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Project Brief: Optimized & Modular RSI Divergence Detection Module (MQL5)

MQL5 Experten Skripte Debugging eines Roboters/Indikators

Spezifikation


I am looking to develop a highly optimized and fully modular script in MQL5 specifically for detecting RSI Divergences. This script will serve as a foundational building block to be integrated into a larger, comprehensive Expert Advisor (EA) later. Therefore, execution speed, strict logic, and a clean codebase are my absolute top priorities.


Here are the core technical requirements for this project:

1. MQL5 Performance & Memory Management (Crucial):

Efficient Handle Creation: The RSI indicator handle must be strictly declared and initialized only once within the OnInit() function.

Optimized Data Retrieval: Use CopyBuffer() efficiently to fetch only the newly required data points per tick or per new bar.

Zero Memory Leaks: Under no circumstances should the indicator be re-called or recalculated from scratch on every OnTick(). The module must be extremely lightweight.

2. Customizable Divergence Selection (Important):

The algorithm must be capable of mathematically detecting BOTH Regular and Hidden divergences.

However, I require external input parameters (e.g., boolean variables like Enable_Regular_Div and Enable_Hidden_Div, or a dropdown Enum) that allow me to strictly control which signals are active and displayed. I must be able to select:

Only Regular Divergences

Only Hidden Divergences

Both simultaneously
This flexibility is critical for my backtesting and strategy optimization.

3. High-Efficiency Detection & Strict Confirmation:

Minimal Lag: The algorithm scanning for peaks and troughs must be mathematically optimized.

No Repainting: The divergence signals must be robust and definitively confirmed (e.g., strictly evaluated after the candle closes). Once a signal is printed or registered, it must not repaint or disappear.

4. Clean & Modular Architecture (Integration-Ready):

Encapsulation: The logic must be cleanly separated into modular functions or classes.

No Global Variable Conflicts: Avoid using loosely defined global variables that could clash when I include this .mqh file or logic into my master EA.

Clear Inputs: All customizable parameters (RSI Period, applied price, peak/trough lookback periods, and the divergence type toggles mentioned above) must be clearly defined as input variables.

5. Documentation:

Please include professional, brief comments explaining the core logic, especially around the loops used for identifying the historical pivots/fractals for the divergence.

Please review these requirements and let me know your approach to ensuring the code remains as fast and modular as requested.

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Projektdetails

Budget
80 - 120 USD
Ausführungsfristen
bis 5 Tag(e)