- Create `mt5/MQL5/Experts/EXNESS_GenX_Trader.mq5` based on `ExpertMAPSAR_Filtered.mq5`.
- Add ZOLO bridge integration (`SendSignalToBridge`, `EnableWebRequest`, `WebRequestURL`).
- Implement `OnInit` logging to match specified output format (GenX Trader v2.0).
- Implement `OnTimer` heartbeat to send "uptime real data" messages to the bridge every hour.
- Correctly use arrow operators (`->`) for dynamically allocated MQL5 objects.
Update README.md and ZOLO_Plugin_Integration.md to reference the OneDrive folder for bridge files instead of the deprecated GitHub repository. This aligns with the user's latest bridge distribution method.
Added functionality to send trading signals to the ZOLO/Soloist bridge.
- Introduced `EnableWebRequest` and `WebRequestURL` inputs.
- Implemented `SendSignalToBridge` function using `WebRequest`.
- Integrated bridge call in `OnTick` to report signals.
Optimize `scripts/merge_best_prs.py` by using `concurrent.futures.ThreadPoolExecutor` to close duplicate PRs in parallel. This significantly reduces execution time by masking network latency for independent API calls.
Benchmarks show a reduction from ~1.31s to ~0.25s for closing 13 PRs with simulated 0.1s latency.
💡 What: Separated the /health endpoint from the main dashboard rendering logic. It now returns a lightweight JSON response.
🎯 Why: The previous implementation rendered the full Markdown dashboard for every health check, consuming unnecessary CPU and I/O resources during frequent polling.
📊 Impact: Reduces health check processing time from file reading + markdown parsing (~milliseconds) to a simple JSON return (~microseconds).
🔬 Measurement: Verified with new test script scripts/test_web_dashboard.py and updated render.yaml/app.yaml to use the new endpoint.
- Create `app.yaml` for Google App Engine Flexible environment.
- Update `scripts/deploy_cloud.py` to support `gcp` argument with specific instructions for project `infra-outrider-snqdt`.
- Update `mt5/MQL5/Experts/SMC_TrendBreakout_MTF_EA.mq5` default `GeminiModel` to `gemini-1.5-pro` and update comments.
- Consolidate file validation logic into a single loop
- Check file size before reading content to prevent loading large files into memory
- Add error handling for file reading
- Reduce I/O operations and loop iterations
This improves the efficiency of the CI validation script, especially for repositories with many files or when large files are accidentally introduced.
- Implemented a Flask-based web dashboard in `scripts/web_dashboard.py` to serve project status and documentation.
- Integrated the web dashboard into `config/startup_config.json` as a managed component.
- Updated `requirements.txt` with `flask` and `markdown` dependencies.
- Added `/health` endpoint for cloud platform health checks.
- Verified system integrity with existing validation and testing scripts.
Explicitly state that custom MQL5 programs and automation scripts are not supported on the Exness Web Terminal and require the Desktop application.
Updated:
- docs/Cloud_Deployment_Guide.md
- QUICK_REFERENCE.md
- docs/Quick_Start_Automation.md
- docs/ZOLO_Plugin_Integration.md
Clarify in README.md and Exness_Deployment_Guide.md that custom EAs and Indicators are not supported on the Exness Web Terminal and require the Desktop application.
Refactored `scripts/test_automation.py` to run independent integration tests in parallel using `concurrent.futures.ProcessPoolExecutor`.
* 💡 **What:** Used `ProcessPoolExecutor` to run tests concurrently.
* 🎯 **Why:** To improve test suite performance.
* 📊 **Measured Improvement:** ~30% faster (3.3s -> 2.25s).
* **Details:** Used processes instead of threads to ensure `contextlib.redirect_stdout` works correctly for each test without interference.
Refactors the get_branch_info function to use a single, more efficient 'git log' command to fetch commit details. This change reduces the number of subprocess calls from two to one per branch, significantly improving performance, especially in repositories with many branches.
A fallback mechanism is included to handle branches with no new commits, ensuring that the last commit date is still captured correctly and preventing any functional regression.
