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# Vercel Web Analytics Implementation ## Summary Successfully implemented Vercel Web Analytics for the MQL5 Trading Automation dashboard project. The implementation follows Vercel's recommended HTML/plain JavaScript approach, which is ideal for this Flask-based application. ## Changes Made ### Modified Files: 1. **dashboard/index.html** - Added Vercel Web Analytics script tags before the closing `</body>` tag - Implemented the standard HTML analytics tracking code that initializes the `window.va` function - Added deferred loading of the Vercel insights script from `/_vercel/insights/script.js` 2. **scripts/web_dashboard.py** - Updated the Flask application's HTML template to include Vercel Web Analytics - Added the same analytics script tags to the dynamically generated HTML - Ensures analytics tracking works on both the static and Flask-rendered pages ### Created Files: 3. **vercel.json** - Created Vercel deployment configuration file - Configured builds for both the Python Flask app and static dashboard files - Set up routing to properly serve the Flask app and static assets - Added production environment variables for Flask ## Implementation Details The implementation uses Vercel's HTML/JavaScript approach for web analytics, which: - Requires no package installation (no @vercel/analytics npm package needed) - Works seamlessly with Flask and static HTML pages - Automatically tracks page views and visitor metrics - Uses deferred script loading for optimal performance - Will be activated once the project is deployed to Vercel with Web Analytics enabled ## Next Steps for Deployment To complete the Vercel Web Analytics setup: 1. **Enable Web Analytics in Vercel Dashboard:** - Go to your Vercel project dashboard - Click the "Analytics" tab - Click "Enable" to activate Web Analytics - This will make the `/_vercel/insights/*` routes available 2. **Deploy to Vercel:** - Run `vercel deploy` or push to your connected Git repository - The analytics will automatically start tracking after deployment 3. **Verify Installation:** - After deployment, visit your site - Open browser DevTools > Network tab - Look for a request to `/_vercel/insights/view` to confirm tracking is active ## Technical Notes - No changes to requirements.txt were needed (Python-only dependencies) - No package manager operations required (npm/yarn/pnpm) - The implementation is framework-agnostic and works with plain HTML/JavaScript - Analytics tracking is non-blocking and won't affect page load performance - The solution supports both the static HTML dashboard and Flask-rendered pages Co-authored-by: Vercel <vercel[bot]@users.noreply.github.com> |
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| .. | ||
| analyze_pr_optimizations.py | ||
| check_ea_status.ps1 | ||
| ci_validate_repo.py | ||
| cleanup.ps1 | ||
| cleanup_accounts.ps1 | ||
| cleanup_guide.md | ||
| cleanup_mql5_folder.ps1 | ||
| cleanup_mt5_terminal.ps1 | ||
| deploy_cloud.py | ||
| deploy_cloud_simple.ps1 | ||
| deploy_dashboard.ps1 | ||
| deploy_exness.ps1 | ||
| deploy_exness_live.ps1 | ||
| deploy_mt5.sh | ||
| example_custom_script.py | ||
| jules_deploy.ps1 | ||
| jules_execute.py | ||
| load_vault.ps1 | ||
| load_vault.py | ||
| merge_best_prs.py | ||
| package_mt5.sh | ||
| pin_prs_issue.md | ||
| README.md | ||
| requirements_bot.txt | ||
| review_pull_requests.py | ||
| review_working_trees.py | ||
| setup_github_secrets.ps1 | ||
| start_bot.ps1 | ||
| start_dev_container.ps1 | ||
| startup.bat | ||
| startup.ps1 | ||
| startup.sh | ||
| startup_orchestrator.py | ||
| sync_github_pages.py | ||
| TELEGRAM_BOT_SETUP.md | ||
| telegram_deploy_bot.py | ||
| test_automation.py | ||
| web_dashboard.py | ||
Scripts Directory
This directory contains automation scripts for the MQL5 trading system.
Automation Scripts
Startup Scripts (Choose one based on your platform)
startup.bat- Windows batch script for simple automationstartup.ps1- PowerShell script with advanced features (recommended for Windows)startup.sh- Bash script for Linux/WSLstartup_orchestrator.py- Python orchestrator (cross-platform)
Helper Scripts
example_custom_script.py- Template for creating your own custom scriptstest_automation.py- Integration tests for all automation scripts
Deployment Scripts
ci_validate_repo.py- Repository validation (used by CI)deploy_mt5.sh- Deploy MQL5 files to MT5 data folderpackage_mt5.sh- Create distribution package
Quick Start
Windows Users
# Run once
.\startup.ps1
# Setup auto-start on boot
.\startup.ps1 -CreateScheduledTask
# Test without executing
.\startup.ps1 -DryRun
Linux/WSL Users
# Run once
./startup.sh
# Setup auto-start on boot (systemd)
./startup.sh --setup-systemd
# Setup auto-start on boot (cron)
./startup.sh --setup-cron
Python Orchestrator (All Platforms)
# Create default configuration
python startup_orchestrator.py --create-config
# Run with default config
python startup_orchestrator.py
# Run with monitoring
python startup_orchestrator.py --monitor 3600
# Dry run
python startup_orchestrator.py --dry-run
Testing
Run the integration tests:
python test_automation.py
Configuration
Edit ../config/startup_config.json to customize:
- What programs to start
- Startup order and delays
- Platform-specific settings
- MT5 terminal path
Documentation
Full documentation available in ../docs/:
Startup_Automation_Guide.md- Complete guideQuick_Start_Automation.md- Quick referenceWindows_Task_Scheduler_Setup.md- Windows setup details
Support
- Issues: GitHub Issues
- Email: Lengkundee01.org@domain.com
- WhatsApp: Agent community