Template dati: Gestione degli Incidenti

const axios = require('axios');
const fs = require('fs');

// --- Configuration ---
const INSTANCE_URL = 'https://[your-instance].service-now.com';
const USERNAME = '[your-username]';
const PASSWORD = '[your-password]';

// Define the date range for the extraction
const startDate = '2023-01-01 00:00:00';
const endDate = '2023-03-31 23:59:59';

const BATCH_SIZE = 1000; // Records per API call for incidents
const SOURCE_SYSTEM = 'ServiceNow';

// --- Main Extraction Logic ---
async function extractIncidentData() {
    const auth = { username: USERNAME, password: PASSWORD };
    const allEvents = [];
    let offset = 0;
    let hasMoreRecords = true;

    console.log(Starting extraction for incidents created between ${startDate} and ${endDate}...);

    while (hasMoreRecords) {
        try {
            // 1. Fetch a batch of incidents
            const incidentQuery = sys_created_on>=${startDate}^sys_created_on<=${endDate};
            const incidentFields = [
                'sys_id', 'number', 'sys_created_on', 'resolved_at', 'closed_at',
                'assigned_to', 'assignment_group', 'priority', 'incident_state',
                'state', 'sys_updated_on'
            ].join(',');

            console.log(Fetching incidents, offset: ${offset}...);
            const incidentResponse = await axios.get(${INSTANCE_URL}/api/now/table/incident, {
                auth,
                params: {
                    sysparm_query: incidentQuery,
                    sysparm_fields: incidentFields,
                    sysparm_limit: BATCH_SIZE,
                    sysparm_offset: offset
                }
            });

            const incidents = incidentResponse.data.result;
            if (incidents.length === 0) {
                hasMoreRecords = false;
                continue;
            }

            // 2. For each incident, fetch its audit trail and generate events
            for (const incident of incidents) {
                const lastDataUpdate = new Date().toISOString();

                // --- Explicit Events from Incident Table ---
                allEvents.push(createEvent(incident, 'Incident Created', incident.sys_created_on, lastDataUpdate));
                if (incident.resolved_at) {
                    allEvents.push(createEvent(incident, 'Resolution Proposed', incident.resolved_at, lastDataUpdate));
                }
                if (incident.closed_at) {
                    allEvents.push(createEvent(incident, 'Incident Closed', incident.closed_at, lastDataUpdate));
                }

                // --- Inferred Events from Audit Table ---
                const auditQuery = documentkey=${incident.sys_id};
                const auditFields = 'sys_created_on,fieldname,oldvalue,newvalue';
                const auditResponse = await axios.get(${INSTANCE_URL}/api/now/table/sys_audit, {
                    auth,
                    params: { sysparm_query: auditQuery, sysparm_fields: auditFields, sysparm_display_value: 'true' }
                });

                const auditRecords = auditResponse.data.result.sort((a, b) => new Date(a.sys_created_on) - new Date(b.sys_created_on));
                
                let isCategorized = false, isGroupAssigned = false, isAgentAssigned = false, isWorkStarted = false, isProblemLinked = false, isReopened = false;
                let lastPriority = null;
                
                for (const audit of auditRecords) {
                    const eventTime = audit.sys_created_on;
                    
                    if (!isCategorized && (audit.fieldname === 'category' || audit.fieldname === 'subcategory') && audit.newvalue) {
                        allEvents.push(createEvent(incident, 'Incident Categorized', eventTime, lastDataUpdate));
                        isCategorized = true;
                    }
                    if (!isGroupAssigned && audit.fieldname === 'assignment_group' && audit.newvalue) {
                        allEvents.push(createEvent(incident, 'Incident Assigned To Group', eventTime, lastDataUpdate));
                        isGroupAssigned = true;
                    } else if (isGroupAssigned && audit.fieldname === 'assignment_group' && audit.newvalue) {
                        allEvents.push(createEvent(incident, 'Assignment Group Changed', eventTime, lastDataUpdate));
                    }
                    if (!isAgentAssigned && audit.fieldname === 'assigned_to' && audit.newvalue) {
                        allEvents.push(createEvent(incident, 'Incident Assigned To Agent', eventTime, lastDataUpdate));
                        isAgentAssigned = true;
                    }
                    if (!isWorkStarted && (audit.fieldname === 'state' || audit.fieldname === 'incident_state') && audit.newvalue.toLowerCase().includes('progress')) {
                        allEvents.push(createEvent(incident, 'Work Started', eventTime, lastDataUpdate));
                        isWorkStarted = true;
                    }
                    if ((audit.fieldname === 'comments' || audit.fieldname === 'work_notes') && audit.newvalue) {
                        allEvents.push(createEvent(incident, 'Support Comment Added', eventTime, lastDataUpdate));
                    }
                    if (audit.fieldname === 'priority') {
                         const oldPriorityVal = parseInt(audit.oldvalue.match(/\d+/), 10);
                         const newPriorityVal = parseInt(audit.newvalue.match(/\d+/), 10);
                         if (lastPriority !== null && newPriorityVal < lastPriority) {
                             allEvents.push(createEvent(incident, 'Incident Escalated', eventTime, lastDataUpdate));
                         }
                         lastPriority = newPriorityVal;
                    }
                    if (!isProblemLinked && audit.fieldname === 'problem_id' && audit.newvalue) {
                        allEvents.push(createEvent(incident, 'Incident Linked To Problem', eventTime, lastDataUpdate));
                        isProblemLinked = true;
                    }
                    if ((audit.fieldname === 'state' || audit.fieldname === 'incident_state') && audit.newvalue.toLowerCase().includes('awaiting')) {
                         allEvents.push(createEvent(incident, 'Awaiting User Confirmation', eventTime, lastDataUpdate));
                    }
                    if (!isReopened && (audit.fieldname === 'state' || audit.fieldname === 'incident_state') && (audit.oldvalue.toLowerCase().includes('resolved') || audit.oldvalue.toLowerCase().includes('closed')) && audit.newvalue.toLowerCase().includes('progress')) {
                        allEvents.push(createEvent(incident, 'Incident Reopened', eventTime, lastDataUpdate));
                        isReopened = true; 
                    }
                }
            }

            offset += BATCH_SIZE;
            console.log(Processed ${incidents.length} incidents. Total events so far: ${allEvents.length});

        } catch (error) {
            console.error('An error occurred:', error.response ? error.response.data : error.message);
            hasMoreRecords = false; // Stop on error
        }
    }

    // 3. Save results to a file
    fs.writeFileSync('servicenow_incident_event_log.json', JSON.stringify(allEvents, null, 2));
    console.log(Extraction complete. ${allEvents.length} events saved to servicenow_incident_event_log.json);
}

// --- Helper Function to create a standard event object ---
function createEvent(incident, activityName, eventTime, lastDataUpdate) {
    return {
        IncidentId: incident.number,
        ActivityName: activityName,
        EventTime: eventTime,
        SourceSystem: SOURCE_SYSTEM,
        LastDataUpdate: lastDataUpdate,
        AssignedTo: incident.assigned_to.display_value || '',
        AssignmentGroup: incident.assignment_group.display_value || '',
        Priority: incident.priority.display_value || '',
        IncidentState: incident.incident_state.display_value || incident.state.display_value || ''
    };
}

// --- Run the script ---
extractIncidentData();

import requests
import pandas as pd
from datetime import datetime
import getpass

class=class="hl-string">"hl-comment"># --- Configuration ---
class=class="hl-string">"hl-comment"># Replace with your ServiceNow instance URL, e.g., class="hl-string">'https://yourinstance.service-now.com'
SNOW_INSTANCE = class="hl-string">"[Your ServiceNow Instance URL]"
class=class="hl-string">"hl-comment"># Replace with your ServiceNow user. Consider using a dedicated service account.
SNOW_USER = class="hl-string">"[Your Username]"
class=class="hl-string">"hl-comment"># It's recommended to use a secure way to handle passwords, like environment variables or a secrets manager.
class=class="hl-string">"hl-comment"># getpass is used here for interactive entry to avoid hardcoding.
SNOW_PASSWORD = getpass.getpass(class="hl-string">"Enter ServiceNow Password: ")

class=class="hl-string">"hl-comment"># Define the date range for the extraction (YYYY-MM-DD format)
START_DATE = class="hl-string">"2023-01-01"
END_DATE = class="hl-string">"2023-06-30"

SOURCE_SYSTEM_NAME = class="hl-string">"ServiceNow"

class=class="hl-string">"hl-comment"># --- Helper Function for Paginated API Calls ---
def fetch_all_records(url, headers, params):
    class="hl-string">"""Fetches all records from a paginated ServiceNow API endpoint."""
    all_records = []
    offset = 0
    limit = 1000
    while True:
        params[class="hl-string">'sysparm_offset'] = offset
        params[class="hl-string">'sysparm_limit'] = limit
        response = requests.get(url, headers=headers, params=params)
        response.raise_for_status() class=class="hl-string">"hl-comment"># Raises an exception for bad status codes
        data = response.json().get(class="hl-string">'result', [])
        if not data:
            break
        all_records.extend(data)
        offset += len(data)
        print(fclass="hl-string">"Fetched {len(all_records)} records so far...")
    return all_records

class=class="hl-string">"hl-comment"># --- Main Script ---
if __name__ == class="hl-string">"__main__":
    auth = (SNOW_USER, SNOW_PASSWORD)
    headers = {class="hl-string">"Accept": class="hl-string">"application/json"}
    last_data_update = datetime.utcnow().isoformat() + class="hl-string">"Z"

    class=class="hl-string">"hl-comment"># 1. Fetch base Incident Data
    print(class="hl-string">"\n--- Fetching Incident Data ---")
    incident_url = fclass="hl-string">"{SNOW_INSTANCE}/api/now/table/incident"
    incident_query = fclass="hl-string">"sys_created_on>={START_DATE} 00:00:00^sys_created_on<={END_DATE} 23:59:59"
    incident_params = {
        class="hl-string">'sysparm_query': incident_query,
        class="hl-string">'sysparm_fields': class="hl-string">'sys_id,number,sys_created_on,closed_at,opened_at,priority,state,assignment_group,assigned_to,problem_id'
    }
    incidents_raw = fetch_all_records(incident_url, headers, auth, incident_params)
    incidents_df = pd.DataFrame(incidents_raw)
    
    if incidents_df.empty:
        print(class="hl-string">"No incidents found for the given date range. Exiting.")
        exit()

    class=class="hl-string">"hl-comment"># Map sys_id to readable values for easier processing later
    for col in [class="hl-string">'assignment_group', class="hl-string">'assigned_to', class="hl-string">'problem_id']:
        if col in incidents_df.columns:
            incidents_df[col] = incidents_df[col].apply(lambda x: x[class="hl-string">'display_value'] if isinstance(x, dict) and x else None)
            
    incident_sys_ids = class="hl-string">','.join(incidents_df[class="hl-string">'sys_id'].unique())

    class=class="hl-string">"hl-comment"># 2. Fetch Audit (sys_audit) Data for these incidents
    print(class="hl-string">"\n--- Fetching Audit Data ---")
    audit_url = fclass="hl-string">"{SNOW_INSTANCE}/api/now/table/sys_audit"
    audit_query = fclass="hl-string">"documentkeyIN{incident_sys_ids}"
    audit_params = {
        class="hl-string">'sysparm_query': audit_query,
        class="hl-string">'sysparm_fields': class="hl-string">'documentkey,sys_created_on,fieldname,oldvalue,newvalue'
    }
    audit_raw = fetch_all_records(audit_url, headers, auth, audit_params)
    audit_df = pd.DataFrame(audit_raw)
    audit_df.rename(columns={class="hl-string">'documentkey': class="hl-string">'sys_id'}, inplace=True)

    class=class="hl-string">"hl-comment"># 3. Fetch Journal (comments) Data for these incidents
    print(class="hl-string">"\n--- Fetching Journal/Comment Data ---")
    journal_url = fclass="hl-string">"{SNOW_INSTANCE}/api/now/table/sys_journal_field"
    journal_query = fclass="hl-string">"element_idIN{incident_sys_ids}^element=work_notes,comments"
    journal_params = {
        class="hl-string">'sysparm_query': journal_query,
        class="hl-string">'sysparm_fields': class="hl-string">'element_id,sys_created_on'
    }
    journal_raw = fetch_all_records(journal_url, headers, auth, journal_params)
    journal_df = pd.DataFrame(journal_raw)
    journal_df.rename(columns={class="hl-string">'element_id': class="hl-string">'sys_id'}, inplace=True)

    print(class="hl-string">"\n--- Processing Data and Generating Event Log ---")
    event_log_frames = []

    class=class="hl-string">"hl-comment"># Merge incident details into audit and journal logs for context
    incidents_context_df = incidents_df[[class="hl-string">'sys_id', class="hl-string">'number', class="hl-string">'assignment_group', class="hl-string">'assigned_to', class="hl-string">'priority', class="hl-string">'state']].copy()
    incidents_context_df.rename(columns={class="hl-string">'number': class="hl-string">'IncidentId'}, inplace=True)

    if not audit_df.empty:
        audit_df = pd.merge(audit_df, incidents_context_df, on=class="hl-string">'sys_id', how=class="hl-string">'left')
    if not journal_df.empty:
        journal_df = pd.merge(journal_df, incidents_context_df, on=class="hl-string">'sys_id', how=class="hl-string">'left')

    class=class="hl-string">"hl-comment"># Activity: Incident Created
    created_df = incidents_df[[class="hl-string">'number', class="hl-string">'sys_created_on', class="hl-string">'assignment_group', class="hl-string">'assigned_to', class="hl-string">'priority', class="hl-string">'state']].copy()
    created_df[class="hl-string">'ActivityName'] = class="hl-string">'Incident Created'
    created_df.rename(columns={class="hl-string">'number': class="hl-string">'IncidentId', class="hl-string">'sys_created_on': class="hl-string">'EventTime', class="hl-string">'assignment_group': class="hl-string">'AssignmentGroup', class="hl-string">'assigned_to': class="hl-string">'AssignedTo', class="hl-string">'priority': class="hl-string">'Priority', class="hl-string">'state': class="hl-string">'IncidentState'}, inplace=True)
    event_log_frames.append(created_df)

    class=class="hl-string">"hl-comment"># Activity: Incident Closed
    closed_df = incidents_df[incidents_df[class="hl-string">'closed_at'].notna() & (incidents_df[class="hl-string">'closed_at'] != class="hl-string">'')].copy()
    closed_df[class="hl-string">'ActivityName'] = class="hl-string">'Incident Closed'
    closed_df.rename(columns={class="hl-string">'number': class="hl-string">'IncidentId', class="hl-string">'closed_at': class="hl-string">'EventTime', class="hl-string">'assignment_group': class="hl-string">'AssignmentGroup', class="hl-string">'assigned_to': class="hl-string">'AssignedTo', class="hl-string">'priority': class="hl-string">'Priority', class="hl-string">'state': class="hl-string">'IncidentState'}, inplace=True)
    event_log_frames.append(closed_df.drop(columns=[class="hl-string">'sys_created_on']))

    class=class="hl-string">"hl-comment"># Process audit data for remaining activities
    if not audit_df.empty:
        audit_df.sort_values(by=[class="hl-string">'sys_id', class="hl-string">'sys_created_on'], inplace=True)
        
        class=class="hl-string">"hl-comment"># Activity: Incident Categorized (first change to category, subcategory, or priority)
        categorized_fields = [class="hl-string">'category', class="hl-string">'subcategory', class="hl-string">'priority']
        categorized_df = audit_df[audit_df[class="hl-string">'fieldname'].isin(categorized_fields)].copy()
        categorized_df = categorized_df.drop_duplicates(subset=[class="hl-string">'sys_id'], keep=class="hl-string">'first')
        categorized_df[class="hl-string">'ActivityName'] = class="hl-string">'Incident Categorized'
        event_log_frames.append(categorized_df)

        class=class="hl-string">"hl-comment"># Activity: Incident Assigned To Group
        assign_group_df = audit_df[(audit_df[class="hl-string">'fieldname'] == class="hl-string">'assignment_group') & (audit_df[class="hl-string">'newvalue'].notna())].copy()
        assign_group_first_df = assign_group_df.drop_duplicates(subset=[class="hl-string">'sys_id'], keep=class="hl-string">'first')
        assign_group_first_df[class="hl-string">'ActivityName'] = class="hl-string">'Incident Assigned To Group'
        event_log_frames.append(assign_group_first_df)
        
        class=class="hl-string">"hl-comment"># Activity: Assignment Group Changed (subsequent changes)
        assign_group_changed_df = assign_group_df.loc[assign_group_df.index.difference(assign_group_first_df.index)]
        assign_group_changed_df[class="hl-string">'ActivityName'] = class="hl-string">'Assignment Group Changed'
        event_log_frames.append(assign_group_changed_df)

        class=class="hl-string">"hl-comment"># Activity: Incident Assigned To Agent
        assign_agent_df = audit_df[(audit_df[class="hl-string">'fieldname'] == class="hl-string">'assigned_to') & (audit_df[class="hl-string">'newvalue'].notna())].copy()
        assign_agent_df = assign_agent_df.drop_duplicates(subset=[class="hl-string">'sys_id'], keep=class="hl-string">'first')
        assign_agent_df[class="hl-string">'ActivityName'] = class="hl-string">'Incident Assigned To Agent'
        event_log_frames.append(assign_agent_df)

        class=class="hl-string">"hl-comment"># Activity: Work Started (State changed to In Progress)
        work_started_df = audit_df[audit_df[class="hl-string">'fieldname'] == class="hl-string">'state'].copy()
        class=class="hl-string">"hl-comment"># Note: The class="hl-string">'newvalue' for state is often a numeric ID. Common value for class="hl-string">'In Progress' is class="hl-string">'2'. Adjust if needed.
        work_started_df = work_started_df[work_started_df[class="hl-string">'newvalue'].isin([class="hl-string">'2', class="hl-string">'In Progress', class="hl-string">'Work in Progress'])]
        work_started_df = work_started_df.drop_duplicates(subset=[class="hl-string">'sys_id'], keep=class="hl-string">'first')
        work_started_df[class="hl-string">'ActivityName'] = class="hl-string">'Work Started'
        event_log_frames.append(work_started_df)
        
        class=class="hl-string">"hl-comment"># Activity: Incident Escalated (Priority increases)
        priority_map = {class="hl-string">'1 - Critical': 1, class="hl-string">'2 - High': 2, class="hl-string">'3 - Moderate': 3, class="hl-string">'4 - Low': 4, class="hl-string">'5 - Planning': 5}
        escalated_df = audit_df[audit_df[class="hl-string">'fieldname'] == class="hl-string">'priority'].copy()
        escalated_df[class="hl-string">'old_priority_val'] = escalated_df[class="hl-string">'oldvalue'].map(priority_map)
        escalated_df[class="hl-string">'new_priority_val'] = escalated_df[class="hl-string">'newvalue'].map(priority_map)
        escalated_df.dropna(subset=[class="hl-string">'old_priority_val', class="hl-string">'new_priority_val'], inplace=True)
        escalated_df = escalated_df[escalated_df[class="hl-string">'new_priority_val'] < escalated_df[class="hl-string">'old_priority_val']]
        escalated_df[class="hl-string">'ActivityName'] = class="hl-string">'Incident Escalated'
        event_log_frames.append(escalated_df)
        
        class=class="hl-string">"hl-comment"># Activity: Incident Linked To Problem
        linked_problem_df = audit_df[(audit_df[class="hl-string">'fieldname'] == class="hl-string">'problem_id') & (audit_df[class="hl-string">'newvalue'].notna())].copy()
        linked_problem_df = linked_problem_df.drop_duplicates(subset=[class="hl-string">'sys_id'], keep=class="hl-string">'first')
        linked_problem_df[class="hl-string">'ActivityName'] = class="hl-string">'Incident Linked To Problem'
        event_log_frames.append(linked_problem_df)
        
        class=class="hl-string">"hl-comment"># Activity: Resolution Proposed (State changed to Resolved)
        resolved_df = audit_df[audit_df[class="hl-string">'fieldname'] == class="hl-string">'state'].copy()
        class=class="hl-string">"hl-comment"># Note: Common value for class="hl-string">'Resolved' is class="hl-string">'6'. Adjust if needed.
        resolved_df = resolved_df[resolved_df[class="hl-string">'newvalue'].isin([class="hl-string">'6', class="hl-string">'Resolved'])]
        resolved_df[class="hl-string">'ActivityName'] = class="hl-string">'Resolution Proposed'
        event_log_frames.append(resolved_df)
        
        class=class="hl-string">"hl-comment"># Activity: Awaiting User Confirmation (State changed to Awaiting User Info, after resolved)
        class=class="hl-string">"hl-comment"># This logic is complex and dependent on workflow. A simplified version is shown.
        state_changes = audit_df[audit_df[class="hl-string">'fieldname'] == class="hl-string">'state'].copy()
        state_changes[class="hl-string">'prev_state'] = state_changes.groupby(class="hl-string">'sys_id')[class="hl-string">'oldvalue'].shift(-1)
        awaiting_df = state_changes[
            (state_changes[class="hl-string">'newvalue'].isin([class="hl-string">'Awaiting User Info', class="hl-string">'3'])) & 
            (state_changes[class="hl-string">'oldvalue'].isin([class="hl-string">'Resolved', class="hl-string">'6']))
        ].copy()
        awaiting_df[class="hl-string">'ActivityName'] = class="hl-string">'Awaiting User Confirmation'
        event_log_frames.append(awaiting_df)

        class=class="hl-string">"hl-comment"># Activity: Incident Reopened
        reopened_df = audit_df[
            (audit_df[class="hl-string">'fieldname'] == class="hl-string">'state') & 
            (audit_df[class="hl-string">'oldvalue'].isin([class="hl-string">'6', class="hl-string">'7', class="hl-string">'Resolved', class="hl-string">'Closed']))
        ].copy()
        reopened_df[class="hl-string">'ActivityName'] = class="hl-string">'Incident Reopened'
        event_log_frames.append(reopened_df)
        
    class=class="hl-string">"hl-comment"># Activity: Support Comment Added
    if not journal_df.empty:
        comment_df = journal_df.copy()
        comment_df[class="hl-string">'ActivityName'] = class="hl-string">'Support Comment Added'
        event_log_frames.append(comment_df)

    class=class="hl-string">"hl-comment"># 4. Consolidate all event dataframes
    print(class="hl-string">"\n--- Consolidating Final Event Log ---")
    final_log = pd.DataFrame()
    for df in event_log_frames:
        if class="hl-string">'sys_created_on' in df.columns:
             df.rename(columns={class="hl-string">'sys_created_on': class="hl-string">'EventTime'}, inplace=True)
        if class="hl-string">'IncidentId' not in df.columns:
            continue class=class="hl-string">"hl-comment"># Skip frames that couldn't be processed
        
        common_cols = {
            class="hl-string">'IncidentId': None,
            class="hl-string">'ActivityName': None,
            class="hl-string">'EventTime': None,
            class="hl-string">'AssignedTo': None,
            class="hl-string">'AssignmentGroup': None,
            class="hl-string">'Priority': None,
            class="hl-string">'IncidentState': None
        }
        
        class=class="hl-string">"hl-comment"># Select and reorder columns, filling missing ones with None
        current_cols = {col: None for col in common_cols.keys()}
        df_subset = df[list(set(df.columns) & set(common_cols.keys()))].copy()
        final_log = pd.concat([final_log, df_subset], ignore_index=True)

    class=class="hl-string">"hl-comment"># 5. Final Cleaning and Formatting
    final_log.dropna(subset=[class="hl-string">'IncidentId', class="hl-string">'ActivityName', class="hl-string">'EventTime'], inplace=True)
    final_log[class="hl-string">'EventTime'] = pd.to_datetime(final_log[class="hl-string">'EventTime'])
    final_log.sort_values(by=[class="hl-string">'IncidentId', class="hl-string">'EventTime'], inplace=True)
    
    final_log[class="hl-string">'SourceSystem'] = SOURCE_SYSTEM_NAME
    final_log[class="hl-string">'LastDataUpdate'] = last_data_update
    
    class=class="hl-string">"hl-comment"># Reorder columns to the desired format
    final_log = final_log[[
        class="hl-string">'IncidentId', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'SourceSystem', class="hl-string">'LastDataUpdate', 
        class="hl-string">'AssignedTo', class="hl-string">'AssignmentGroup', class="hl-string">'Priority', class="hl-string">'IncidentState'
    ]]

    class=class="hl-string">"hl-comment"># 6. Save to CSV
    output_filename = class="hl-string">'servicenow_incident_event_log.csv'
    final_log.to_csv(output_filename, index=False, date_format=class="hl-string">'%Y-%m-%dT%H:%M:%S.%f')
    print(fclass="hl-string">"\nSuccessfully extracted {len(final_log)} events for {final_log['IncidentId'].nunique()} incidents.")
    print(fclass="hl-string">"Event log saved to {output_filename}")