise ImportError("xlwings is not installed. Install with: pip install xlwings")
+
+                # Use status with spinner while processing the workbook
+                with console.status(f"[bold cyan]Exporting {output_filename}...", spinner="dots"):
+                    # PERFORMANCE: Make Excel invisible BEFORE opening the workbook
+                    app_xw = None
+                    screen_updating_original = None
+                    visible_original = None
+                    try:
+                        # Get or create Excel app in invisible mode
+                        if xw.apps:
+                            app_xw = xw.apps.active
+                            visible_original = app_xw.visible
+                            screen_updating_original = app_xw.screen_updating
+                        else:
+                            # Create new app in invisible mode
+                            app_xw = xw.App(visible=False)
+                            visible_original = False
+                            screen_updating_original = True
+
+                        app_xw.visible = False  # Make Excel invisible
+                        app_xw.screen_updating = False  # Disable screen updates
+
+                    except Exception as e:
+                        logging.warning(f"Failed to manage Excel visibility: {e}")
+                        app_xw = None
+
+                    # Open TEMPLATE directly (not a copy)
+                    wb_xw = xw.Book(template_path, update_links=False)
+
+                    try:
+                        # CAPTURE TEMPLATE STATE: Save initial state for restoration before save
+                        template_state = _capture_workbook_state(wb_xw, workbook_context=f"{workbook_id} ({output_filename})")
+                        logging.info(f"Captured template state: active_sheet='{template_state['active_sheet']}', {len(template_state['sheets'])} sheet(s)")
+
+                        # Get sheets for this workbook
+                        workbook_sheets = [s for s in excel_sheets_config if s.get("workbook_id") == workbook_id]
+
+                        # Process each sheet with xlwings
+                        for sheet_config in workbook_sheets:
+                            _process_sheet_xlwings(
+                                wb_xw,
+                                sheet_config,
+                                requests_data,
+                                organizations_data,
+                                requests_mapping_config=requests_mapping_config,
+                                organizations_mapping_config=organizations_mapping_config,
+                                template_vars=template_vars,
+                                workbook_context=f"{workbook_id} ({output_filename})"
+                            )
+
+                        # RESTORE TEMPLATE STATE: Restore initial state before saving
+                        _restore_workbook_state(wb_xw, template_state, workbook_context=f"{workbook_id} ({output_filename})")
+                        logging.info(f"Restored template state before save")
+
+                        # Save as output file with forced overwrite (with retry mechanism)
+                        # This preserves filesystem versioning for cloud storage
+                        # Disable alerts to force silent overwrite
+                        abs_output_path = os.path.abspath(output_path)
+                        if app_xw:
+                            display_alerts_original = app_xw.api.DisplayAlerts
+                            app_xw.api.DisplayAlerts = False
+                        try:
+                            _save_workbook_with_retry(wb_xw, abs_output_path)
+                            logging.info(f"Saved workbook to: {abs_output_path}")
+                        finally:
+                            if app_xw:
+                                app_xw.api.DisplayAlerts = display_alerts_original
+                        # Excel automatically recalculates formulas on save
+                        # No need for separate recalculation step
+
+                    finally:
+                        # Always close the workbook and restore visibility/screen updates
+                        wb_xw.close()
+                        if app_xw is not None:
+                            try:
+                                if screen_updating_original is not None:
+                                    app_xw.screen_updating = screen_updating_original
+                                if visible_original is not None:
+                                    app_xw.visible = visible_original
+                            except:
+                                pass
+
+                # Calculate duration and display success message
+                workbook_duration = perf_counter() - workbook_start_time
+                console.print(f"[green]✓ Created: {output_filename} ({workbook_duration:.2f}s)[/green]")
+                success_count += 1
+
+            except Exception as e:
+                console.print(f"[bold red]✗ Error processing {output_filename}: {e}[/bold red]")
+                logging.error(f"Excel export error for {output_filename}: {e}", exc_info=True)
+                error_count += 1
+                continue
+
+        except Exception as e:
+            console.print(f"[bold red]✗ Error processing workbook {workbook_id}: {e}[/bold red]")
+            logging.error(f"Excel workbook processing error: {e}", exc_info=True)
+            error_count += 1
+
+    # Summary with total duration
+    total_workbooks = success_count + error_count
+    export_duration = perf_counter() - export_start_time
+
+    if error_count == 0:
+        # Success: all workbooks processed
+        console.print(f"\n[green]✓ Excel export completed successfully: {success_count}/{total_workbooks} workbooks generated ({export_duration:.2f}s)[/green]")
+    else:
+        # Failure: some or all workbooks failed
+        if success_count > 0:
+            # Partial success
+            console.print(f"\n[yellow]⚠ Excel export completed with errors ({export_duration:.2f}s)[/yellow]")
+            console.print(f"[green]  {success_count} workbook(s) generated successfully[/green]")
+            console.print(f"[bold red]  {error_count} workbook(s) failed[/bold red]")
+        else:
+            # Complete failure
+            console.print(f"\n[bold red]✗ Excel export failed: all {error_count} workbook(s) failed ({export_duration:.2f}s)[/bold red]")
+
+    return error_count == 0, error_count
+
+
+# ============================================================================
+# INTERNAL FUNCTIONS
+# ============================================================================
+
+def _prepare_template_variables():
+    """
+    Prepare variables available for Template String evaluation.
+
+    Returns:
+        Dictionary of variables available to .format(**locals())
+    """
+    # Get UTC timestamp from requests file
+    # Use constant from do_dashboard_constants (SINGLE SOURCE OF TRUTH)
+    requests_file = REQUESTS_FILE_NAME
+    if os.path.exists(requests_file):
+        file_mtime = os.path.getmtime(requests_file)
+        extract_date_time_utc = datetime.fromtimestamp(file_mtime, tz=timezone.utc)
+    else:
+        extract_date_time_utc = datetime.now(tz=timezone.utc)
+
+    # Convert to Paris timezone
+    extract_date_time_french = extract_date_time_utc.astimezone(
+        ZoneInfo('Europe/Paris')
+    )
+
+    return {
+        'extract_date_time_utc': extract_date_time_utc,
+        'extract_date_time_french': extract_date_time_french,
+    }
+
+
+def _apply_filter(item, filter_condition):
+    """
+    Apply filter condition to item (AND logic for all conditions).
+
+    Args:
+        item: Dictionary to filter
+        filter_condition: List of [field_name, operator, value] conditions
+
+    Returns:
+        Boolean True if item passes all filters
+    """
+    if not filter_condition:
+        return True  # Empty filter = accept all
+
+    for field_path, operator, expected_value in filter_condition:
+        actual_value = get_nested_value(item, field_path.split("."))
+
+        if actual_value is None:
+            return False  # Missing field = filter out
+
+        # Apply operator
+        if operator == "==":
+            if actual_value != expected_value:
+                return False
+        elif operator == "<>":
+            if actual_value == expected_value:
+                return False
+        elif operator == ">":
+            if not (actual_value > expected_value):
+                return False
+        elif operator == ">=":
+            if not (actual_value >= expected_value):
+                return False
+        elif operator == "<":
+            if not (actual_value < expected_value):
+                return False
+        elif operator == "<=":
+            if not (actual_value <= expected_value):
+                return False
+
+    return True  # All conditions passed
+
+
+def _apply_sort(items, sort_keys):
+    """
+    Apply multi-key sort to items with support for mixed asc/desc ordering.
+
+    Args:
+        items: List of dictionaries to sort
+        sort_keys: List of [field_name, order] or [field_name, order, option]
+                  where:
+                  - order is "asc" or "desc"
+                  - option (optional) can be:
+                    * datetime format string (e.g., "%Y-%m-%d") for date parsing
+                    * "*natsort" for natural alphanumeric sorting
+                  Supports MIXED asc/desc on different columns!
+
+    Returns:
+        Sorted list
+    """
+    if not sort_keys:
+        return items
+
+    def natural_sort_key(text):
+        """
+        Helper for natural alphanumeric sorting.
+        Converts "ENDOBEST-003-920-BA" to ["endobest", "-", 3, "-", 920, "-", "ba"]
+        Python's native list comparison handles the rest element by element.
+        """
+        def convert(segment):
+            return int(segment) if segment.isdigit() else segment.lower()
+        return [convert(s) for s in re.split(r'(\d+)', str(text)) if s]
+
+    def compare_items(item1, item2):
+        """
+        Comparator function for multi-key sorting with mixed asc/desc support.
+        Returns: -1 if item1 < item2, 0 if equal, 1 if item1 > item2
+        """
+        for sort_spec in sort_keys:
+            field_name = sort_spec[0]
+            order = sort_spec[1] if len(sort_spec) > 1 else "asc"
+            sort_option = sort_spec[2] if len(sort_spec) > 2 else None
+
+            # Get values from both items
+            val1 = get_nested_value(item1, field_name.split("."))
+            val2 = get_nested_value(item2, field_name.split("."))
+
+            # Handle undefined/None - place at end
+            is_undef1 = val1 in [None, "", "undefined"]
+            is_undef2 = val2 in [None, "", "undefined"]
+
+            # Both undefined: equal
+            if is_undef1 and is_undef2:
+                continue
+
+            # Only one undefined: undefined goes last
+            if is_undef1:
+                return 1  # item1 > item2 (undefined last)
+            if is_undef2:
+                return -1  # item1 < item2 (item2 is undefined)
+
+            # Check if natural sort requested
+            is_natural_sort = (sort_option == "*natsort")
+
+            # Parse datetime if option is a datetime format (not *natsort)
+            if sort_option and not is_natural_sort:
+                datetime_format = sort_option
+                try:
+                    val1 = datetime.strptime(str(val1), datetime_format).timestamp()
+                except (ValueError, TypeError):
+                    val1 = None
+                    return 1  # Invalid datetime goes last
+
+                try:
+                    val2 = datetime.strptime(str(val2), datetime_format).timestamp()
+                except (ValueError, TypeError):
+                    val2 = None
+                    return -1  # Invalid datetime goes last
+
+            # Apply natural sort transformation if requested
+            if is_natural_sort:
+                val1 = natural_sort_key(val1)
+                val2 = natural_sort_key(val2)
+
+            # Compare values
+            # For strings (non-natsort), use case-insensitive comparison for natural alphabetical ordering
+            if isinstance(val1, str) and isinstance(val2, str):
+                val1_lower = val1.lower()
+                val2_lower = val2.lower()
+                if val1_lower < val2_lower:
+                    cmp_result = -1
+                elif val1_lower > val2_lower:
+                    cmp_result = 1
+                else:
+                    # Case-insensitive equal, use case-sensitive as tiebreaker
+                    if val1 < val2:
+                        cmp_result = -1
+                    elif val1 > val2:
+                        cmp_result = 1
+                    else:
+                        cmp_result = 0
+            else:
+                # Non-string comparison (numbers, dates, natsort lists, etc.)
+                if val1 < val2:
+                    cmp_result = -1
+                elif val1 > val2:
+                    cmp_result = 1
+                else:
+                    cmp_result = 0  # Equal, continue to next sort key
+
+            # Apply asc/desc ordering
+            if cmp_result != 0:
+                is_desc = isinstance(order, str) and order.lower() == "desc"
+                return cmp_result if not is_desc else -cmp_result
+
+        # All keys are equal
+        return 0
+
+    # Use functools.cmp_to_key to convert comparator to key function
+    return sorted(items, key=functools.cmp_to_key(compare_items))
+
+
+def _apply_value_replacement(value, replacements):
+    """
+    Apply value replacement rules (first-match-wins, strict type matching).
+
+    Args:
+        value: Value to potentially replace
+        replacements: List of [value_before, value_after] pairs
+
+    Returns:
+        Replaced value or original
+
+    Note:
+        This function is currently prepared for future use in table data filling.
+    """
+    if not replacements:
+        return value
+
+    for value_before, value_after in replacements:
+        if value == value_before:  # Strict equality
+            return value_after
+
+    return value  # No match, return original
+
+
+# OBSOLETE: _preserve_media_in_workbook() removed - xlwings handles media preservation automatically
+# When using xlwings, Excel natively preserves all media, images, and relationships
+
+
+def _save_workbook_with_retry(wb_xw, output_path):
+    """
+    Save workbook with retry mechanism for transient xlwings/Excel failures.
+
+    Excel's SaveAs can fail randomly on some environments (especially Excel 2013).
+    This function retries the save operation with configurable retry count and delay.
+
+    Args:
+        wb_xw: xlwings Book object
+        output_path: Absolute path where workbook should be saved
+
+    Raises:
+        Exception: If SaveAs fails after all retry attempts
+    """
+    from time import sleep
+
+    for attempt in range(1, EXCEL_COM_MAX_RETRIES + 1):
+        try:
+            logging.info(f"SaveAs attempt {attempt}/{EXCEL_COM_MAX_RETRIES}: {output_path}")
+            wb_xw.api.SaveAs(output_path)
+            logging.info(f"SaveAs succeeded on attempt {attempt}")
+            return  # Success
+
+        except Exception as e:
+            error_msg = f"SaveAs failed on attempt {attempt}: {type(e).__name__}: {str(e)}"
+
+            if attempt < EXCEL_COM_MAX_RETRIES:
+                # Intermediate retry - log as warning and sleep before retry
+                logging.warning(f"{error_msg} - Retrying in {EXCEL_COM_RETRY_DELAY}s...")
+                sleep(EXCEL_COM_RETRY_DELAY)
+            else:
+                # Final attempt failed - log as critical error and raise
+                logging.error(f"{error_msg} - All {EXCEL_COM_MAX_RETRIES} retry attempts exhausted")
+                raise
+
+
+def _capture_workbook_state(wb_xw, workbook_context=""):
+    """
+    Capture the visual state of the workbook (active sheet, selections, scroll positions).
+
+    This allows restoration of the template's visual state after data processing,
+    ensuring recipients see the workbook exactly as designed in the template.
+
+    Args:
+        wb_xw: xlwings Book object
+        workbook_context: String identifier for logging (workbook_id and filename)
+
+    Returns:
+        dict: State dictionary with 'active_sheet' and 'sheets' state per sheet
+    """
+    ctx = f"[{workbook_context}]" if workbook_context else ""
+    logging.info(f"{ctx} [CAPTURE_STATE] Starting workbook state capture")
+    logging.info(f"{ctx} [CAPTURE_STATE] Total sheets: {len(wb_xw.sheets)}")
+
+    state = {
+        'active_sheet': None,
+        'sheets': {}
+    }
+
+    try:
+        # Capture active sheet name
+        state['active_sheet'] = wb_xw.api.ActiveSheet.Name
+        logging.info(f"{ctx} [CAPTURE_STATE] Active sheet captured: '{state['active_sheet']}'")
+    except Exception as e:
+        logging.warning(f"{ctx} [CAPTURE_STATE] Could not capture active sheet: {type(e).__name__}: {str(e)}")
+
+    # Capture state for each sheet
+    for idx, sheet in enumerate(wb_xw.sheets, 1):
+        logging.info(f"{ctx} [CAPTURE_STATE] Processing sheet {idx}/{len(wb_xw.sheets)}: '{sheet.name}'")
+        try:
+            # Activate sheet to get its state
+            sheet.activate()
+            logging.info(f"{ctx} [CAPTURE_STATE] Sheet '{sheet.name}' activated successfully")
+            sheet_api = sheet.api
+
+            sheet_state = {
+                'selection': None,
+                'scroll_row': 1,
+                'scroll_col': 1
+            }
+
+            # Capture selection address
+            try:
+                selection_address = sheet_api.Application.Selection.Address
+                sheet_state['selection'] = selection_address
+                logging.info(f"{ctx} [CAPTURE_STATE] Sheet '{sheet.name}' selection captured: {selection_address}")
+            except Exception as e:
+                sheet_state['selection'] = "A1"  # Default
+                logging.warning(f"{ctx} [CAPTURE_STATE] Could not capture selection for sheet '{sheet.name}': {type(e).__name__}, defaulting to A1")
+
+            # Capture scroll position
+            try:
+                scroll_row = sheet_api.Application.ActiveWindow.ScrollRow
+                scroll_col = sheet_api.Application.ActiveWindow.ScrollColumn
+                sheet_state['scroll_row'] = scroll_row
+                sheet_state['scroll_col'] = scroll_col
+                logging.info(f"{ctx} [CAPTURE_STATE] Sheet '{sheet.name}' scroll position captured: Row={scroll_row}, Col={scroll_col}")
+            except Exception as e:
+                logging.warning(f"{ctx} [CAPTURE_STATE] Could not capture scroll position for sheet '{sheet.name}': {type(e).__name__}, keeping defaults")
+
+            state['sheets'][sheet.name] = sheet_state
+            logging.info(f"{ctx} [CAPTURE_STATE] Sheet '{sheet.name}' state complete: {sheet_state}")
+
+        except Exception as e:
+            logging.error(f"{ctx} [CAPTURE_STATE] ERROR capturing state for sheet '{sheet.name}': {type(e).__name__}: {str(e)}")
+
+    logging.info(f"{ctx} [CAPTURE_STATE] Workbook state capture complete. Captured {len(state['sheets'])} sheet(s)")
+    return state
+
+
+def _restore_workbook_state(wb_xw, state, workbook_context=""):
+    """
+    Restore the visual state of the workbook (active sheet, selections, scroll positions).
+
+    Args:
+        wb_xw: xlwings Book object
+        state: State dictionary from _capture_workbook_state()
+        workbook_context: String identifier for logging (workbook_id and filename)
+    """
+    if not state:
+        logging.warning("[RESTORE_STATE] Empty state provided, skipping restoration")
+        return
+
+    from time import sleep
+
+    ctx = f"[{workbook_context}]" if workbook_context else ""
+    logging.info(f"{ctx} [RESTORE_STATE] Starting workbook state restoration")
+    logging.info(f"{ctx} [RESTORE_STATE] Restoring {len(state.get('sheets', {}))} sheet(s)")
+
+    # NOTE: Screen updating is already disabled at the global level (in export_to_excel)
+    # for the entire workbook processing cycle (from open to save).
+    # We do NOT re-disable it here to avoid state conflicts.
+    # The global setting ensures all operations (capture, process, restore, save) run efficiently.
+
+    # CRITICAL: Excel 2013 COM layer lock recovery
+    # After bulk paste operations, Excel's COM layer can enter a "locked" state where Range.Select()
+    # fails persistently. This appears to be a fundamental limitation/bug in Excel 2013.
+    # To work around this, we need to:
+    # 1. Give Excel time to recover with a large delay
+    # 2. Then make a "dummy" Range.Select() to wake up the COM layer
+    # 3. Then proceed with real restorations
+    logging.info(f"{ctx} [RESTORE_STATE] Waiting for Excel COM layer to stabilize after bulk operations (2 seconds)...")
+    sleep(2.0)  # Large delay to allow COM layer to recover
+
+    # Track original visibility state (used for temporary visibility during retries)
+    original_app_visible = None
+    try:
+        if wb_xw.app:
+            original_app_visible = wb_xw.app.visible
+
+            if not original_app_visible:
+                # Make Excel visible during restoration so user sees what's happening
+                # (important for selection restore retries which may take 2+ seconds)
+                wb_xw.app.visible = True
+                logging.info(f"{ctx} [RESTORE_STATE] Excel app temporarily made visible for restoration operations")
+    except Exception as e:
+        logging.warning(f"{ctx} [RESTORE_STATE] Could not manage Excel visibility during restoration: {type(e).__name__}: {str(e)}")
+
+    # Wake up the COM layer with a dummy selection attempt on the first sheet
+    # This "primes" the COM layer so subsequent Range.Select() calls work reliably
+    try:
+        if len(wb_xw.sheets) > 0:
+            first_sheet = wb_xw.sheets[0]
+            first_sheet.activate()
+            logging.info(f"{ctx} [RESTORE_STATE] Priming COM layer by activating first sheet...")
+            first_sheet.api.Range("$A$1").Select()
+            logging.info(f"{ctx} [RESTORE_STATE] COM layer priming successful")
+    except Exception as e:
+        # This is not critical - if it fails, retries will handle it
+        logging.info(f"{ctx} [RESTORE_STATE] COM layer priming attempt completed (may have failed, retries will handle it)")
+
+    # Restore state for each sheet
+    for idx, (sheet_name, sheet_state) in enumerate(state.get('sheets', {}).items(), 1):
+        logging.info(f"{ctx} [RESTORE_STATE] Processing sheet {idx}: '{sheet_name}'")
+        try:
+            sheet = wb_xw.sheets[sheet_name]
+            sheet.activate()
+            logging.info(f"{ctx} [RESTORE_STATE] Sheet '{sheet_name}' activated successfully")
+
+            # Small delay after activation to ensure Excel has completed the sheet switch
+            sleep(0.3)
+
+            sheet_api = sheet.api
+
+            # Restore selection with retry mechanism for transient Excel COM failures
+            if sheet_state.get('selection'):
+                selection = sheet_state['selection']
+                selection_restored = False
+
+                # Try to restore original selection with retry
+                for attempt in range(1, EXCEL_COM_MAX_RETRIES + 1):
+                    try:
+                        logging.info(f"{ctx} [RESTORE_STATE] Selection restore attempt {attempt}/{EXCEL_COM_MAX_RETRIES} for '{selection}' on sheet '{sheet_name}'")
+                        sheet_api.Range(selection).Select()
+                        logging.info(f"{ctx} [RESTORE_STATE] Sheet '{sheet_name}' selection restored to: {selection}")
+                        selection_restored = True
+                        break  # Success
+                    except Exception as e:
+                        error_msg = f"Selection restore failed on attempt {attempt}: {type(e).__name__}: {str(e)}"
+
+                        if attempt < EXCEL_COM_MAX_RETRIES:
+                            # Intermediate retry - log as warning and sleep before retry
+                            logging.warning(f"{ctx} [RESTORE_STATE] {error_msg} - Retrying in {EXCEL_COM_RETRY_DELAY}s...")
+                            sleep(EXCEL_COM_RETRY_DELAY)
+                        else:
+                            # Final attempt failed - log as error, will default to A1
+                            logging.error(f"{ctx} [RESTORE_STATE] {error_msg} - All {EXCEL_COM_MAX_RETRIES} retry attempts exhausted")
+
+                # If selection restore failed after all retries, default to A1
+                if not selection_restored:
+                    logging.warning(f"{ctx} [RESTORE_STATE] Could not restore selection '{selection}' for sheet '{sheet_name}' after {EXCEL_COM_MAX_RETRIES} attempts, defaulting to A1")
+
+                    # Try to set default A1 selection (using absolute reference: $A$1)
+                    for attempt in range(1, EXCEL_COM_MAX_RETRIES + 1):
+                        try:
+                            logging.info(f"{ctx} [RESTORE_STATE] A1 default attempt {attempt}/{EXCEL_COM_MAX_RETRIES} for sheet '{sheet_name}'")
+                            sheet_api.Range("$A$1").Select()
+                            logging.info(f"{ctx} [RESTORE_STATE] Sheet '{sheet_name}' selection defaulted to A1")
+                            break  # Success
+                        except Exception as e2:
+                            error_msg = f"A1 default failed on attempt {attempt}: {type(e2).__name__}: {str(e2)}"
+
+                            if attempt < EXCEL_COM_MAX_RETRIES:
+                                logging.warning(f"{ctx} [RESTORE_STATE] {error_msg} - Retrying in {EXCEL_COM_RETRY_DELAY}s...")
+                                sleep(EXCEL_COM_RETRY_DELAY)
+                            else:
+                                logging.error(f"{ctx} [RESTORE_STATE] {error_msg} - All {EXCEL_COM_MAX_RETRIES} retry attempts exhausted")
+
+            # Restore scroll position
+            try:
+                scroll_row = sheet_state.get('scroll_row', 1)
+                scroll_col = sheet_state.get('scroll_col', 1)
+                sheet_api.Application.ActiveWindow.ScrollRow = scroll_row
+                sheet_api.Application.ActiveWindow.ScrollColumn = scroll_col
+                logging.info(f"{ctx} [RESTORE_STATE] Sheet '{sheet_name}' scroll position restored: Row={scroll_row}, Col={scroll_col}")
+            except Exception as e:
+                logging.warning(f"{ctx} [RESTORE_STATE] Could not restore scroll position for sheet '{sheet_name}': {type(e).__name__}")
+
+        except Exception as e:
+            logging.error(f"{ctx} [RESTORE_STATE] ERROR restoring state for sheet '{sheet_name}': {type(e).__name__}: {str(e)}")
+
+    # Restore active sheet
+    if state.get('active_sheet'):
+        try:
+            from time import sleep
+
+            active_sheet_name = state['active_sheet']
+            wb_xw.sheets[active_sheet_name].activate()
+
+            # Wait for sheet activation to complete on Excel 2013's COM layer
+            sleep(0.3)
+
+            logging.info(f"{ctx} [RESTORE_STATE] Active sheet restored to: '{active_sheet_name}'")
+        except Exception as e:
+            logging.error(f"{ctx} [RESTORE_STATE] Could not restore active sheet '{state.get('active_sheet')}': {type(e).__name__}: {str(e)}")
+
+    # Force sheet tabs to scroll to show the first sheet
+    # This ensures the tab bar starts from the first sheet, regardless of which sheet is active
+    # NOTE: ScrollWorkbookTabs only works when Excel is visible
+    try:
+        if len(wb_xw.sheets) > 0 and wb_xw.app:
+            logging.info(f"{ctx} [RESTORE_STATE] Attempting to scroll sheet tabs to first sheet")
+
+            try:
+                # ScrollWorkbookTabs with negative number scrolls tabs LEFT (toward first sheet)
+                # Use large negative number (-100) to guarantee we reach the beginning
+                # Excel visibility is already managed at the beginning of this function
+                wb_xw.api.Application.ActiveWindow.ScrollWorkbookTabs(-100)
+                logging.info(f"{ctx} [RESTORE_STATE] Sheet tabs scrolled to beginning")
+            except Exception as e:
+                logging.warning(f"{ctx} [RESTORE_STATE] Could not scroll sheet tabs to beginning: {type(e).__name__}: {str(e)}")
+    except Exception as e:
+        logging.error(f"{ctx} [RESTORE_STATE] ERROR during sheet tabs scroll operation: {type(e).__name__}: {str(e)}")
+
+    # Restore original visibility state (if we temporarily made it visible)
+    # NOTE: Screen updating restoration is handled at the global level (in export_to_excel)
+    # after the workbook is saved and closed
+    try:
+        if original_app_visible is not None and wb_xw.app:
+            if not original_app_visible and wb_xw.app.visible:
+                # Restore to hidden state if it was originally hidden
+                wb_xw.app.visible = False
+                logging.info(f"{ctx} [RESTORE_STATE] Excel app visibility restored to original state: False")
+    except Exception as e:
+        logging.warning(f"{ctx} [RESTORE_STATE] Could not restore Excel app visibility: {type(e).__name__}: {str(e)}")
+
+    logging.info(f"{ctx} [RESTORE_STATE] Workbook state restoration complete")
+
+
+def _handle_output_exists(output_path, action):
+    """
+    Handle existing output file (Overwrite/Increment/Backup).
+
+    Args:
+        output_path: Full path to output file
+        action: "Overwrite", "Increment", or "Backup"
+
+    Returns:
+        Actual path to use (may be different if Increment/Backup)
+    """
+    if not os.path.exists(output_path):
+        logging.info(f"Output file doesn't exist yet: {output_path}")
+        return output_path
+
+    logging.info(f"Output file exists, applying '{action}' rule: {output_path}")
+
+    if action == OUTPUT_ACTION_OVERWRITE:
+        logging.info(f"Overwriting existing file: {output_path}")
+        return output_path
+
+    elif action == OUTPUT_ACTION_INCREMENT:
+        base, ext = os.path.splitext(output_path)
+        counter = 1
+        while os.path.exists(f"{base}_{counter}{ext}"):
+            counter += 1
+        new_path = f"{base}_{counter}{ext}"
+        logging.info(f"Using incremented filename: {new_path}")
+        return new_path
+
+    elif action == OUTPUT_ACTION_BACKUP:
+        base, ext = os.path.splitext(output_path)
+        counter = 1
+        backup_path = f"{base}_backup_{counter}{ext}"
+        while os.path.exists(backup_path):
+            counter += 1
+            backup_path = f"{base}_backup_{counter}{ext}"
+
+        try:
+            logging.info(f"Backing up existing file to: {backup_path}")
+            shutil.copy2(output_path, backup_path)
+            logging.info(f"Backup successful: {output_path} -> {backup_path}")
+        except Exception as e:
+            logging.error(f"Backup failed: {e}")
+            raise
+
+        # Return original path - the existing file will be overwritten by SaveAs
+        return output_path
+
+    return output_path
+
+
+def _get_column_mapping(mapping_config, mapping_column_name, source_type):
+    """
+    Extract column mapping from Requests_Mapping or Organizations_Mapping.
+
+    The mapping column contains user-friendly 1-based indices (1, 2, 3, ...)
+    indicating which column in the Excel table each field should be placed.
+    These are converted to 0-based indices for internal use.
+
+    Args:
+        mapping_config: List of mapping config rows (dicts with field_name, etc.)
+        mapping_column_name: Name of the mapping column to extract (e.g., "MainReport_PatientsList")
+        source_type: "Requests" or "Organizations"
+
+    Returns:
+        Dictionary: {excel_column_index: source_field_name}
+        Example: {0: "Patient_Identification.Patient_Id", 1: "Request.Status", ...}
+        Indices are 0-based (converted from 1-based user input)
+        or None if mapping_column not found
+    """
+    if not mapping_config:
+        return None
+
+    column_mapping = {}
+
+    for row in mapping_config:
+        # Get the field name (source field in the JSON)
+        field_name = row.get("field_name")
+        if not field_name:
+            continue
+
+        # Get the mapping value from the specified column
+        mapping_value = row.get(mapping_column_name)
+        if mapping_value is None or mapping_value == "":
+            continue  # Skip empty mappings
+
+        # Convert mapping_value to integer (1-based user-friendly index)
+        try:
+            user_col_index = int(mapping_value)
+        except (ValueError, TypeError):
+            logging.warning(f"Invalid column index '{mapping_value}' for field '{field_name}'")
+            continue
+
+        # Convert 1-based to 0-based index
+        excel_col_index = user_col_index - 1
+
+        if excel_col_index < 0:
+            logging.warning(f"Column index '{user_col_index}' for field '{field_name}' must be >= 1")
+            continue
+
+        # Store: excel_column_index -> field_name
+        # Field name needs to be qualified with group for Requests
+        # (extracted from the row's field_group if available)
+        if source_type == "Requests":
+            field_group = row.get("field_group", "")
+            if field_group:
+                full_field_name = f"{field_group}.{field_name}"
+            else:
+                full_field_name = field_name
+        else:
+            # For Organizations, field_name might already be qualified or standalone
+            full_field_name = field_name
+
+        column_mapping[excel_col_index] = full_field_name
+
+    return column_mapping if column_mapping else None
+
+
+def _parse_range_dimensions(start_row, start_col, end_row, end_col, header_row_count=0):
+    """
+    Shared utility: Calculate dimensions from cell coordinates.
+
+    Args:
+        start_row, start_col: Starting cell (1-based, after headers)
+        end_row, end_col: Ending cell (1-based)
+        header_row_count: Number of header rows (0 if none)
+
+    Returns:
+        Tuple of (width, total_height, data_height)
+    """
+    width = end_col - start_col + 1
+    total_height = end_row - start_row + 1
+    data_height = total_height - header_row_count
+    return width, total_height, data_height
+
+
+def _get_named_range_dimensions(workbook, range_name):
+    """
+    Get dimensions of named range or table in workbook.
+
+    Args:
+        workbook: openpyxl Workbook object
+        range_name: Name of the named range or table
+
+    Returns:
+        Tuple of (sheet_name, start_cell, height, width) or None if not found
+    """
+    # First check for defined named ranges (in openpyxl 3.x)
+    if range_name in workbook.defined_names:
+        defined_name = workbook.defined_names[range_name]
+        # Get the range reference from attr_text (e.g., "Sheet!$A$1:$B$10")
+        range_ref = defined_name.attr_text
+
+        # Parse: "SheetName!$A$1:$B$10"
+        if '!' in range_ref:
+            sheet_name, cell_range = range_ref.split('!')
+            # Remove quotes if present
+            sheet_name = sheet_name.strip("'\"")
+            # Remove $ signs for parsing
+            cell_range = cell_range.replace('$', '')
+
+            if sheet_name in workbook.sheetnames:
+                sheet = workbook[sheet_name]
+
+                # Parse cell range (e.g., "A1:B10" or single "A1")
+                if ':' in cell_range:
+                    start_cell_str, end_cell_str = cell_range.split(':')
+                    start_cell = sheet[start_cell_str]
+                    end_cell = sheet[end_cell_str]
+                    width = end_cell.column - start_cell.column + 1
+                    height = end_cell.row - start_cell.row + 1
+                else:
+                    start_cell = sheet[cell_range]
+                    width = 1
+                    height = 1
+
+                return sheet_name, start_cell, height, width
+
+    # Check if it's a Table (Excel table object, not just a named range)
+    for sheet_name in workbook.sheetnames:
+        sheet = workbook[sheet_name]
+        if hasattr(sheet, 'tables') and range_name in sheet.tables:
+            table = sheet.tables[range_name]
+            # Table has a 'ref' property with the range (e.g., "A4:F5")
+            # Excel tables can have header rows (default 1, but can be 0)
+            table_ref = table.ref
+            header_row_count = getattr(table, 'headerRowCount', 1) or 0  # 0 if None or False
+
+            # Parse cell range (e.g., "A4:F5")
+            if ':' in table_ref:
+                start_cell_str, end_cell_str = table_ref.split(':')
+                start_cell_temp = sheet[start_cell_str]
+                end_cell = sheet[end_cell_str]
+                width = end_cell.column - start_cell_temp.column + 1
+                total_height = end_cell.row - start_cell_temp.row + 1
+
+                # Skip header rows: point to first DATA row
+                if header_row_count > 0:
+                    data_start_row = start_cell_temp.row + header_row_count
+                    start_cell = sheet.cell(row=data_start_row, column=start_cell_temp.column)
+                else:
+                    start_cell = start_cell_temp
+
+                # Calculate data row count (total - headers)
+                height = total_height - header_row_count
+            else:
+                start_cell = sheet[table_ref]
+                width = 1
+                height = 1
+
+            return sheet_name, start_cell, height, width
+
+    return None
+
+# OBSOLETE: _update_named_range_height() removed
+# This function was only called by the old openpyxl-based _process_sheet() implementation
+# xlwings uses table.Resize() via COM API instead, which is more reliable
+# See PHASE 2 migration notes for details
+
+
+# OBSOLETE: _recalculate_workbook() removed - xlwings handles formula recalculation automatically
+# When using xlwings with wb.save(), Excel automatically recalculates all formulas
+
+# OBSOLETE: _process_sheet() removed - openpyxl implementation migrated to xlwings
+# All sheet processing is now handled by _process_sheet_xlwings() using xlwings library
+# This eliminates code duplication and provides better preservation of workbook structure
+
+
+def _get_table_dimensions_xlwings(workbook_xw, range_name):
+    """
+    Get dimensions of an Excel table OR named range using xlwings COM API.
+
+    First searches for ListObjects (structured tables), then falls back to
+    simple named ranges if no table is found.
+
+    Args:
+        workbook_xw: xlwings Book object (already open)
+        range_name: Name of the Excel table (ListObject) or named range
+
+    Returns:
+        Tuple (sheet_name, start_cell, height, width, header_row_count, target_type) or None if not found
+        - start_cell: Points to FIRST DATA ROW (after headers for tables, first row for named ranges)
+        - height: Number of DATA ROWS (excluding headers for tables)
+        - header_row_count: Number of header rows (0 for named ranges, 0 or 1 for tables)
+        - target_type: TARGET_TYPE_TABLE or TARGET_TYPE_NAMED_RANGE
+
+    Note:
+        - For tables with headers: start_cell points to first data row (after header)
+        - For tables without headers: start_cell points to first row of table
+        - For named ranges: start_cell points to first row (no headers assumed)
+    """
+    # Helper class to mimic openpyxl Cell behavior
+    class CellRef:
+        def __init__(self, row, column):
+            self.row = row
+            self.column = column
+        @property
+        def coordinate(self):
+            col_letter = get_column_letter(self.column)
+            return f"{col_letter}{self.row}"
+
+    # === PRIORITY 1: Check if it's a table (ListObject) ===
+    # Excel tables are more reliable than plain named ranges with xlwings
+    for sheet in workbook_xw.sheets:
+        sheet_api = sheet.api
+
+        # Try to get the table count - if this fails, the sheet has no ListObjects property
+        try:
+            table_count = sheet_api.ListObjects.Count
+        except:
+            # Sheet doesn't support ListObjects or has none
+            continue
+
+        # If no tables in this sheet, skip
+        if table_count == 0:
+            continue
+
+        # Iterate through tables by index
+        for i in range(1, table_count + 1):  # COM indexing starts at 1
+            try:
+                xl_table = sheet_api.ListObjects.Item(i)
+                table_name = xl_table.Name
+                if table_name == range_name:
+                    # Found a table - get its range
+                    xl_range = xl_table.Range
+                    sheet_name = sheet.name
+                    total_rows = xl_range.Rows.Count
+                    total_cols = xl_range.Columns.Count
+                    start_row = xl_range.Row
+                    start_col = xl_range.Column
+
+                    # Get header row count from the table
+                    # In COM API, ListObject has ShowHeaders property (boolean) and HeaderRowRange
+                    # ShowHeaders: True if table has header row, False if not
+                    try:
+                        has_headers = xl_table.ShowHeaders
+                        header_row_count = 1 if has_headers else 0
+                    except:
+                        # If ShowHeaders not accessible, try HeaderRowRange
+                        try:
+                            header_range = xl_table.HeaderRowRange
+                            header_row_count = 1 if header_range is not None else 0
+                        except:
+                            # Fallback: assume headers exist (most common case)
+                            header_row_count = 1
+
+                    # Data height = total height - header rows
+                    data_height = total_rows - header_row_count
+
+                    # start_cell points to the FIRST DATA ROW (after headers)
+                    # If table has headers: skip them. If no headers: start at table start
+                    if header_row_count > 0:
+                        data_start_row = start_row + header_row_count
+                    else:
+                        data_start_row = start_row
+                    start_cell = CellRef(data_start_row, start_col)
+
+                    logging.info(f"[TABLE FOUND] Located table '{range_name}' at {sheet_name}!{start_cell.coordinate} "
+                                f"(data rows: {data_height}, headers: {header_row_count}, total width: {total_cols})")
+                    return sheet_name, start_cell, data_height, total_cols, header_row_count, TARGET_TYPE_TABLE
+            except Exception as e:
+                # Error accessing this specific table, skip it
+                logging.warning(f"Error accessing table {i} in '{sheet.name}': {type(e).__name__}")
+
+    # === PRIORITY 2: Check if it's a named range ===
+    # Named ranges don't have headers - data starts at first row
+    try:
+        if range_name in workbook_xw.names:
+            named_range = workbook_xw.names[range_name]
+            target_range = named_range.refers_to_range
+
+            sheet_name = target_range.sheet.name
+            start_row = target_range.row
+            start_col = target_range.column
+            total_rows = target_range.rows.count
+            total_cols = target_range.columns.count
+
+            # Named ranges have no headers - all rows are data rows
+            header_row_count = 0
+            data_height = total_rows
+
+            start_cell = CellRef(start_row, start_col)
+
+            logging.info(f"[NAMED RANGE FOUND] Located named range '{range_name}' at {sheet_name}!{start_cell.coordinate} "
+                        f"(data rows: {data_height}, no headers, total width: {total_cols})")
+            return sheet_name, start_cell, data_height, total_cols, header_row_count, TARGET_TYPE_NAMED_RANGE
+    except Exception as e:
+        logging.warning(f"Error accessing named range '{range_name}': {type(e).__name__}: {str(e)}")
+
+    # Range/table not found
+    logging.warning(f"Named range or table '{range_name}' not found in workbook")
+    return None
+
+
+# ============================================================================
+# HELPER FUNCTIONS FOR SHEET PROCESSING (extracted from _process_sheet_xlwings)
+# ============================================================================
+
+def _fill_variable_in_sheet(workbook_xw, target_name, source_template, template_vars, workbook_context=""):
+    """
+    Fill a single variable cell with evaluated template value.
+
+    Args:
+        workbook_xw: xlwings Book object
+        target_name: Name of the target named range (single cell)
+        source_template: Template string with {variables}
+        template_vars: Dictionary of variable values
+        workbook_context: Context string for logging
+
+    Returns:
+        Boolean True if successful
+    """
+    try:
+        # Evaluate template string
+        cell_value = source_template.format(**template_vars)
+    except KeyError as e:
+        logging.warning(f"Unknown variable in template: {e}")
+        return False
+
+    # Write to named cell using xlwings
+    try:
+        named_range = workbook_xw.names[target_name]
+        target_range = named_range.refers_to_range
+        target_range.value = cell_value
+        logging.info(f"Set variable '{target_name}' to '{cell_value}'")
+        return True
+    except KeyError:
+        logging.warning(f"Named range '{target_name}' not found in {workbook_context}")
+        return False
+    except Exception as e:
+        logging.warning(f"Error setting variable '{target_name}' in {workbook_context}: {e}")
+        return False
+
+
+def _prepare_table_data(source_type, source, sheet_config, requests_data, organizations_data,
+                        requests_mapping_config, organizations_mapping_config, target_name):
+    """
+    Prepare table data: select source, apply filter/sort, get column mapping.
+
+    Args:
+        source_type: Type of source (Requests or Organizations)
+        source: Source identifier (mapping name)
+        sheet_config: Sheet configuration dictionary
+        requests_data: Requests data list
+        organizations_data: Organizations data list
+        requests_mapping_config: Requests mapping config
+        organizations_mapping_config: Organizations mapping config
+        target_name: Target range name (for logging)
+
+    Returns:
+        Tuple of (sorted_data, column_mapping) or (None, None) if error
+    """
+    # Select source data and mapping config
+    if source_type == SOURCE_TYPE_REQUESTS:
+        source_data = requests_data
+        mapping_config = requests_mapping_config
+    else:
+        source_data = organizations_data
+        mapping_config = organizations_mapping_config
+
+    # Apply filter and sort
+    filter_condition = sheet_config.get("filter_condition")
+    sort_keys = sheet_config.get("sort_keys")
+
+    filtered_data = [item for item in source_data if _apply_filter(item, filter_condition)]
+    sorted_data = _apply_sort(filtered_data, sort_keys)
+
+    # Get column mapping
+    column_mapping = _get_column_mapping(mapping_config, source, source_type)
+    if not column_mapping:
+        logging.warning(f"Column mapping '{source}' not found or empty for {target_name}")
+        return None, None
+
+    return sorted_data, column_mapping
+
+
+def _resize_table_range(workbook_xw, sheet_xw, target_name, start_cell, max_col, start_row, num_data_rows, header_row_count=0, target_type=TARGET_TYPE_TABLE):
+    """
+    Resize Excel table (ListObject) or named range to match data dimensions.
+
+    For Tables (ListObjects): Uses ListObject.Resize() COM API
+    For Named Ranges: Redefines the named range via Name.RefersTo property
+
+    Args:
+        workbook_xw: xlwings Book object (needed for named range resize)
+        sheet_xw: xlwings Sheet object
+        target_name: Name of the table/named range
+        start_cell: Starting cell (CellRef) - points to FIRST DATA ROW (after headers for tables)
+        max_col: Maximum column (1-based)
+        start_row: Starting row (1-based, first data row)
+        num_data_rows: Number of data rows
+        header_row_count: Number of header rows in the table (0 for named ranges)
+        target_type: TARGET_TYPE_TABLE or TARGET_TYPE_NAMED_RANGE
+
+    Returns:
+        None (logging handles errors)
+    """
+    if num_data_rows <= 1:
+        return
+
+    try:
+        # Calculate the last data row
+        last_data_row = start_row + num_data_rows - 1
+
+        if target_type == TARGET_TYPE_TABLE:
+            # === TABLE (ListObject) RESIZE ===
+            excel_sheet = sheet_xw.api
+
+            # Find the ListObject (Table) by name
+            for list_obj in excel_sheet.ListObjects:
+                if list_obj.Name == target_name:
+                    # If header_row_count not provided (legacy fallback), get it from the table
+                    if header_row_count == 0:
+                        try:
+                            has_headers = list_obj.ShowHeaders
+                            header_row_count = 1 if has_headers else 0
+                        except:
+                            header_row_count = 1
+
+                    # For resize, include header rows if they exist
+                    if header_row_count > 0:
+                        first_row = start_row - header_row_count
+                    else:
+                        first_row = start_row
+
+                    resize_range_str = f"{get_column_letter(start_cell.column)}{first_row}:{get_column_letter(max_col)}{last_data_row}"
+
+                    # Perform resize via ListObject.Resize()
+                    new_range = excel_sheet.Range(resize_range_str)
+                    list_obj.Resize(new_range)
+                    logging.info(f"Resized table '{target_name}' to {resize_range_str} (header_rows={header_row_count})")
+                    break
+
+        elif target_type == TARGET_TYPE_NAMED_RANGE:
+            # === NAMED RANGE RESIZE ===
+            # Redefine the named range to cover all data rows
+            # Named ranges have no headers, so start_row is the first row
+            first_col_letter = get_column_letter(start_cell.column)
+            last_col_letter = get_column_letter(max_col)
+
+            # Build the range address in A1 style
+            range_address = f"${first_col_letter}${start_row}:${last_col_letter}${last_data_row}"
+
+            # Get the actual Range object from the sheet and assign it to the Name
+            # This avoids R1C1/A1 format issues by using the Range object directly
+            new_range = sheet_xw.range(range_address)
+            workbook_xw.api.Names(target_name).RefersTo = new_range.api
+            logging.info(f"Resized named range '{target_name}' to {sheet_xw.name}!{range_address}")
+
+    except Exception as e:
+        logging.warning(f"Resize skipped for {target_name} ({target_type}): {e}")
+
+
+def _duplicate_template_row(sheet_xw, start_cell, max_col, start_row, num_data_rows, target_name, workbook_context=""):
+    """
+    Duplicate template row to all data rows via copy-paste.
+
+    Args:
+        sheet_xw: xlwings Sheet object
+        start_cell: Starting cell (CellRef)
+        max_col: Maximum column (1-based)
+        start_row: Starting row (1-based)
+        num_data_rows: Number of data rows
+        target_name: Target range name (for logging)
+        workbook_context: Context string for logging
+
+    Returns:
+        None (logging handles errors)
+    """
+    if num_data_rows <= 1:
+        return
+
+    try:
+        # Replicate template row to all data rows in a single operation
+        template_range_str = f"{get_column_letter(start_cell.column)}{start_row}:{get_column_letter(max_col)}{start_row}"
+        last_data_row = start_row + num_data_rows - 1
+        full_target_range_str = f"{get_column_letter(start_cell.column)}{start_row}:{get_column_letter(max_col)}{last_data_row}"
+
+        # Copy template row
+        sheet_xw.range(template_range_str).copy()
+        # Paste to entire range - Excel automatically replicates the template row
+        sheet_xw.range(full_target_range_str).paste()
+
+        # CRITICAL: Deselect after paste to avoid COM layer lock
+        # After bulk paste on large ranges (85k+ cells), Excel's COM layer becomes saturated
+        # and leaves a massive selection active. This prevents subsequent Range.Select() calls.
+        # Solution: Reset Excel's selection state by switching sheets and back, then select A1.
+        try:
+            from time import sleep
+            logging.info(f"Deselecting range after bulk paste for {target_name}...")
+
+            # Switch to another sheet to force Excel to reset selection state
+            other_sheets = [s for s in sheet_xw.book.sheets if s.name != sheet_xw.name]
+            if other_sheets:
+                other_sheets[0].activate()
+                sleep(0.1)
+
+            # Reactivate our sheet - Excel resets selection management when returning
+            sheet_xw.activate()
+
+            # Select A1 - COM should manage this easily now
+            sheet_xw.api.Range("$A$1").Select()
+            logging.info(f"Successfully deselected after bulk paste for {target_name} (sheet reactivation)")
+
+        except Exception as e:
+            # Deselection is non-critical, log and continue if it fails
+            logging.warning(f"Deselection after paste failed for {target_name}: {type(e).__name__}: {str(e)}")
+
+    except Exception as e:
+        logging.warning(f"Template duplication failed for {target_name} in {workbook_context}: {e}")
+
+
+def _fill_table_with_data(sheet_xw, start_cell, start_row, start_col, sorted_data, column_mapping,
+                          value_replacement, target_name, sheet_name):
+    """
+    Fill table with data: group contiguous columns and transfer via bulk 2D arrays.
+
+    Args:
+        sheet_xw: xlwings Sheet object
+        start_cell: Starting cell (CellRef)
+        start_row: Starting row (1-based)
+        start_col: Starting column (1-based)
+        sorted_data: Sorted list of data items
+        column_mapping: Dict mapping Excel column indices to source field paths
+        value_replacement: Value replacement configuration (or None)
+        target_name: Target range name (for logging)
+        sheet_name: Sheet name (for logging)
+
+    Returns:
+        None (logging handles errors and success)
+    """
+    try:
+        # === Prepare column mapping and group contiguous columns ===
+        col_order = sorted(column_mapping.keys())
+
+        # Group contiguous columns for optimal bulk update
+        contiguous_groups = []
+        if col_order:
+            current_group = [col_order[0]]
+            for i in range(1, len(col_order)):
+                if col_order[i] == col_order[i-1] + 1:
+                    current_group.append(col_order[i])
+                else:
+                    contiguous_groups.append(current_group)
+                    current_group = [col_order[i]]
+            contiguous_groups.append(current_group)
+
+        # === Update contiguous column groups (bulk 2D transfer) ===
+        for col_group in contiguous_groups:
+            # Build 2D array for this group: rows × columns
+            data_2d = []
+            for item in sorted_data:
+                row_values = []
+                for excel_col_index in col_group:
+                    source_field_path = column_mapping[excel_col_index]
+                    # Get value from source item
+                    value = get_nested_value(item, source_field_path.split("."))
+
+                    # Apply value replacement
+                    if value_replacement:
+                        value = _apply_value_replacement(value, value_replacement)
+
+                    row_values.append(value)
+                data_2d.append(row_values)
+
+            # Transfer entire group to Excel in ONE operation
+            first_col_in_group = start_col + col_group[0]
+            first_col_letter = get_column_letter(first_col_in_group)
+            target_range_start = f"{first_col_letter}{start_row}"
+
+            # Write 2D array at once (xlwings automatically maps rows × columns)
+            sheet_xw.range(target_range_start).value = data_2d
+
+        # Logging
+        num_data_rows = len(sorted_data)
+        logging.info(f"Filled table {target_name} with {num_data_rows} rows "
+                   f"at {sheet_name}!{start_cell.coordinate} "
+                   f"(bulk duplication + {len(contiguous_groups)} contiguous group(s))")
+    except Exception as e:
+        logging.error(f"Error filling table data for {target_name}: {e}")
+        logging.error(f"Traceback: {traceback.format_exc()}")
+
+
+def _process_sheet_xlwings(workbook_xw, sheet_config, requests_data, organizations_data,
+                           requests_mapping_config, organizations_mapping_config, template_vars,
+                           workbook_context=""):
+    """
+    Process a single sheet using xlwings (hybrid approach).
+
+    Delegates to specialized helpers to maintain clarity and testability.
+
+    Args:
+        workbook_xw: xlwings Book object
+        sheet_config: Sheet configuration dict
+        requests_data: List of request dictionaries
+        organizations_data: List of organization dictionaries
+        requests_mapping_config: Requests mapping config (for column mapping)
+        organizations_mapping_config: Organizations mapping config
+        template_vars: Dictionary of variables for template evaluation
+        workbook_context: Context string identifying the workbook (for logging)
+
+    Returns:
+        Boolean True if successful
+    """
+    source_type = sheet_config.get("source_type")
+    source = sheet_config.get("source")
+    target_name = sheet_config.get("target_name")
+    value_replacement = sheet_config.get("value_replacement")
+
+    # === Variable sources: single cell fill ===
+    if source_type == SOURCE_TYPE_VARIABLE:
+        return _fill_variable_in_sheet(workbook_xw, target_name, source, template_vars, workbook_context)
+
+    # === Table sources: bulk data filling ===
+    if source_type not in [SOURCE_TYPE_REQUESTS, SOURCE_TYPE_ORGANIZATIONS]:
+        return False
+
+    # Prepare data: filter, sort, get column mapping
+    sorted_data, column_mapping = _prepare_table_data(
+        source_type, source, sheet_config, requests_data, organizations_data,
+        requests_mapping_config, organizations_mapping_config, target_name
+    )
+    if sorted_data is None or column_mapping is None:
+        return False
+
+    # Get table/named range dimensions from xlwings
+    try:
+        table_dims = _get_table_dimensions_xlwings(workbook_xw, target_name)
+        if not table_dims:
+            logging.warning(f"Target '{target_name}' not found (neither table nor named range)")
+            return False
+
+        sheet_name, start_cell, table_height, table_width, header_row_count, target_type = table_dims
+        sheet_xw = workbook_xw.sheets[sheet_name]
+        start_row = start_cell.row
+        start_col = start_cell.column
+        max_col = start_col + table_width - 1
+        num_data_rows = len(sorted_data)
+
+        # === Bulk operations for data filling ===
+        if sorted_data:
+            # STEP 0: Resize table/named range to match data dimensions
+            _resize_table_range(workbook_xw, sheet_xw, target_name, start_cell, max_col, start_row, num_data_rows, header_row_count, target_type)
+
+            # STEP 1: Duplicate template row to all data rows
+            _duplicate_template_row(sheet_xw, start_cell, max_col, start_row, num_data_rows, target_name, workbook_context)
+
+            # STEP 2-3: Fill with data (grouped contiguous columns)
+            _fill_table_with_data(sheet_xw, start_cell, start_row, start_col, sorted_data,
+                                column_mapping, value_replacement, target_name, sheet_name)
+        else:
+            # No data - template row stays empty
+            logging.info(f"No data for target '{target_name}' ({target_type}), leaving template row empty")
+
+        return True
+
+    except Exception as e:
+        logging.warning(f"Error processing target '{target_name}': {e}")
+        logging.error(f"Traceback: {traceback.format_exc()}")
+        return False
+
+
+# ============================================================================
+# COMPREHENSIVE EXCEL EXPORT ORCHESTRATION (for main script)
+# ============================================================================
+
+def prepare_excel_export(requests_mapping_config, organizations_mapping_config):
+    """
+    Validate Excel export configuration (no data loading).
+
+    This function has a SINGLE responsibility: validate the Excel export CONFIG.
+    It does NOT load production data (JSONs) - that is the responsibility of
+    the execution functions (run_normal_mode_export, export_excel_only).
+
+    IMPORTANT: Mapping configs MUST be provided by the caller. The caller is responsible for:
+    1. Loading mapping configs from Excel (e.g., via load_requests_mapping_config())
+    2. Passing them to this function for config validation
+
+    This follows the dependency injection pattern: the caller provides dependencies,
+    this function validates config. This ensures:
+    - Clear responsibility separation: validation ≠ data loading
+    - Early CONFIG validation (BEFORE data collection in NORMAL MODE)
+    - Late DATA loading (AFTER collection, only when needed for execution)
+
+    Args:
+        requests_mapping_config: Loaded requests mapping (required, non-empty list/dict)
+        organizations_mapping_config: Loaded organizations mapping (required, non-empty list/dict)
+
+    Returns:
+        Tuple of (excel_config, has_critical_errors, error_messages)
+        - excel_config: Tuple of (workbooks_config, sheets_config) or None if errors
+        - has_critical_errors: Boolean True if validation found critical errors
+        - error_messages: List of error message strings
+
+    Note:
+        JSONs are loaded separately by execution functions:
+        - NORMAL MODE: run_normal_mode_export() loads JSONs AFTER data collection
+        - --EXCEL-ONLY: export_excel_only() loads JSONs before execution
+    """
+
+    error_messages = []
+    excel_config = None
+    has_critical_errors = False
+
+    # === STEP 1: Validate mapping configurations are provided ===
+    # Caller is responsible for loading these configs before calling this function
+    if not requests_mapping_config or (isinstance(requests_mapping_config, (list, dict)) and len(requests_mapping_config) == 0):
+        error_msg = "Requests mapping configuration must be provided and non-empty"
+        error_messages.append(error_msg)
+        logging.error(error_msg)
+        if console:
+            console.print(f"[bold red]✗ {error_msg}[/bold red]")
+        has_critical_errors = True
+        return excel_config, has_critical_errors, error_messages
+
+    if not organizations_mapping_config or (isinstance(organizations_mapping_config, (list, dict)) and len(organizations_mapping_config) == 0):
+        error_msg = "Organizations mapping configuration must be provided and non-empty"
+        error_messages.append(error_msg)
+        logging.error(error_msg)
+        if console:
+            console.print(f"[bold red]✗ {error_msg}[/bold red]")
+        has_critical_errors = True
+        return excel_config, has_critical_errors, error_messages
+
+    # === STEP 2: Load Excel config ===
+    logging.info("Loading Excel export configuration...")
+
+    excel_workbooks_config, excel_sheets_config, has_config_error, config_error_messages = load_excel_export_config(console)
+    if has_config_error:
+        error_msg = "Critical errors in Excel Export Config"
+        error_messages.append(error_msg)
+        error_messages.extend(config_error_messages)
+        has_critical_errors = True
+        logging.warning(error_msg)
+        if console:
+            console.print(f"[bold red]✗ {error_msg}[/bold red]")
+        excel_config = (excel_workbooks_config, excel_sheets_config)
+        return excel_config, has_critical_errors, error_messages
+
+    if not excel_workbooks_config or not excel_sheets_config:
+        error_msg = "Excel export configuration is empty"
+        error_messages.append(error_msg)
+        logging.warning(error_msg)
+        if console:
+            console.print(f"[bold red]✗ {error_msg}[/bold red]")
+        excel_config = (excel_workbooks_config, excel_sheets_config)
+        return excel_config, has_critical_errors, error_messages
+
+    # Package config into tuple for downstream functions
+    excel_config = (excel_workbooks_config, excel_sheets_config)
+
+    # === STEP 3: Validate Excel config ===
+    logging.info("Validating Excel export configuration...")
+
+    has_critical_errors, validation_errors = validate_excel_config(
+        excel_config,
+        console,
+        requests_mapping_config or [],
+        organizations_mapping_config or {}
+    )
+
+    if validation_errors:
+        error_messages.extend(validation_errors)
+        if has_critical_errors and console:
+            console.print("[bold red]✗ Critical validation errors found[/bold red]")
+    else:
+        logging.info("✓ Excel export configuration validated successfully")
+
+    return excel_config, has_critical_errors, error_messages
+
+
+# ============================================================================
+# HIGH-LEVEL ORCHESTRATION FUNCTIONS (for main script integration)
+# ============================================================================
+
+def export_excel_only(sys_argv,
+                      requests_filename=None, organizations_filename=None,
+                      requests_mapping_config=None, organizations_mapping_config=None):
+    """
+    Orchestrates EXCEL_ONLY mode - complete end-to-end Excel export workflow.
+
+    This function completely encapsulates the --excel_only mode:
+    1. Validates Excel configuration
+    2. Loads JSON data files (must exist)
+    3. Executes Excel export with error handling
+    4. Displays user-friendly messages and confirmations
+
+    IMPORTANT: The caller (main script) is responsible for loading mapping configs
+    before calling this function. This ensures consistent config instances across
+    the application and follows the dependency injection pattern.
+
+    This follows the same pattern as run_check_only_mode() from quality_checks module.
+
+    Args:
+        sys_argv: sys.argv from main script (for potential future CLI arg parsing)
+        requests_filename: Name of requests JSON file (e.g., "do_requests.json")
+        organizations_filename: Name of organizations JSON file (e.g., "do_organizations.json")
+        requests_mapping_config: Loaded requests mapping configuration (REQUIRED - caller must load)
+        organizations_mapping_config: Loaded organizations mapping configuration (REQUIRED - caller must load)
+    """
+    global console
+
+    if not requests_filename:
+        requests_filename = REQUESTS_FILE_NAME
+    if not organizations_filename:
+        organizations_filename = ORGANIZATIONS_FILE_NAME
+
+    print()
+    console.print("[bold cyan]═══ EXCEL ONLY MODE ═══[/bold cyan]\n")
+
+    # Step 1: Validate Excel configuration (no data loading)
+    logging.info("EXCEL ONLY MODE: Validating Excel configuration")
+    excel_config, has_config_critical, error_messages = \
+        prepare_excel_export(requests_mapping_config, organizations_mapping_config)
+
+    # Step 2: Handle critical configuration errors
+    if has_config_critical:
+        print()
+        console.print("[bold red]⚠ CRITICAL CONFIGURATION ERROR(S) DETECTED[/bold red]")
+        console.print("[bold red]────────────────────────────────────[/bold red]")
+        for idx, error_msg in enumerate(error_messages, 1):
+            console.print(f"[bold red]Error {idx}: {error_msg}[/bold red]")
+        console.print("[bold red]────────────────────────────────────[/bold red]")
+        print()
+        try:
+            import questionary
+            answer = questionary.confirm(
+                "⚠ Continue anyway?",
+                default=False
+            ).ask()
+            if not answer:
+                console.print("[bold red]Aborted by user[/bold red]")
+                logging.warning("EXCEL ONLY MODE: Aborted by user due to critical errors")
+                return
+        except ImportError:
+            console.print("[bold yellow]⚠ questionary not available for confirmation[/bold yellow]")
+            console.print("[bold yellow]Proceeding with export despite critical errors[/bold yellow]")
+
+    # Step 3: Load JSON data files (must exist in --excel-only mode)
+    logging.info("EXCEL ONLY MODE: Loading data files")
+    requests_data = _load_json_file_internal(requests_filename)
+    organizations_data = _load_json_file_internal(organizations_filename)
+
+    if requests_data is None or organizations_data is None:
+        console.print("[bold red]✗ Error: Could not load data files for Excel export[/bold red]")
+        logging.error("EXCEL ONLY MODE: Data file loading failed")
+        return
+
+    # Step 4: Execute Excel export (direct call to export_to_excel, console is global)
+    print()
+    console.print("[bold cyan]═══ Excel Export ═══[/bold cyan]\n")
+    logging.info("EXCEL ONLY MODE: Executing export")
+
+    if excel_config:
+        try:
+            logging.info(f"Starting Excel export: {len(requests_data)} requests, {len(organizations_data)} organizations")
+
+            success, error_count = export_to_excel(
+                requests_data,
+                organizations_data,
+                excel_config,
+                requests_mapping_config=requests_mapping_config,
+                organizations_mapping_config=organizations_mapping_config
+            )
+
+            if success:
+                logging.info("EXCEL ONLY MODE: Export completed successfully")
+            else:
+                logging.warning(f"EXCEL ONLY MODE: Export completed with {error_count} error(s)")
+        except Exception as e:
+            error_msg = f"Excel export failed: {str(e)}"
+            logging.error(f"EXCEL ONLY MODE: {error_msg}\n{traceback.format_exc()}")
+            console.print(f"[bold red]✗ {error_msg}[/bold red]\n")
+    else:
+        console.print("[bold red]✗ Could not load Excel configuration[/bold red]\n")
+        logging.error("EXCEL ONLY MODE: Excel config missing")
+
+
+def run_normal_mode_export(excel_enabled, excel_config,
+                           requests_mapping_config=None, organizations_mapping_config=None):
+    """
+    Orchestrates Excel export during normal mode execution.
+
+    This function encapsulates the Excel export step that runs after requests and organizations
+    have been collected and written to JSON files. It handles:
+    - Loading JSONs from filesystem (ensures fresh data consistency)
+    - Executing Excel export with comprehensive error handling
+    - Displaying results to user
+
+    This is called from the normal workflow after data collection completes.
+
+    Args:
+        excel_enabled: Boolean indicating if Excel export is enabled
+        excel_config: Tuple of (workbooks_config, sheets_config) or None
+        requests_mapping_config: Loaded requests mapping configuration (optional)
+        organizations_mapping_config: Loaded organizations mapping configuration (optional)
+
+    Note:
+        This function loads JSON files from the filesystem (which were written
+        during the data collection phase) to ensure consistency.
+
+    Returns:
+        Tuple of (export_succeeded, error_message)
+        - export_succeeded: Boolean True if export completed successfully (or skipped)
+        - error_message: String with error details (empty if success=True or skipped)
+    """
+    global console
+
+    # Only proceed if export is enabled and config is available
+    if not excel_enabled or not excel_config:
+        logging.info("Excel export not enabled or config missing, skipping")
+        return True, ""  # FIX BUG #3: Return True when export is intentionally skipped (not an error)
+
+    print()
+    console.print("[bold cyan]═══ Excel Export ═══[/bold cyan]\n")
+    logging.info("NORMAL MODE: Starting Excel export")
+
+    try:
+        # Load JSONs from filesystem to ensure data consistency with what was written
+        # Use constants imported from do_dashboard_constants.py (SINGLE SOURCE OF TRUTH)
+        requests_from_fs = _load_json_file_internal(REQUESTS_FILE_NAME)
+        organizations_from_fs = _load_json_file_internal(ORGANIZATIONS_FILE_NAME)
+
+        if requests_from_fs is None or organizations_from_fs is None:
+            error_msg = "Could not load data files for Excel export"
+            logging.error(f"NORMAL MODE: {error_msg}")
+            console.print(f"[bold red]✗ {error_msg}[/bold red]\n")
+            return False, error_msg
+
+        # Execute the export (direct call to export_to_excel, console is global)
+        logging.info(f"Starting Excel export: {len(requests_from_fs)} requests, {len(organizations_from_fs)} organizations")
+
+        success, error_count = export_to_excel(
+            requests_from_fs,
+            organizations_from_fs,
+            excel_config,
+            requests_mapping_config=requests_mapping_config,
+            organizations_mapping_config=organizations_mapping_config
+        )
+
+        if success:
+            logging.info("NORMAL MODE: Excel export completed successfully")
+            return True, ""
+        else:
+            error_msg = f"Excel export completed with {error_count} error(s)"
+            logging.warning(f"NORMAL MODE: {error_msg}")
+            return False, error_msg
+
+    except Exception as e:
+        error_msg = f"Unexpected error during Excel export: {str(e)}"
+        logging.error(f"NORMAL MODE: {error_msg}\n{traceback.format_exc()}")
+        console.print(f"[bold red]✗ {error_msg}[/bold red]\n")
+        return False, error_msg
+
+
+def _load_json_file_internal(filename):
+    """
+    Internal helper to load JSON file.
+
+    Args:
+        filename: Path to JSON file
+
+    Returns:
+        Parsed JSON data or None if file doesn't exist or can't be parsed
+    """
+    try:
+        if not os.path.exists(filename):
+            logging.warning(f"JSON file not found: {filename}")
+            return None
+
+        with open(filename, 'r', encoding='utf-8') as f:
+            data = json.load(f)
+            logging.info(f"Loaded {filename}: {len(data) if isinstance(data, list) else 'data'}")
+            return data
+
+    except Exception as e:
+        logging.error(f"Error loading {filename}: {str(e)}")
+        return None
diff --git a/do_dashboard_excel_only-exe.bat b/do_dashboard_excel_only-exe.bat
new file mode 100644
index 0000000..7fc15ae
--- /dev/null
+++ b/do_dashboard_excel_only-exe.bat
@@ -0,0 +1,3 @@
+@echo off
+do_dashboard.exe --excel-only %*
+
diff --git a/do_dashboard_excel_only.bat b/do_dashboard_excel_only.bat
new file mode 100644
index 0000000..92b927a
--- /dev/null
+++ b/do_dashboard_excel_only.bat
@@ -0,0 +1,4 @@
+@echo off
+call C:\PythonProjects\.rcvenv\Scripts\activate.bat
+python do_dashboard.py --excel-only %*
+
diff --git a/do_dashboard_quality_checks.py b/do_dashboard_quality_checks.py
new file mode 100644
index 0000000..62227b3
--- /dev/null
+++ b/do_dashboard_quality_checks.py
@@ -0,0 +1,786 @@
+"""
+DO Dashboard - Quality Checks Module
+
+This module contains all quality assurance functions:
+- JSON file loading and backup utilities
+- Comprehensive non-regression checks with configurable rules
+- Config-driven validation with Warning/Critical thresholds
+- Support for special rules (New/Deleted Requests, New/Deleted Fields)
+- 4-step logic for normal rules (field selection, transition matching, exception application, bloc_scope)
+
+Note: Coherence check is not applicable for DO Dashboard since organization
+counters are computed directly from request details (not from a separate API).
+"""
+
+import json
+import logging
+import os
+import shutil
+
+import openpyxl
+from rich.console import Console
+from do_dashboard_utils import get_nested_value, get_old_filename as _get_old_filename, get_config_path
+from do_dashboard_constants import (
+    REQUESTS_FILE_NAME,
+    ORGANIZATIONS_FILE_NAME,
+    OLD_FILE_SUFFIX,
+    DASHBOARD_CONFIG_FILE_NAME,
+    REGRESSION_CHECK_TABLE_NAME
+)
+
+
+# ============================================================================
+# MODULE CONFIGURATION
+# ============================================================================
+
+# Debug mode: Set to True to display detailed changes for each regression check rule
+debug_mode = False
+
+
+def enable_debug_mode():
+    """Enable debug mode to display detailed changes for each regression check rule."""
+    global debug_mode
+    debug_mode = True
+    if console:
+        console.print("[dim]DEBUG MODE enabled - detailed changes will be displayed[/dim]")
+
+
+# ============================================================================
+# MODULE DEPENDENCIES (injected from main module)
+# ============================================================================
+
+# Will be injected by the main module
+console = None
+
+# Regression check config is loaded on-demand via load_regression_check_config()
+regression_check_config = []
+
+# NOTE: File names and table names are imported from do_dashboard_constants.py (SINGLE SOURCE OF TRUTH):
+# - REQUESTS_FILE_NAME
+# - ORGANIZATIONS_FILE_NAME
+# - OLD_FILE_SUFFIX
+# - DASHBOARD_CONFIG_FILE_NAME
+# - REGRESSION_CHECK_TABLE_NAME
+
+
+def set_dependencies(console_instance):
+    """
+    Inject console instance from main module.
+
+    Args:
+        console_instance: Rich Console instance for formatted output
+    """
+    global console
+    console = console_instance
+
+
+# ============================================================================
+# CONFIGURATION LOADING
+# ============================================================================
+
+def load_regression_check_config(console_instance=None):
+    """Loads and validates the regression check configuration from the Excel file.
+
+    Args:
+        console_instance: Optional Rich Console instance. If not provided, uses global console.
+    """
+    global regression_check_config, console
+
+    if console_instance:
+        console = console_instance
+
+    config_path = os.path.join(get_config_path(), DASHBOARD_CONFIG_FILE_NAME)
+
+    try:
+        workbook = openpyxl.load_workbook(config_path)
+    except FileNotFoundError:
+        error_msg = f"Error: Configuration file not found at: {config_path}"
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    if REGRESSION_CHECK_TABLE_NAME not in workbook.sheetnames:
+        error_msg = f"Error: Sheet '{REGRESSION_CHECK_TABLE_NAME}' not found in the configuration file."
+        logging.critical(error_msg)
+        console.print(f"[bold red]{error_msg}[/bold red]")
+        raise Exception(error_msg)
+
+    sheet = workbook[REGRESSION_CHECK_TABLE_NAME]
+    headers = [cell.value for cell in sheet[1]]
+
+    temp_config = []
+
+    for row_index, row in enumerate(sheet.iter_rows(min_row=2, values_only=True), start=2):
+        rule_config = dict(zip(headers, row))
+
+        # Skip if ignore column contains "ignore" (case insensitive)
+        ignore_value = rule_config.get("ignore")
+        if ignore_value and isinstance(ignore_value, str) and "ignore" in ignore_value.lower():
+            continue
+
+        # Skip if all columns are None (empty row)
+        if all(value is None for value in row):
+            continue
+
+        # Validate bloc_title and line_label
+        bloc_title = rule_config.get("bloc_title")
+        line_label = rule_config.get("line_label")
+
+        if not bloc_title or not isinstance(bloc_title, str):
+            continue  # Skip rows without bloc_title (header separators, etc.)
+
+        if not line_label or not isinstance(line_label, str):
+            error_msg = f"Error in Regression_Check config, row {row_index}: 'line_label' is mandatory when 'bloc_title' is specified."
+            logging.critical(error_msg)
+            console.print(f"[bold red]{error_msg}[/bold red]")
+            raise Exception(error_msg)
+
+        # Validate thresholds
+        warning_threshold = rule_config.get("warning_threshold")
+        critical_threshold = rule_config.get("critical_threshold")
+
+        if warning_threshold is None or not isinstance(warning_threshold, (int, float)) or warning_threshold < 0:
+            error_msg = f"Error in Regression_Check config, row {row_index}: 'warning_threshold' must be a number >= 0."
+            logging.critical(error_msg)
+            console.print(f"[bold red]{error_msg}[/bold red]")
+            raise Exception(error_msg)
+
+        if critical_threshold is None or not isinstance(critical_threshold, (int, float)) or critical_threshold < 0:
+            error_msg = f"Error in Regression_Check config, row {row_index}: 'critical_threshold' must be a number >= 0."
+            logging.critical(error_msg)
+            console.print(f"[bold red]{error_msg}[/bold red]")
+            raise Exception(error_msg)
+
+        # Parse JSON fields
+        for json_field in ["field_selection", "transitions"]:
+            value = rule_config.get(json_field)
+            if value and isinstance(value, str):
+                try:
+                    rule_config[json_field] = json.loads(value)
+                except json.JSONDecodeError:
+                    error_msg = f"Error in Regression_Check config, row {row_index}, field '{json_field}': Invalid JSON format."
+                    logging.critical(error_msg)
+                    console.print(f"[bold red]{error_msg}[/bold red]")
+                    raise Exception(error_msg)
+            elif value is None:
+                rule_config[json_field] = None
+
+        # Validate field_selection format
+        field_selection = rule_config.get("field_selection")
+
+        # Special rules that don't use field_selection
+        special_rules_no_selection = ["New Fields", "Deleted Fields", "Deleted Requests"]
+
+        if line_label not in special_rules_no_selection:
+            # Standard rules and "New Requests" MUST have field_selection
+            if field_selection is None:
+                error_msg = f"Error in Regression_Check config, row {row_index}: 'field_selection' is mandatory for rule '{line_label}'."
+                logging.critical(error_msg)
+                console.print(f"[bold red]{error_msg}[/bold red]")
+                raise Exception(error_msg)
+
+            if not isinstance(field_selection, list):
+                console.print(f"[yellow]⚠ Row {row_index}: 'field_selection' must be a JSON array of [action, selector] pairs, skipping rule[/yellow]")
+                rule_config["_config_error"] = True
+            else:
+                for step_idx, step in enumerate(field_selection):
+                    if not isinstance(step, list) or len(step) != 2:
+                        console.print(f"[yellow]⚠ Row {row_index}: field_selection[{step_idx}] must be array of 2 elements [action, selector], skipping rule[/yellow]")
+                        rule_config["_config_error"] = True
+                        break
+
+                    action, field_selector = step
+
+                    if action not in ["include", "exclude"]:
+                        console.print(f"[yellow]⚠ Row {row_index}: field_selection[{step_idx}] action must be 'include' or 'exclude', got '{action}', skipping rule[/yellow]")
+                        rule_config["_config_error"] = True
+                        break
+
+                    if not isinstance(field_selector, str) or "." not in field_selector:
+                        console.print(f"[yellow]⚠ Row {row_index}: field_selection[{step_idx}] selector must be string with dot notation (e.g., '*.*', 'group.*', 'group.field'), got '{field_selector}', skipping rule[/yellow]")
+                        rule_config["_config_error"] = True
+                        break
+        else:
+            if field_selection is not None and field_selection != [] and field_selection != "":
+                console.print(f"[yellow]⚠ Row {row_index}: Special rule '{line_label}' should have empty field_selection, got {field_selection}[/yellow]")
+                rule_config["_config_error"] = True
+
+        # Validate bloc_scope
+        bloc_scope = rule_config.get("bloc_scope")
+        if bloc_scope is not None and bloc_scope not in ["all", "any"]:
+            error_msg = f"Error in Regression_Check config, row {row_index}: 'bloc_scope' must be 'all' or 'any'."
+            logging.critical(error_msg)
+            console.print(f"[bold red]{error_msg}[/bold red]")
+            raise Exception(error_msg)
+
+        # Validate transitions format
+        transitions = rule_config.get("transitions")
+        config_error = False
+
+        if transitions is not None:
+            if not isinstance(transitions, list):
+                console.print(f"[yellow]⚠ Row {row_index}: 'transitions' must be a JSON array, skipping this rule[/yellow]")
+                config_error = True
+            else:
+                for step_idx, transition_step in enumerate(transitions):
+                    if not isinstance(transition_step, list) or len(transition_step) != 4:
+                        console.print(f"[yellow]⚠ Row {row_index}: transitions[{step_idx}] must be array of 4 elements [action, field_selector, from, to], skipping[/yellow]")
+                        config_error = True
+                        break
+
+                    action, field_selector, from_val, to_val = transition_step
+
+                    if action not in ["include", "exclude"]:
+                        console.print(f"[yellow]⚠ Row {row_index}: transitions[{step_idx}] action must be 'include' or 'exclude', got '{action}', skipping[/yellow]")
+                        config_error = True
+                        break
+
+                    if not isinstance(field_selector, str) or "." not in field_selector:
+                        console.print(f"[yellow]⚠ Row {row_index}: transitions[{step_idx}] field_selector must be string with dot notation, got '{field_selector}', skipping[/yellow]")
+                        config_error = True
+                        break
+
+        if config_error:
+            rule_config["_config_error"] = True
+
+        temp_config.append(rule_config)
+
+    regression_check_config = temp_config
+    console.print(f"Loaded {len(regression_check_config)} regression check rules.", style="green")
+
+
+def run_check_only_mode(sys_argv):
+    """
+    Orchestrates CHECK_ONLY and CHECK_ONLY_COMPARE modes.
+
+    - CHECK_ONLY: Full non-regression validation on existing files
+    - CHECK_ONLY_COMPARE: Regression-only comparison of two specific files
+
+    Args:
+        sys_argv: sys.argv from main script (to parse command-line arguments)
+    """
+    global console
+
+    if console is None:
+        console = Console()
+
+    print()
+
+    # Detect CHECK_ONLY_COMPARE mode: --check-only <file1> <file2>
+    if len(sys_argv) >= 4:
+        current_file = sys_argv[2]
+        old_file = sys_argv[3]
+
+        console.print("[bold cyan]═══ CHECK ONLY COMPARE MODE ═══[/bold cyan]")
+        console.print(f"Comparing two specific files:\n")
+        console.print(f"  Current: [bold]{current_file}[/bold]")
+        console.print(f"  Old:     [bold]{old_file}[/bold]\n")
+
+        print()
+        load_regression_check_config(console)
+
+        print()
+        has_regression_critical = run_quality_checks(
+            current_requests=current_file,
+            old_requests_filename=old_file
+        )
+
+        if has_regression_critical:
+            console.print("[bold red]✗ CRITICAL issues detected![/bold red]")
+        else:
+            console.print("[bold green]✓ All checks passed successfully![/bold green]")
+
+    else:
+        console.print("[bold cyan]═══ CHECK ONLY MODE ═══[/bold cyan]")
+        console.print("Running quality checks on existing data files without collecting new data.\n")
+
+        print()
+        load_regression_check_config(console)
+
+        print()
+        old_requests_file = _get_old_filename(REQUESTS_FILE_NAME, OLD_FILE_SUFFIX)
+        has_regression_critical = run_quality_checks(
+            current_requests=REQUESTS_FILE_NAME,
+            old_requests_filename=old_requests_file
+        )
+
+        if has_regression_critical:
+            console.print("[bold red]✗ CRITICAL issues detected![/bold red]")
+        else:
+            console.print("[bold green]✓ All checks passed successfully![/bold green]")
+
+
+# ============================================================================
+# FILE UTILITIES
+# ============================================================================
+
+def load_json_file(filename):
+    """
+    Loads a JSON file (requests, organizations, or any JSON data).
+    Returns the parsed JSON data or None if file doesn't exist or error occurred.
+    """
+    if os.path.exists(filename):
+        try:
+            with open(filename, 'r', encoding='utf-8') as f:
+                return json.load(f)
+        except Exception as e:
+            logging.warning(f"Could not load JSON file '{filename}': {e}")
+            console.print(f"[yellow]⚠ Warning: Could not load JSON file '{filename}': {e}[/yellow]")
+    return None
+
+
+def backup_output_files():
+    """
+    Silently backups current output files before writing new versions.
+    Called AFTER all checks pass to avoid losing history on crash.
+    """
+    def _backup_file_silent(source, destination):
+        if os.path.exists(source):
+            try:
+                shutil.copy2(source, destination)
+            except Exception as e:
+                logging.warning(f"Could not backup {source}: {e}")
+
+    _backup_file_silent(REQUESTS_FILE_NAME, _get_old_filename(REQUESTS_FILE_NAME, OLD_FILE_SUFFIX))
+    _backup_file_silent(ORGANIZATIONS_FILE_NAME, _get_old_filename(ORGANIZATIONS_FILE_NAME, OLD_FILE_SUFFIX))
+
+
+# ============================================================================
+# QUALITY CHECKS ORCHESTRATION
+# ============================================================================
+
+def run_quality_checks(current_requests, old_requests_filename):
+    """
+    Runs non-regression quality checks on requests data.
+
+    Note: Coherence check is not applicable for DO Dashboard since organization
+    counters are computed from request details, not from a separate API.
+
+    Args:
+        current_requests: Either a filename (str) to load requests from,
+                          or a list of request dictionaries (already in memory)
+        old_requests_filename: Filename of old requests for regression comparison (str)
+
+    Returns:
+        has_regression_critical (bool)
+
+    Usage:
+        - Normal mode:
+          run_quality_checks(
+              current_requests=output_requests,       # list (in memory)
+              old_requests_filename=REQUESTS_FILE_NAME  # str (current file on disk)
+          )
+
+        - Check-only mode:
+          run_quality_checks(
+              current_requests=REQUESTS_FILE_NAME,    # str (current file)
+              old_requests_filename=get_old_filename(REQUESTS_FILE_NAME)  # str (old file)
+          )
+    """
+    global console, regression_check_config
+
+    if not regression_check_config:
+        if console is None:
+            console = Console()
+        load_regression_check_config(console)
+
+    console.print("[bold cyan]══════════════════════════════════════════════════[/bold cyan]")
+
+    # Load current_requests if it's a filename
+    if isinstance(current_requests, str):
+        current_requests_data = load_json_file(current_requests)
+        if current_requests_data is None:
+            console.print(f"[bold red]Error: Could not load current requests from '{current_requests}'[/bold red]")
+            return True
+    elif isinstance(current_requests, list):
+        current_requests_data = current_requests
+    else:
+        console.print(f"[bold red]Error: current_requests must be either a filename (str) or a list of requests[/bold red]")
+        return True
+
+    # Run non-regression check
+    has_regression_critical = non_regression_check(current_requests_data, old_requests_filename)
+
+    console.print("[bold cyan]══════════════════════════════════════════════════[/bold cyan]")
+    print()
+
+    return has_regression_critical
+
+
+# ============================================================================
+# NON-REGRESSION CHECK
+# ============================================================================
+
+def non_regression_check(output_requests, old_requests_filename):
+    """
+    Comprehensive config-driven non-regression check comparing current vs old requests.
+    Uses rules from regression_check_config loaded from Excel.
+    Returns True if any critical issue was found, False otherwise.
+
+    Args:
+        output_requests: Current requests data (list)
+        old_requests_filename: Filename of old requests JSON file to load
+    """
+    console.print("\n[bold]═══ Non Regression Check ═══[/bold]\n")
+
+    console.print(f"[dim]Loading old requests from: {old_requests_filename}[/dim]")
+    old_requests = load_json_file(old_requests_filename)
+
+    if old_requests is None:
+        console.print(f"[yellow]⚠ No old requests file found at '{old_requests_filename}', skipping non-regression check[/yellow]")
+        return False
+
+    has_critical = False
+
+    # ========== INTERNAL UTILITY FUNCTIONS ==========
+
+    def _is_undefined(value):
+        return value in [None, "", "undefined"]
+
+    def _values_are_equal(val1, val2):
+        if _is_undefined(val1) and _is_undefined(val2):
+            return True
+        return val1 == val2
+
+    def _apply_pipeline_step(checked_fields, action, field_selector, from_pattern, to_pattern):
+        for i, field_record in enumerate(checked_fields):
+            group_name, field_name, old_val, new_val, is_checked = field_record
+            if not _field_selector_matches_pattern(field_selector, group_name, field_name):
+                continue
+            if _transition_matches(old_val, new_val, from_pattern, to_pattern):
+                if action == "include":
+                    checked_fields[i][4] = True
+                elif action == "exclude":
+                    checked_fields[i][4] = False
+
+    def _transition_matches(old_val, new_val, expected_old, expected_new):
+        if expected_old == "*undefined":
+            old_matches = old_val in [None, "", "undefined"]
+        elif expected_old == "*defined":
+            old_matches = old_val not in [None, "", "undefined"]
+        elif expected_old == "*":
+            old_matches = True
+        else:
+            old_matches = (old_val == expected_old)
+
+        if expected_new == "*undefined":
+            new_matches = new_val in [None, "", "undefined"]
+        elif expected_new == "*defined":
+            new_matches = new_val not in [None, "", "undefined"]
+        elif expected_new == "*":
+            new_matches = True
+        else:
+            new_matches = (new_val == expected_new)
+
+        return old_matches and new_matches
+
+    def _get_status_and_style(count, warning_threshold, critical_threshold):
+        nonlocal has_critical
+        if count > critical_threshold:
+            has_critical = True
+            return "CRITICAL", "red", "✗"
+        elif count > warning_threshold:
+            return "WARNING", "yellow", "⚠"
+        else:
+            return "OK", "green", "✓"
+
+    def _print_block_header(title, status_tuple, indent=0):
+        indent_str = "  " * indent
+        status, color, emoji = status_tuple
+        console.print(f"{indent_str}{emoji} [{color}][bold]{title}[/bold][/{color}]")
+
+    def _print_check_line(message, count, status_tuple, indent=1):
+        indent_str = "  " * indent
+        status, color, emoji = status_tuple
+        console.print(f"{indent_str}{emoji} [{color}]{message}: {count}[/{color}]")
+
+    def _calculate_block_status(line_statuses):
+        if any(s[0] == "CRITICAL" for s in line_statuses):
+            return ("CRITICAL", "red", "✗")
+        elif any(s[0] == "WARNING" for s in line_statuses):
+            return ("WARNING", "yellow", "⚠")
+        else:
+            return ("OK", "green", "✓")
+
+    def _field_selector_matches_pattern(selector, group_name, field_name):
+        if selector == "*.*":
+            return True
+        sel_group, sel_field = selector.split(".", 1)
+        if sel_group != "*" and sel_group != group_name:
+            return False
+        if sel_field == "*":
+            return True
+        return sel_field == field_name
+
+    def _apply_field_selection_pipeline(all_fields, field_selection_config):
+        candidate_fields = set()
+        if not field_selection_config:
+            return candidate_fields
+        for action, field_selector in field_selection_config:
+            for group_name, field_name in all_fields:
+                if _field_selector_matches_pattern(field_selector, group_name, field_name):
+                    if action == "include":
+                        candidate_fields.add((group_name, field_name))
+                    elif action == "exclude":
+                        candidate_fields.discard((group_name, field_name))
+        return candidate_fields
+
+    def _get_key_field_from_new_requests_rule(rule, new_requests_list, old_requests_list):
+        if not new_requests_list or not old_requests_list:
+            raise ValueError("Cannot determine key field: empty request lists")
+
+        new_req = new_requests_list[0]
+        old_req = old_requests_list[0]
+
+        candidate_fields = _build_candidate_fields(new_req, old_req, rule.get("field_selection"))
+
+        if not candidate_fields:
+            raise ValueError(
+                f"field_selection produced no candidate fields. "
+                f"Config: {rule.get('field_selection')}"
+            )
+
+        for group_name, field_name in sorted(candidate_fields):
+            new_val = get_nested_value(new_req, [group_name, field_name])
+            old_val = get_nested_value(old_req, [group_name, field_name])
+            if new_val is not None and old_val is not None:
+                return field_name, group_name
+
+        raise ValueError(
+            f"No field in field_selection has values in both first new and old request. "
+            f"Candidates from pipeline: {candidate_fields}. "
+            f"Verify field_selection config or data has proper values."
+        )
+
+    def _build_requests_dict(requests_list, key_field, field_group):
+        result = {}
+        for request in requests_list:
+            key = get_nested_value(request, [field_group, key_field])
+            if key:
+                result[key] = request
+        return result
+
+    def _matches_transition(old_val, new_val, transitions_config):
+        if transitions_config is None:
+            return False
+        for transition in transitions_config:
+            expected_old, expected_new = transition
+            if _transition_matches(old_val, new_val, expected_old, expected_new):
+                return True
+        return False
+
+    def _process_special_rule(rule, line_label, new_dict, old_dict):
+        if line_label == "New Requests":
+            return len(set(new_dict.keys()) - set(old_dict.keys()))
+        elif line_label == "Deleted Requests":
+            return len(set(old_dict.keys()) - set(new_dict.keys()))
+        else:
+            return 0
+
+    def _process_new_deleted_fields(line_label, new_dict, old_dict):
+        field_counts = {}
+        common_keys = sorted(set(new_dict.keys()) & set(old_dict.keys()))
+
+        for key in common_keys:
+            new_req = new_dict[key]
+            old_req = old_dict[key]
+
+            all_groups = sorted(set(new_req.keys()) | set(old_req.keys()))
+
+            for group_name in all_groups:
+                new_group = new_req.get(group_name, {})
+                old_group = old_req.get(group_name, {})
+
+                if not isinstance(new_group, dict):
+                    new_group = {}
+                if not isinstance(old_group, dict):
+                    old_group = {}
+
+                new_fields = set(new_group.keys())
+                old_fields = set(old_group.keys())
+
+                if line_label == "New Fields":
+                    changed_fields = sorted(new_fields - old_fields)
+                elif line_label == "Deleted Fields":
+                    changed_fields = sorted(old_fields - new_fields)
+                else:
+                    changed_fields = []
+
+                for field_name in changed_fields:
+                    qualified_name = f"{group_name}.{field_name}"
+                    field_counts[qualified_name] = field_counts.get(qualified_name, 0) + 1
+
+        return sorted(field_counts.items(), key=lambda x: (-x[1], x[0]))
+
+    def _build_candidate_fields(new_req, old_req, field_selection_config):
+        common_groups = sorted(set(new_req.keys()) & set(old_req.keys()))
+        all_available_fields = []
+
+        for group_name in common_groups:
+            new_group = new_req.get(group_name, {})
+            old_group = old_req.get(group_name, {})
+
+            if not isinstance(new_group, dict):
+                new_group = {}
+            if not isinstance(old_group, dict):
+                old_group = {}
+
+            common_field_names = sorted(set(new_group.keys()) & set(old_group.keys()))
+            for field_name in common_field_names:
+                all_available_fields.append((group_name, field_name))
+
+        if not field_selection_config:
+            return []
+
+        candidate_fields = _apply_field_selection_pipeline(all_available_fields, field_selection_config)
+        return sorted(candidate_fields, key=lambda x: (x[0], x[1]))
+
+    def _process_rule(rule, new_dict, old_dict):
+        if rule.get("_config_error"):
+            return 0, []
+
+        field_selection_config = rule.get("field_selection")
+        bloc_scope = rule.get("bloc_scope") or "any"
+
+        common_keys = sorted(set(new_dict.keys()) & set(old_dict.keys()))
+        matching_requests_count = 0
+        details_list = []
+
+        for key in common_keys:
+            new_req = new_dict[key]
+            old_req = old_dict[key]
+
+            candidate_fields = _build_candidate_fields(new_req, old_req, field_selection_config)
+
+            if not candidate_fields:
+                continue
+
+            all_fields_list = []
+            changed_fields = []
+
+            for group_name, field_name in candidate_fields:
+                new_val = get_nested_value(new_req, [group_name, field_name])
+                old_val = get_nested_value(old_req, [group_name, field_name])
+
+                field_has_changed = not _values_are_equal(old_val, new_val)
+                if field_has_changed:
+                    changed_fields.append((group_name, field_name))
+                    all_fields_list.append([group_name, field_name, old_val, new_val, False])
+
+            transitions_config = rule.get("transitions", [])
+            if transitions_config and isinstance(transitions_config, list):
+                for action, field_selector, from_val, to_val in transitions_config:
+                    _apply_pipeline_step(all_fields_list, action, field_selector, from_val, to_val)
+
+            checked_fields = [(f[0], f[1], f[2], f[3]) for f in all_fields_list if f[4]]
+
+            inclusion_matches = False
+            if bloc_scope == "all":
+                if len(changed_fields) > 0 and len(checked_fields) == len(changed_fields):
+                    inclusion_matches = True
+            else:  # bloc_scope == "any"
+                if len(checked_fields) > 0:
+                    inclusion_matches = True
+
+            if inclusion_matches:
+                matching_requests_count += 1
+                if debug_mode and checked_fields:
+                    field_changes = [(f"{gn}.{fn}", ov, nv) for gn, fn, ov, nv in checked_fields]
+                    details_list.append((key, field_changes))
+
+        return matching_requests_count, details_list
+
+    # ========== MAIN LOGIC ==========
+
+    key_field = None
+    field_group = None
+
+    for rule in regression_check_config:
+        if rule.get("line_label") == "New Requests":
+            try:
+                key_field, field_group = _get_key_field_from_new_requests_rule(
+                    rule,
+                    output_requests,
+                    old_requests
+                )
+                break
+            except ValueError as e:
+                console.print(f"[bold red]Error determining key field: {e}[/bold red]")
+                return True
+
+    if not key_field:
+        console.print("[bold red]Error: 'New Requests' rule not found or has no valid field_selection[/bold red]")
+        return True
+
+    console.print(f"[dim]Using key field: {field_group}.{key_field}[/dim]\n")
+
+    new_dict = _build_requests_dict(output_requests, key_field, field_group)
+    old_dict = _build_requests_dict(old_requests, key_field, field_group)
+
+    # Group rules by bloc_title, preserving order of first appearance
+    blocs = {}
+    bloc_order = []
+    for rule in regression_check_config:
+        bloc_title = rule["bloc_title"]
+        if bloc_title not in blocs:
+            blocs[bloc_title] = []
+            bloc_order.append(bloc_title)
+        blocs[bloc_title].append(rule)
+
+    for bloc_title in bloc_order:
+        rules = blocs[bloc_title]
+        line_results = []
+
+        for rule in rules:
+            line_label = rule["line_label"]
+
+            if line_label in ["New Requests", "Deleted Requests"]:
+                count = _process_special_rule(rule, line_label, new_dict, old_dict)
+                line_results.append((line_label, count, None, "simple"))
+
+            elif line_label in ["New Fields", "Deleted Fields"]:
+                field_list = _process_new_deleted_fields(line_label, new_dict, old_dict)
+                count = len(field_list)
+                line_results.append((line_label, count, field_list, "fields"))
+
+            else:
+                count, details = _process_rule(rule, new_dict, old_dict)
+                line_results.append((line_label, count, details, "details"))
+
+        # Calculate status for each line
+        line_results_with_status = []
+        for line_label, count, data, result_type in line_results:
+            rule = next(r for r in rules if r["line_label"] == line_label)
+            warning_threshold = rule["warning_threshold"]
+            critical_threshold = rule["critical_threshold"]
+            status_tuple = _get_status_and_style(count, warning_threshold, critical_threshold)
+            line_results_with_status.append((line_label, count, data, result_type, status_tuple))
+
+        bloc_status = _calculate_block_status([result[4] for result in line_results_with_status])
+        _print_block_header(bloc_title, bloc_status, indent=0)
+
+        for line_label, count, data, result_type, status_tuple in line_results_with_status:
+            should_display = (bloc_title == "Structure") or (status_tuple[0] != "OK")
+
+            if should_display:
+                if result_type == "fields":
+                    _print_check_line(line_label, count, status_tuple, indent=1)
+                    for field_name, request_count in data:
+                        console.print(f"    {field_name} ({request_count} requests)")
+
+                elif result_type == "details":
+                    _print_check_line(line_label, count, status_tuple, indent=1)
+                    if debug_mode and data and len(data) > 0:
+                        for request_key, field_changes in data:
+                            console.print(f"      [dim]{key_field}: {request_key}[/dim]")
+                            for qualified_field, old_val, new_val in field_changes:
+                                old_display = f"'{old_val}'" if isinstance(old_val, str) else str(old_val)
+                                new_display = f"'{new_val}'" if isinstance(new_val, str) else str(new_val)
+                                console.print(f"        - {qualified_field}: {old_display} → {new_display}")
+
+                else:
+                    _print_check_line(line_label, count, status_tuple, indent=1)
+
+        console.print()
+
+    return has_critical
diff --git a/do_dashboard_utils.py b/do_dashboard_utils.py
new file mode 100644
index 0000000..85b9129
--- /dev/null
+++ b/do_dashboard_utils.py
@@ -0,0 +1,221 @@
+"""
+DO Dashboard - Utility Functions Module
+
+This module contains generic utility functions used throughout the DO Dashboard:
+- HTTP client management (thread-safe)
+- Nested data structure navigation with wildcard support
+- Configuration path resolution (script vs PyInstaller)
+- Thread position management for progress bars
+- Filename generation utilities
+"""
+
+import os
+import sys
+import threading
+
+import httpx
+
+from do_dashboard_constants import CONFIG_FOLDER_NAME
+
+
+# ============================================================================
+# GLOBAL VARIABLES (managed by main module)
+# ============================================================================
+thread_local_storage = threading.local()
+
+
+def run_with_context(func, context, *args, **kwargs):
+    """
+    Wrapper to set thread-local context before running a function in a new thread.
+    Useful for ThreadPoolExecutor where context is lost.
+    """
+    thread_local_storage.current_request_context = context
+    return func(*args, **kwargs)
+
+
+# These will be set/accessed from the main module
+httpx_clients = {}
+_clients_lock = threading.Lock()
+threads_list = []
+_threads_list_lock = threading.Lock()
+
+
+# ============================================================================
+# HTTP CLIENT MANAGEMENT
+# ============================================================================
+
+def get_httpx_client() -> httpx.Client:
+    """
+    Get or create thread-local HTTP client.
+    Keep-alive is disabled to avoid stale connections with load balancers.
+    """
+    global httpx_clients
+    thread_id = threading.get_ident()
+
+    with _clients_lock:
+        if thread_id not in httpx_clients:
+            # Create client with keep-alive disabled
+            httpx_clients[thread_id] = httpx.Client(
+                headers={"Connection": "close"},  # Explicitly request closing
+                limits=httpx.Limits(max_keepalive_connections=0, max_connections=100)
+            )
+        return httpx_clients[thread_id]
+
+
+def clear_httpx_client():
+    """
+    Removes the current thread's client from the cache.
+    Ensures a fresh client (and socket pool) will be created on the next call.
+    """
+    global httpx_clients
+    thread_id = threading.get_ident()
+    with _clients_lock:
+        if thread_id in httpx_clients:
+            try:
+                httpx_clients[thread_id].close()
+            except:
+                pass
+            del httpx_clients[thread_id]
+
+
+def get_thread_position():
+    """
+    Get the position of the current thread in the threads list.
+    Used for managing progress bar positions in multithreaded environment.
+    """
+    global threads_list
+    thread_id = threading.get_ident()
+    with _threads_list_lock:
+        if thread_id not in threads_list:
+            threads_list.append(thread_id)
+            return len(threads_list) - 1
+        else:
+            return threads_list.index(thread_id)
+
+
+# ============================================================================
+# NESTED DATA NAVIGATION
+# ============================================================================
+
+def get_nested_value(data_structure, path, default=None):
+    """
+    Extracts a value from a nested structure of dictionaries and lists.
+    Supports a wildcard '*' in the path to retrieve all elements from a list.
+
+    Args:
+        data_structure: The nested dict/list structure to navigate
+        path: List of keys/indices to follow. Use '*' for list wildcard.
+        default: Value to return if path not found
+
+    Returns:
+        The value at the end of the path, or default if not found
+
+    Examples:
+        get_nested_value({"a": {"b": 1}}, ["a", "b"]) -> 1
+        get_nested_value({"items": [{"x": 1}, {"x": 2}]}, ["items", "*", "x"]) -> [1, 2]
+    """
+    if data_structure is None:
+        return "$$$$ No Data"
+    if not path:
+        return default
+
+    if "*" in path:
+        wildcard_index = path.index("*")
+        path_before = path[:wildcard_index]
+        path_after = path[wildcard_index + 1:]
+
+        def _get_simple_nested_value(ds, p, d):
+            cl = ds
+            for k in p:
+                if isinstance(cl, dict):
+                    cl = cl.get(k)
+                elif isinstance(cl, list):
+                    try:
+                        if isinstance(k, int) and -len(cl) <= k < len(cl):
+                            cl = cl[k]
+                        else:
+                            return d
+                    except (IndexError, TypeError):
+                        return d
+                else:
+                    return d
+                if cl is None:
+                    return d
+            return cl
+
+        base_level = _get_simple_nested_value(data_structure, path_before, default)
+
+        if not isinstance(base_level, list):
+            return default
+
+        results = []
+        for item in base_level:
+            value = get_nested_value(item, path_after, default)
+            if value is not default and value != "$$$$ No Data":
+                results.append(value)
+
+        # Flatten the results by one level to handle multiple wildcards
+        final_results = []
+        for res in results:
+            if isinstance(res, list):
+                final_results.extend(res)
+            else:
+                final_results.append(res)
+
+        return final_results
+
+    # No wildcard, original logic (iterative)
+    current_level = data_structure
+    for key_or_index in path:
+        if isinstance(current_level, dict):
+            current_level = current_level.get(key_or_index)
+            if current_level is None:
+                return default
+        elif isinstance(current_level, list):
+            try:
+                if isinstance(key_or_index, int) and -len(current_level) <= key_or_index < len(current_level):
+                    current_level = current_level[key_or_index]
+                else:
+                    return default
+            except (IndexError, TypeError):
+                return default
+        else:
+            return default
+    return current_level
+
+
+# ============================================================================
+# CONFIGURATION UTILITIES
+# ============================================================================
+
+def get_config_path():
+    """
+    Gets the correct path to the config folder.
+    Works for both script execution and PyInstaller executable.
+
+    Returns:
+        Path to config folder
+    """
+    if getattr(sys, 'frozen', False):
+        # Running as a PyInstaller bundle
+        config_folder = CONFIG_FOLDER_NAME
+        return os.path.join(sys._MEIPASS, config_folder)
+    else:
+        # Running as a script
+        return CONFIG_FOLDER_NAME
+
+
+def get_old_filename(current_filename, old_suffix="_old"):
+    """Generate old backup filename from current filename.
+
+    Example: "do_requests.json" -> "do_requests_old.json"
+
+    Args:
+        current_filename: Current file name (e.g., "do_requests.json")
+        old_suffix: Suffix to append before file extension (default: "_old")
+
+    Returns:
+        Old backup filename with suffix before extension
+    """
+    name, ext = os.path.splitext(current_filename)
+    return f"{name}{old_suffix}{ext}"