{
  "sessionId": "4c0f4b2a-9f2e-42b2-933f-5413cadea81c",
  "projectHash": "c4ece9c032ac20d038bbd73e9aa5f86cb3fd24c826b8e99b6edcd77db288fcb1",
  "startTime": "2026-03-03T11:45:32.754Z",
  "lastUpdated": "2026-03-03T11:46:06.088Z",
  "messages": [
    {
      "id": "c3bc1f9c-8758-4d8f-b93d-19b5d5a68f35",
      "timestamp": "2026-03-03T11:45:32.754Z",
      "type": "user",
      "content": [
        {
          "text": "make @avg_bandwidth_12months.py export to google sheet"
        },
        {
          "text": "\n--- Content from referenced files ---"
        },
        {
          "text": "\nContent from @avg_bandwidth_12months.py:\n"
        },
        {
          "text": "import boto3\nfrom datetime import datetime\nfrom dateutil.relativedelta import relativedelta\nfrom aws_utils import get_account_names, get_boto_session\n\ndef get_average_bandwidth_report():\n    session = get_boto_session()\n    ce_client = session.client('ce')\n    \n    all_accounts = get_account_names()\n    if not all_accounts:\n        print(\"Could not retrieve account list. Check Organizations permissions.\")\n        return\n\n    # Set dates for the last 12 full months\n    now = datetime.now()\n    first_day_current_month = now.replace(day=1)\n    end_date = first_day_current_month.strftime('%Y-%m-%d')\n    start_date = (first_day_current_month - relativedelta(months=12)).strftime('%Y-%m-%d')\n\n    # Initialize tracking: {acc_id: {'usage': 0.0, 'cost': 0.0}}\n    account_totals = {acc_id: {'usage': 0.0, 'cost': 0.0} for acc_id in all_accounts.keys()}\n    \n    next_token = None\n\n    try:\n        while True:\n            params = {\n                'TimePeriod': {'Start': start_date, 'End': end_date},\n                'Granularity': 'MONTHLY',\n                'Metrics': ['UsageQuantity', 'UnblendedCost'],\n                'GroupBy': [\n                    {'Type': 'DIMENSION', 'Key': 'LINKED_ACCOUNT'},\n                    {'Type': 'DIMENSION', 'Key': 'USAGE_TYPE'}\n                ]\n            }\n            if next_token:\n                params['NextPageToken'] = next_token\n\n            response = ce_client.get_cost_and_usage(**params)\n\n            for result in response['ResultsByTime']:\n                for group in result['Groups']:\n                    acc_id = group['Keys'][0]\n                    usage_type = group['Keys'][1]\n                    usage_amount = float(group['Metrics']['UsageQuantity']['Amount'])\n                    unit = group['Metrics']['UsageQuantity']['Unit']\n                    cost_amount = float(group['Metrics']['UnblendedCost']['Amount'])\n\n                    # Bandwidth calculation logic from bwsuage.py\n                    if \"DataTransfer\" in usage_type:\n                        if unit == 'Bytes':\n                            usage_amount /= (1024**3)\n                        elif unit in ['MB', 'Megabytes']:\n                            usage_amount /= 1024\n                        \n                        if acc_id not in account_totals:\n                            account_totals[acc_id] = {'usage': 0.0, 'cost': 0.0}\n                        \n                        account_totals[acc_id]['usage'] += usage_amount\n                        account_totals[acc_id]['cost'] += cost_amount\n\n            next_token = response.get('NextPageToken')\n            if not next_token:\n                break\n\n        print(f\"\\n--- 12-Month Average Bandwidth & Cost Report ---\")\n        print(f\"Period: {start_date} to {end_date}\")\n        print(f\"{'Account Name':<25} | {'Avg GB':<10} | {'Avg Cost ($)':<12} | {'12m Total ($)'}\")\n        print(\"-\" * 80)\n\n        # Sort by total cost descending\n        sorted_accounts = sorted(\n            account_totals.items(), \n            key=lambda x: x[1]['cost'], \n            reverse=True\n        )\n        \n        for acc_id, totals in sorted_accounts:\n            acc_name = all_accounts.get(acc_id, f\"Deleted/Unknown ({acc_id})\")\n            avg_usage = totals['usage'] / 12.0\n            avg_cost = totals['cost'] / 12.0\n            total_cost = totals['cost']\n            \n            print(f\"{acc_name[:25]:<25} | {avg_usage:>10.2f} | {avg_cost:>12.2f} | {total_cost:>13.2f}\")\n\n        print(f\"\\nTotal Accounts Scanned: {len(all_accounts)}\")\n\n    except Exception as e:\n        print(f\"Error: {e}\")\n\nif __name__ == \"__main__\":\n    get_average_bandwidth_report()"
        },
        {
          "text": "\n--- End of content ---"
        }
      ],
      "displayContent": [
        {
          "text": "make @avg_bandwidth_12months.py export to google sheet"
        }
      ]
    },
    {
      "id": "631dd684-8e81-4641-90b5-56952bbbcbb4",
      "timestamp": "2026-03-03T11:45:35.796Z",
      "type": "gemini",
      "content": "I will read `aws_utils.py` to confirm the signature and usage of the `export_to_sheets` function.",
      "thoughts": [
        {
          "subject": "Initiating Google Sheets Integration",
          "description": "I'm now zeroing in on integrating the Google Sheets export functionality. My plan is to call `export_to_sheets` from `avg_bandwidth_12months.py`.  I'll need to figure out how to structure the data from the script into the `title`, `headers`, and `rows` arguments expected by the function.",
          "timestamp": "2026-03-03T11:45:34.867Z"
        },
        {
          "subject": "Verifying `export_to_sheets` Function",
          "description": "I've begun examining `aws_utils.py` to understand `export_to_sheets`'s requirements. This is key for correctly passing data from `avg_bandwidth_12months.py`. Next, I'll focus on how the report data in `avg_bandwidth_12months.py` is formatted so I can prepare the `headers` and `rows` data structures.",
          "timestamp": "2026-03-03T11:45:35.676Z"
        }
      ],
      "tokens": {
        "input": 16644,
        "output": 43,
        "cached": 3264,
        "thoughts": 192,
        "tool": 0,
        "total": 16879
      },
      "model": "gemini-3-flash-preview",
      "toolCalls": [
        {
          "id": "read_file_1772538335795_0",
          "name": "read_file",
          "args": {
            "file_path": "aws_utils.py"
          },
          "result": [
            {
              "functionResponse": {
                "id": "read_file_1772538335795_0",
                "name": "read_file",
                "response": {
                  "output": "import boto3\nimport json\nimport os\nimport subprocess\nimport time\nfrom datetime import datetime, date\nfrom dateutil.relativedelta import relativedelta\n\n# Attempt to load .env file if python-dotenv is installed\ntry:\n    from dotenv import load_dotenv\n    load_dotenv()\nexcept ImportError:\n    pass\n\n# --- GOOGLE SHEETS CONFIG ---\ndef get_google_client_secret_file():\n    return os.getenv('GOOGLE_CLIENT_SECRET_FILE', 'client_secret.json')\n\ndef get_google_authorized_user_file():\n    return os.getenv('GOOGLE_AUTHORIZED_USER_FILE', 'authorized_user.json')\n\nSCOPES = [\n    'https://www.googleapis.com/auth/spreadsheets',\n    'https://www.googleapis.com/auth/drive'\n]\n\ndef get_google_auth():\n    \"\"\"Authenticates with Google Sheets API.\"\"\"\n    import gspread\n    from google_auth_oauthlib.flow import InstalledAppFlow\n    from google.auth.transport.requests import Request\n    from google.oauth2.credentials import Credentials\n\n    creds = None\n    auth_user_file = get_google_authorized_user_file()\n    client_secret_file = get_google_client_secret_file()\n\n    if os.path.exists(auth_user_file):\n        creds = Credentials.from_authorized_user_file(auth_user_file, SCOPES)\n    \n    if not creds or not creds.valid:\n        if creds and creds.expired and creds.refresh_token:\n            creds.refresh(Request())\n        else:\n            if not os.path.exists(client_secret_file):\n                print(f\"Warning: {client_secret_file} not found. Google Sheets export will be skipped.\")\n                return None\n            flow = InstalledAppFlow.from_client_secrets_file(client_secret_file, SCOPES)\n            creds = flow.run_local_server(port=0)\n        with open(auth_user_file, 'w') as token:\n            token.write(creds.to_json())\n    \n    return gspread.authorize(creds)\n\ndef export_to_sheets(title, headers, rows):\n    \"\"\"\n    Creates a Google Sheet and populates it with headers and rows.\n    Title will be appended with ISO8601 date.\n    \"\"\"\n    gc = get_google_auth()\n    if not gc:\n        return None\n\n    full_title = f\"{title}_{date.today().isoformat()}\"\n    print(f\"Exporting to Google Sheet: {full_title}...\")\n    \n    try:\n        sh = gc.create(full_title)\n        ws = sh.get_worksheet(0)\n        ws.update_title(\"Data\")\n        \n        # Prepare data: headers + rows\n        data = [headers] + rows\n        ws.update(data)\n        \n        # Basic formatting\n        ws.format(\"A1:Z1\", {\"textFormat\": {\"bold\": True}})\n        ws.freeze(rows=1)\n        \n        print(f\"Successfully exported to: {sh.url}\")\n        return sh.url\n    except Exception as e:\n        print(f\"Error exporting to Google Sheets: {e}\")\n        return None\n\ndef get_boto_session():\n    \"\"\"\n    Returns a boto3 session for the parent profile.\n    Ensures SSO login is valid and unsets conflicting env vars.\n    \"\"\"\n    ensure_sso_login()\n    parent_profile = os.getenv('AWS_PARENT_PROFILE', 'default')\n    \n    # Unset env vars that would override the profile\n    for var in ['AWS_ACCESS_KEY_ID', 'AWS_SECRET_ACCESS_KEY', 'AWS_SESSION_TOKEN']:\n        if var in os.environ:\n            del os.environ[var]\n            \n    os.environ['AWS_PROFILE'] = parent_profile\n    return boto3.Session(profile_name=parent_profile)\n\ndef ensure_sso_login():\n    \"\"\"\n    Checks if the current session has valid credentials.\n    If not, attempts to run 'aws sso login'.\n    Uses AWS_PARENT_PROFILE from env or defaults to 'default'.\n    \"\"\"\n    parent_profile = os.getenv('AWS_PARENT_PROFILE', 'default')\n    \n    # We create a temporary session to check credentials\n    session = boto3.Session(profile_name=parent_profile)\n    \n    try:\n        # Check if we can get an identity (indicates valid session)\n        sts = session.client('sts')\n        sts.get_caller_identity()\n    except Exception:\n        print(f\"Session for profile '{parent_profile}' expired or invalid. Attempting SSO login...\")\n        try:\n            # We use subprocess to call the CLI for login as it handles the browser flow\n            subprocess.run([\"aws\", \"sso\", \"login\", \"--profile\", parent_profile], check=True)\n            print(\"SSO login successful.\")\n        except subprocess.CalledProcessError:\n            print(\"Error: 'aws sso login' failed. Please login manually.\")\n            return False\n        except Exception as e:\n            print(f\"An unexpected error occurred during login: {e}\")\n            return False\n    \n    return True\n\ndef get_skip_accounts():\n    \"\"\"Returns a list of account IDs to skip from SKIP_ACCOUNTS env var.\"\"\"\n    skip_str = os.getenv('SKIP_ACCOUNTS', '')\n    if not skip_str:\n        return []\n    return [s.strip() for s in skip_str.split(',') if s.strip()]\n\ndef get_ou_ids():\n    \"\"\"Returns a list of OU IDs from OU_IDS env var.\"\"\"\n    ou_str = os.getenv('OU_IDS', '')\n    if ou_str:\n        return [o.strip() for o in ou_str.split(',') if o.strip()]\n    return []\n\ndef get_account_names():\n    \"\"\"Fetches account names from AWS Organizations, excluding skipped accounts.\"\"\"\n    session = get_boto_session()\n    org_client = session.client('organizations')\n    skip_accounts = get_skip_accounts()\n    accounts = {}\n    try:\n        paginator = org_client.get_paginator('list_accounts')\n        for page in paginator.paginate():\n            for account in page['Accounts']:\n                if account['Status'] == 'ACTIVE' and account['Id'] not in skip_accounts:\n                    accounts[account['Id']] = account['Name']\n    except Exception as e:\n        sts = session.client('sts')\n        try:\n            identity = sts.get_caller_identity()['Arn']\n        except:\n            identity = \"Unknown\"\n        print(f\"Error fetching account names (Identity: {identity}): {e}\")\n        print(\"Tip: If you don't have permission to list all accounts, try specifying OU_IDS in your .env file.\")\n    return accounts\n\ndef get_previous_month_range():\n    \"\"\"Returns (start_date, end_date) for the previous month in YYYY-MM-DD format.\"\"\"\n    today = date.today()\n    first_day_curr = today.replace(day=1)\n    last_day_prev = first_day_curr - relativedelta(days=1)\n    start_date = last_day_prev.replace(day=1).strftime('%Y-%m-%d')\n    end_date = first_day_curr.strftime('%Y-%m-%d')\n    return start_date, end_date\n\ndef get_last_n_months_ranges(n=3):\n    \"\"\"Returns a list of (start_date, end_date, label) for the last n months.\"\"\"\n    ranges = []\n    current_date = datetime.now().replace(day=1)\n    for i in range(1, n + 1):\n        start_dt = current_date - relativedelta(months=i)\n        end_dt = current_date - relativedelta(months=i-1)\n        ranges.append((\n            start_dt.strftime('%Y-%m-%d'),\n            end_dt.strftime('%Y-%m-%d'),\n            start_dt.strftime('%Y-%m')\n        ))\n    return ranges\n\ndef get_aws_pricing(service_code, filters):\n    \"\"\"Generic helper to fetch on-demand price from AWS Pricing API (us-east-1).\"\"\"\n    session = get_boto_session()\n    pricing_client = session.client('pricing', region_name='us-east-1')\n    try:\n        response = pricing_client.get_products(\n            ServiceCode=service_code,\n            Filters=filters\n        )\n        if response['PriceList']:\n            price_item = json.loads(response['PriceList'][0])\n            on_demand = price_item['terms']['OnDemand']\n            term_key = list(on_demand.keys())[0]\n            price_dimensions = on_demand[term_key]['priceDimensions']\n            dim_key = list(price_dimensions.keys())[0]\n            return float(price_dimensions[dim_key]['pricePerUnit']['USD'])\n    except Exception as e:\n        print(f\"Error fetching pricing for {service_code}: {e}\")\n    return None\n\ndef setup_org_accounts_session(ou_ids=None, profile_suffix='.admin'):\n    \"\"\"\n    Yields (account_dict, profile_name) for active accounts in OUs.\n    Handles boto3 session setup for each account.\n    Excludes accounts in SKIP_ACCOUNTS env var.\n    If no OUs are provided, scans the entire organization.\n    \"\"\"\n    session = get_boto_session()\n\n    if ou_ids is None:\n        ou_ids = get_ou_ids()\n        \n    skip_accounts = get_skip_accounts()\n    org_client = session.client('organizations')\n\n    if not ou_ids:\n        # Fallback: Scan all accounts in the organization if no OUs specified\n        try:\n            paginator = org_client.get_paginator('list_accounts')\n            for page in paginator.paginate():\n                for account in page['Accounts']:\n                    if account['Status'] == 'ACTIVE' and account['Id'] not in skip_accounts:\n                        # Sanitize account name for profile use\n                        account_name = account['Name'].replace(\" - \", \"-\").replace(\" \", \"-\")\n                        profile_name = f'{account_name}{profile_suffix}'\n                        yield account, profile_name\n            return\n        except Exception as e:\n            sts = session.client('sts')\n            try:\n                identity = sts.get_caller_identity()['Arn']\n            except:\n                identity = \"Unknown\"\n            print(f\"Error fetching all accounts in organization (Identity: {identity}): {e}\")\n            print(\"Tip: If you don't have permission to list all accounts, try specifying OU_IDS in your .env file.\")\n            return\n\n    for ou_id in ou_ids:\n        try:\n            paginator = org_client.get_paginator('list_accounts_for_parent')\n            for page in paginator.paginate(ParentId=ou_id):\n                for account in page['Accounts']:\n                    if account['Status'] == 'ACTIVE' and account['Id'] not in skip_accounts:\n                        # Sanitize account name for profile use\n                        account_name = account['Name'].replace(\" - \", \"-\").replace(\" \", \"-\")\n                        profile_name = f'{account_name}{profile_suffix}'\n                        yield account, profile_name\n        except Exception as e:\n            print(f\"Error fetching accounts for OU {ou_id}: {e}\")\n"
                }
              }
            }
          ],
          "status": "success",
          "timestamp": "2026-03-03T11:45:35.825Z",
          "resultDisplay": "",
          "displayName": "ReadFile",
          "description": "Reads and returns the content of a specified file. If the file is large, the content will be truncated. The tool's response will clearly indicate if truncation has occurred and will provide details on how to read more of the file using the 'start_line' and 'end_line' parameters. Handles text, images (PNG, JPG, GIF, WEBP, SVG, BMP), audio files (MP3, WAV, AIFF, AAC, OGG, FLAC), and PDF files. For text files, it can read specific line ranges.",
          "renderOutputAsMarkdown": true
        }
      ]
    },
    {
      "id": "b08e3a5e-862b-4dd1-a017-19a517f3c070",
      "timestamp": "2026-03-03T11:45:51.546Z",
      "type": "gemini",
      "content": "I will modify `avg_bandwidth_12months.py` to import `export_to_sheets` and use it to export the report data.",
      "thoughts": [
        {
          "subject": "Implementing Export Functionality",
          "description": "I'm making progress. I've successfully verified the existence of `export_to_sheets` within `aws_utils.py`. The next logical step is to integrate this function into `avg_bandwidth_12months.py`. My current plan involves importing the function and adapting the script's data output to leverage its capabilities.",
          "timestamp": "2026-03-03T11:45:37.788Z"
        },
        {
          "subject": "Refactoring for Data Handling",
          "description": "I'm now focusing on adapting the `avg_bandwidth_12months.py` script. The original script's output format is not directly compatible with `export_to_sheets`. I'm updating the data retrieval loop to capture the necessary values to assemble the `headers` and `rows` data structures, ensuring they are ready for the export function call.",
          "timestamp": "2026-03-03T11:45:39.833Z"
        },
        {
          "subject": "Structuring Data for Export",
          "description": "I'm now implementing the integration of `export_to_sheets` into the main script. This involves refactoring the data processing within `avg_bandwidth_12months.py`. I've added the import statement and am modifying the output loop to build the `rows` list. I've defined the `headers` and will call the export function at the end, and have also reviewed the existing output format. I'm now testing the updated loop to verify the data structure.",
          "timestamp": "2026-03-03T11:45:41.736Z"
        }
      ],
      "tokens": {
        "input": 19403,
        "output": 2141,
        "cached": 16653,
        "thoughts": 681,
        "tool": 0,
        "total": 22225
      },
      "model": "gemini-3-flash-preview",
      "toolCalls": [
        {
          "id": "replace_1772538351543_0",
          "name": "replace",
          "args": {
            "old_string": "from aws_utils import get_account_names, get_boto_session\n\ndef get_average_bandwidth_report():\n    session = get_boto_session()\n    ce_client = session.client('ce')\n    \n    all_accounts = get_account_names()\n    if not all_accounts:\n        print(\"Could not retrieve account list. Check Organizations permissions.\")\n        return\n\n    # Set dates for the last 12 full months\n    now = datetime.now()\n    first_day_current_month = now.replace(day=1)\n    end_date = first_day_current_month.strftime('%Y-%m-%d')\n    start_date = (first_day_current_month - relativedelta(months=12)).strftime('%Y-%m-%d')\n\n    # Initialize tracking: {acc_id: {'usage': 0.0, 'cost': 0.0}}\n    account_totals = {acc_id: {'usage': 0.0, 'cost': 0.0} for acc_id in all_accounts.keys()}\n    \n    next_token = None\n\n    try:\n        while True:\n            params = {\n                'TimePeriod': {'Start': start_date, 'End': end_date},\n                'Granularity': 'MONTHLY',\n                'Metrics': ['UsageQuantity', 'UnblendedCost'],\n                'GroupBy': [\n                    {'Type': 'DIMENSION', 'Key': 'LINKED_ACCOUNT'},\n                    {'Type': 'DIMENSION', 'Key': 'USAGE_TYPE'}\n                ]\n            }\n            if next_token:\n                params['NextPageToken'] = next_token\n\n            response = ce_client.get_cost_and_usage(**params)\n\n            for result in response['ResultsByTime']:\n                for group in result['Groups']:\n                    acc_id = group['Keys'][0]\n                    usage_type = group['Keys'][1]\n                    usage_amount = float(group['Metrics']['UsageQuantity']['Amount'])\n                    unit = group['Metrics']['UsageQuantity']['Unit']\n                    cost_amount = float(group['Metrics']['UnblendedCost']['Amount'])\n\n                    # Bandwidth calculation logic from bwsuage.py\n                    if \"DataTransfer\" in usage_type:\n                        if unit == 'Bytes':\n                            usage_amount /= (1024**3)\n                        elif unit in ['MB', 'Megabytes']:\n                            usage_amount /= 1024\n                        \n                        if acc_id not in account_totals:\n                            account_totals[acc_id] = {'usage': 0.0, 'cost': 0.0}\n                        \n                        account_totals[acc_id]['usage'] += usage_amount\n                        account_totals[acc_id]['cost'] += cost_amount\n\n            next_token = response.get('NextPageToken')\n            if not next_token:\n                break\n\n        print(f\"\\n--- 12-Month Average Bandwidth & Cost Report ---\")\n        print(f\"Period: {start_date} to {end_date}\")\n        print(f\"{'Account Name':<25} | {'Avg GB':<10} | {'Avg Cost ($)':<12} | {'12m Total ($)'}\")\n        print(\"-\" * 80)\n\n        # Sort by total cost descending\n        sorted_accounts = sorted(\n            account_totals.items(), \n            key=lambda x: x[1]['cost'], \n            reverse=True\n        )\n        \n        for acc_id, totals in sorted_accounts:\n            acc_name = all_accounts.get(acc_id, f\"Deleted/Unknown ({acc_id})\")\n            avg_usage = totals['usage'] / 12.0\n            avg_cost = totals['cost'] / 12.0\n            total_cost = totals['cost']\n            \n            print(f\"{acc_name[:25]:<25} | {avg_usage:>10.2f} | {avg_cost:>12.2f} | {total_cost:>13.2f}\")\n\n        print(f\"\\nTotal Accounts Scanned: {len(all_accounts)}\")\n\n    except Exception as e:\n        print(f\"Error: {e}\")",
            "file_path": "/Users/bob/git/dxw/aws-stuff/avg_bandwidth_12months.py",
            "new_string": "from aws_utils import get_account_names, get_boto_session, export_to_sheets\n\ndef get_average_bandwidth_report():\n    session = get_boto_session()\n    ce_client = session.client('ce')\n    \n    all_accounts = get_account_names()\n    if not all_accounts:\n        print(\"Could not retrieve account list. Check Organizations permissions.\")\n        return\n\n    # Set dates for the last 12 full months\n    now = datetime.now()\n    first_day_current_month = now.replace(day=1)\n    end_date = first_day_current_month.strftime('%Y-%m-%d')\n    start_date = (first_day_current_month - relativedelta(months=12)).strftime('%Y-%m-%d')\n\n    # Initialize tracking: {acc_id: {'usage': 0.0, 'cost': 0.0}}\n    account_totals = {acc_id: {'usage': 0.0, 'cost': 0.0} for acc_id in all_accounts.keys()}\n    \n    next_token = None\n\n    try:\n        while True:\n            params = {\n                'TimePeriod': {'Start': start_date, 'End': end_date},\n                'Granularity': 'MONTHLY',\n                'Metrics': ['UsageQuantity', 'UnblendedCost'],\n                'GroupBy': [\n                    {'Type': 'DIMENSION', 'Key': 'LINKED_ACCOUNT'},\n                    {'Type': 'DIMENSION', 'Key': 'USAGE_TYPE'}\n                ]\n            }\n            if next_token:\n                params['NextPageToken'] = next_token\n\n            response = ce_client.get_cost_and_usage(**params)\n\n            for result in response['ResultsByTime']:\n                for group in result['Groups']:\n                    acc_id = group['Keys'][0]\n                    usage_type = group['Keys'][1]\n                    usage_amount = float(group['Metrics']['UsageQuantity']['Amount'])\n                    unit = group['Metrics']['UsageQuantity']['Unit']\n                    cost_amount = float(group['Metrics']['UnblendedCost']['Amount'])\n\n                    # Bandwidth calculation logic from bwsuage.py\n                    if \"DataTransfer\" in usage_type:\n                        if unit == 'Bytes':\n                            usage_amount /= (1024**3)\n                        elif unit in ['MB', 'Megabytes']:\n                            usage_amount /= 1024\n                        \n                        if acc_id not in account_totals:\n                            account_totals[acc_id] = {'usage': 0.0, 'cost': 0.0}\n                        \n                        account_totals[acc_id]['usage'] += usage_amount\n                        account_totals[acc_id]['cost'] += cost_amount\n\n            next_token = response.get('NextPageToken')\n            if not next_token:\n                break\n\n        print(f\"\\n--- 12-Month Average Bandwidth & Cost Report ---\")\n        print(f\"Period: {start_date} to {end_date}\")\n        print(f\"{'Account Name':<25} | {'Avg GB':<10} | {'Avg Cost ($)':<12} | {'12m Total ($)'}\")\n        print(\"-\" * 80)\n\n        # Sort by total cost descending\n        sorted_accounts = sorted(\n            account_totals.items(), \n            key=lambda x: x[1]['cost'], \n            reverse=True\n        )\n        \n        rows = []\n        for acc_id, totals in sorted_accounts:\n            acc_name = all_accounts.get(acc_id, f\"Deleted/Unknown ({acc_id})\")\n            avg_usage = totals['usage'] / 12.0\n            avg_cost = totals['cost'] / 12.0\n            total_cost = totals['cost']\n            \n            print(f\"{acc_name[:25]:<25} | {avg_usage:>10.2f} | {avg_cost:>12.2f} | {total_cost:>13.2f}\")\n            rows.append([acc_name, acc_id, round(avg_usage, 2), round(avg_cost, 2), round(total_cost, 2)])\n\n        print(f\"\\nTotal Accounts Scanned: {len(all_accounts)}\")\n\n        headers = [\"Account Name\", \"Account ID\", \"Avg GB\", \"Avg Cost ($)\", \"12m Total ($)\"]\n        export_to_sheets(\"Avg_Bandwidth_12m\", headers, rows)\n\n    except Exception as e:\n        print(f\"Error: {e}\")",
            "instruction": "Import export_to_sheets from aws_utils and call it after generating the report to export the data to a Google Sheet.",
            "allow_multiple": false
          },
          "result": [
            {
              "functionResponse": {
                "id": "replace_1772538351543_0",
                "name": "replace",
                "response": {
                  "output": "Successfully modified file: /Users/bob/git/dxw/aws-stuff/avg_bandwidth_12months.py (1 replacements). Here is the updated code:\nimport boto3\nfrom datetime import datetime\nfrom dateutil.relativedelta import relativedelta\nfrom aws_utils import get_account_names, get_boto_session, export_to_sheets\n\ndef get_average_bandwidth_report():\n    session = get_boto_session()\n    ce_client = session.client('ce')\n    \n...\n            account_totals.items(), \n            key=lambda x: x[1]['cost'], \n            reverse=True\n        )\n        \n        rows = []\n        for acc_id, totals in sorted_accounts:\n            acc_name = all_accounts.get(acc_id, f\"Deleted/Unknown ({acc_id})\")\n            avg_usage = totals['usage'] / 12.0\n            avg_cost = totals['cost'] / 12.0\n            total_cost = totals['cost']\n            \n            print(f\"{acc_name[:25]:<25} | {avg_usage:>10.2f} | {avg_cost:>12.2f} | {total_cost:>13.2f}\")\n            rows.append([acc_name, acc_id, round(avg_usage, 2), round(avg_cost, 2), round(total_cost, 2)])\n\n        print(f\"\\nTotal Accounts Scanned: {len(all_accounts)}\")\n\n        headers = [\"Account Name\", \"Account ID\", \"Avg GB\", \"Avg Cost ($)\", \"12m Total ($)\"]\n        export_to_sheets(\"Avg_Bandwidth_12m\", headers, rows)\n\n    except Exception as e:\n        print(f\"Error: {e}\")\n\nif __name__ == \"__main__\":\n    get_average_bandwidth_report()\n..."
                }
              }
            }
          ],
          "status": "success",
          "timestamp": "2026-03-03T11:46:04.039Z",
          "resultDisplay": {
            "fileDiff": "Index: avg_bandwidth_12months.py\n===================================================================\n--- avg_bandwidth_12months.py\tCurrent\n+++ avg_bandwidth_12months.py\tProposed\n@@ -1,7 +1,7 @@\n import boto3\n from datetime import datetime\n from dateutil.relativedelta import relativedelta\n-from aws_utils import get_account_names, get_boto_session\n+from aws_utils import get_account_names, get_boto_session, export_to_sheets\n \n def get_average_bandwidth_report():\n     session = get_boto_session()\n@@ -76,6 +76,7 @@\n             reverse=True\n         )\n         \n+        rows = []\n         for acc_id, totals in sorted_accounts:\n             acc_name = all_accounts.get(acc_id, f\"Deleted/Unknown ({acc_id})\")\n             avg_usage = totals['usage'] / 12.0\n@@ -83,9 +84,13 @@\n             total_cost = totals['cost']\n             \n             print(f\"{acc_name[:25]:<25} | {avg_usage:>10.2f} | {avg_cost:>12.2f} | {total_cost:>13.2f}\")\n+            rows.append([acc_name, acc_id, round(avg_usage, 2), round(avg_cost, 2), round(total_cost, 2)])\n \n         print(f\"\\nTotal Accounts Scanned: {len(all_accounts)}\")\n \n+        headers = [\"Account Name\", \"Account ID\", \"Avg GB\", \"Avg Cost ($)\", \"12m Total ($)\"]\n+        export_to_sheets(\"Avg_Bandwidth_12m\", headers, rows)\n+\n     except Exception as e:\n         print(f\"Error: {e}\")\n \n",
            "fileName": "avg_bandwidth_12months.py",
            "filePath": "/Users/bob/git/dxw/aws-stuff/avg_bandwidth_12months.py",
            "originalContent": "import boto3\nfrom datetime import datetime\nfrom dateutil.relativedelta import relativedelta\nfrom aws_utils import get_account_names, get_boto_session\n\ndef get_average_bandwidth_report():\n    session = get_boto_session()\n    ce_client = session.client('ce')\n    \n    all_accounts = get_account_names()\n    if not all_accounts:\n        print(\"Could not retrieve account list. Check Organizations permissions.\")\n        return\n\n    # Set dates for the last 12 full months\n    now = datetime.now()\n    first_day_current_month = now.replace(day=1)\n    end_date = first_day_current_month.strftime('%Y-%m-%d')\n    start_date = (first_day_current_month - relativedelta(months=12)).strftime('%Y-%m-%d')\n\n    # Initialize tracking: {acc_id: {'usage': 0.0, 'cost': 0.0}}\n    account_totals = {acc_id: {'usage': 0.0, 'cost': 0.0} for acc_id in all_accounts.keys()}\n    \n    next_token = None\n\n    try:\n        while True:\n            params = {\n                'TimePeriod': {'Start': start_date, 'End': end_date},\n                'Granularity': 'MONTHLY',\n                'Metrics': ['UsageQuantity', 'UnblendedCost'],\n                'GroupBy': [\n                    {'Type': 'DIMENSION', 'Key': 'LINKED_ACCOUNT'},\n                    {'Type': 'DIMENSION', 'Key': 'USAGE_TYPE'}\n                ]\n            }\n            if next_token:\n                params['NextPageToken'] = next_token\n\n            response = ce_client.get_cost_and_usage(**params)\n\n            for result in response['ResultsByTime']:\n                for group in result['Groups']:\n                    acc_id = group['Keys'][0]\n                    usage_type = group['Keys'][1]\n                    usage_amount = float(group['Metrics']['UsageQuantity']['Amount'])\n                    unit = group['Metrics']['UsageQuantity']['Unit']\n                    cost_amount = float(group['Metrics']['UnblendedCost']['Amount'])\n\n                    # Bandwidth calculation logic from bwsuage.py\n                    if \"DataTransfer\" in usage_type:\n                        if unit == 'Bytes':\n                            usage_amount /= (1024**3)\n                        elif unit in ['MB', 'Megabytes']:\n                            usage_amount /= 1024\n                        \n                        if acc_id not in account_totals:\n                            account_totals[acc_id] = {'usage': 0.0, 'cost': 0.0}\n                        \n                        account_totals[acc_id]['usage'] += usage_amount\n                        account_totals[acc_id]['cost'] += cost_amount\n\n            next_token = response.get('NextPageToken')\n            if not next_token:\n                break\n\n        print(f\"\\n--- 12-Month Average Bandwidth & Cost Report ---\")\n        print(f\"Period: {start_date} to {end_date}\")\n        print(f\"{'Account Name':<25} | {'Avg GB':<10} | {'Avg Cost ($)':<12} | {'12m Total ($)'}\")\n        print(\"-\" * 80)\n\n        # Sort by total cost descending\n        sorted_accounts = sorted(\n            account_totals.items(), \n            key=lambda x: x[1]['cost'], \n            reverse=True\n        )\n        \n        for acc_id, totals in sorted_accounts:\n            acc_name = all_accounts.get(acc_id, f\"Deleted/Unknown ({acc_id})\")\n            avg_usage = totals['usage'] / 12.0\n            avg_cost = totals['cost'] / 12.0\n            total_cost = totals['cost']\n            \n            print(f\"{acc_name[:25]:<25} | {avg_usage:>10.2f} | {avg_cost:>12.2f} | {total_cost:>13.2f}\")\n\n        print(f\"\\nTotal Accounts Scanned: {len(all_accounts)}\")\n\n    except Exception as e:\n        print(f\"Error: {e}\")\n\nif __name__ == \"__main__\":\n    get_average_bandwidth_report()\n",
            "newContent": "import boto3\nfrom datetime import datetime\nfrom dateutil.relativedelta import relativedelta\nfrom aws_utils import get_account_names, get_boto_session, export_to_sheets\n\ndef get_average_bandwidth_report():\n    session = get_boto_session()\n    ce_client = session.client('ce')\n    \n    all_accounts = get_account_names()\n    if not all_accounts:\n        print(\"Could not retrieve account list. Check Organizations permissions.\")\n        return\n\n    # Set dates for the last 12 full months\n    now = datetime.now()\n    first_day_current_month = now.replace(day=1)\n    end_date = first_day_current_month.strftime('%Y-%m-%d')\n    start_date = (first_day_current_month - relativedelta(months=12)).strftime('%Y-%m-%d')\n\n    # Initialize tracking: {acc_id: {'usage': 0.0, 'cost': 0.0}}\n    account_totals = {acc_id: {'usage': 0.0, 'cost': 0.0} for acc_id in all_accounts.keys()}\n    \n    next_token = None\n\n    try:\n        while True:\n            params = {\n                'TimePeriod': {'Start': start_date, 'End': end_date},\n                'Granularity': 'MONTHLY',\n                'Metrics': ['UsageQuantity', 'UnblendedCost'],\n                'GroupBy': [\n                    {'Type': 'DIMENSION', 'Key': 'LINKED_ACCOUNT'},\n                    {'Type': 'DIMENSION', 'Key': 'USAGE_TYPE'}\n                ]\n            }\n            if next_token:\n                params['NextPageToken'] = next_token\n\n            response = ce_client.get_cost_and_usage(**params)\n\n            for result in response['ResultsByTime']:\n                for group in result['Groups']:\n                    acc_id = group['Keys'][0]\n                    usage_type = group['Keys'][1]\n                    usage_amount = float(group['Metrics']['UsageQuantity']['Amount'])\n                    unit = group['Metrics']['UsageQuantity']['Unit']\n                    cost_amount = float(group['Metrics']['UnblendedCost']['Amount'])\n\n                    # Bandwidth calculation logic from bwsuage.py\n                    if \"DataTransfer\" in usage_type:\n                        if unit == 'Bytes':\n                            usage_amount /= (1024**3)\n                        elif unit in ['MB', 'Megabytes']:\n                            usage_amount /= 1024\n                        \n                        if acc_id not in account_totals:\n                            account_totals[acc_id] = {'usage': 0.0, 'cost': 0.0}\n                        \n                        account_totals[acc_id]['usage'] += usage_amount\n                        account_totals[acc_id]['cost'] += cost_amount\n\n            next_token = response.get('NextPageToken')\n            if not next_token:\n                break\n\n        print(f\"\\n--- 12-Month Average Bandwidth & Cost Report ---\")\n        print(f\"Period: {start_date} to {end_date}\")\n        print(f\"{'Account Name':<25} | {'Avg GB':<10} | {'Avg Cost ($)':<12} | {'12m Total ($)'}\")\n        print(\"-\" * 80)\n\n        # Sort by total cost descending\n        sorted_accounts = sorted(\n            account_totals.items(), \n            key=lambda x: x[1]['cost'], \n            reverse=True\n        )\n        \n        rows = []\n        for acc_id, totals in sorted_accounts:\n            acc_name = all_accounts.get(acc_id, f\"Deleted/Unknown ({acc_id})\")\n            avg_usage = totals['usage'] / 12.0\n            avg_cost = totals['cost'] / 12.0\n            total_cost = totals['cost']\n            \n            print(f\"{acc_name[:25]:<25} | {avg_usage:>10.2f} | {avg_cost:>12.2f} | {total_cost:>13.2f}\")\n            rows.append([acc_name, acc_id, round(avg_usage, 2), round(avg_cost, 2), round(total_cost, 2)])\n\n        print(f\"\\nTotal Accounts Scanned: {len(all_accounts)}\")\n\n        headers = [\"Account Name\", \"Account ID\", \"Avg GB\", \"Avg Cost ($)\", \"12m Total ($)\"]\n        export_to_sheets(\"Avg_Bandwidth_12m\", headers, rows)\n\n    except Exception as e:\n        print(f\"Error: {e}\")\n\nif __name__ == \"__main__\":\n    get_average_bandwidth_report()\n",
            "diffStat": {
              "model_added_lines": 6,
              "model_removed_lines": 1,
              "model_added_chars": 349,
              "model_removed_chars": 57,
              "user_added_lines": 1,
              "user_removed_lines": 7,
              "user_added_chars": 28,
              "user_removed_chars": 177
            },
            "isNewFile": false
          },
          "displayName": "Edit",
          "description": "Replaces text within a file. By default, the tool expects to find and replace exactly ONE occurrence of `old_string`. If you want to replace multiple occurrences of the exact same string, set `allow_multiple` to true. This tool requires providing significant context around the change to ensure precise targeting. Always use the read_file tool to examine the file's current content before attempting a text replacement.\n      \n      The user has the ability to modify the `new_string` content. If modified, this will be stated in the response.\n      \n      Expectation for required parameters:\n      1. `old_string` MUST be the exact literal text to replace (including all whitespace, indentation, newlines, and surrounding code etc.).\n      2. `new_string` MUST be the exact literal text to replace `old_string` with (also including all whitespace, indentation, newlines, and surrounding code etc.). Ensure the resulting code is correct and idiomatic and that `old_string` and `new_string` are different.\n      3. `instruction` is the detailed instruction of what needs to be changed. It is important to Make it specific and detailed so developers or large language models can understand what needs to be changed and perform the changes on their own if necessary. \n      4. NEVER escape `old_string` or `new_string`, that would break the exact literal text requirement.\n      **Important:** If ANY of the above are not satisfied, the tool will fail. CRITICAL for `old_string`: Must uniquely identify the instance(s) to change. Include at least 3 lines of context BEFORE and AFTER the target text, matching whitespace and indentation precisely. If this string matches multiple locations and `allow_multiple` is not true, the tool will fail.\n      5. Prefer to break down complex and long changes into multiple smaller atomic calls to this tool. Always check the content of the file after changes or not finding a string to match.\n      **Multiple replacements:** Set `allow_multiple` to true if you want to replace ALL occurrences that match `old_string` exactly.",
          "renderOutputAsMarkdown": true
        }
      ]
    },
    {
      "id": "1722f8c6-65ae-4418-8d08-55b8a0550a7a",
      "timestamp": "2026-03-03T11:46:06.088Z",
      "type": "gemini",
      "content": "I've updated `avg_bandwidth_12months.py` to export the report to Google Sheets. The script now:\n1. Imports `export_to_sheets` from `aws_utils.py`.\n2. Collects each account's 12-month averages (GB and Cost) and total cost into a list of rows.\n3. Automatically triggers a Google Sheet export titled `Avg_Bandwidth_12m_[DATE]` after printing the results to the console.",
      "thoughts": [
        {
          "subject": "Integrating the Export Function",
          "description": "I've successfully integrated the `export_to_sheets` function into the `avg_bandwidth_12months.py` script. The script now gathers report data and initiates the export process immediately after displaying the summary information in the console. This streamlined approach allows for seamless data handling.",
          "timestamp": "2026-03-03T11:46:06.016Z"
        }
      ],
      "tokens": {
        "input": 22000,
        "output": 105,
        "cached": 16575,
        "thoughts": 57,
        "tool": 0,
        "total": 22162
      },
      "model": "gemini-3-flash-preview"
    }
  ],
  "kind": "main"
}