Mahmoud Chen
b2ff4ee9dc
- Full 'What Is OrderFlow Analysis?' section explaining microstructure concepts - System overview with ASCII architecture diagram - Detailed data flow pipeline showing all engines and detectors - Module dependency graph with line counts - 5 Core Patterns: detection logic, strength formulas, source data table - Volume Profile Framing: ASCII shape diagrams (P/b/D/Double), qualified levels - State Machine: full lifecycle diagram with all transitions - 29 instruments with per-instrument threshold tables (indices, metals, forex, stocks, crypto) - Dual data feed architecture diagram (MT5 + Bybit) - Dashboard: 8 JS component layout, 9 WebSocket channels with throttling - Database: full 5-table schema diagram - API reference: 16 REST endpoints + strategy status labels + scanner priority scoring - Demo mode documentation with signal quality grading (A+/A/B/C) - Pattern detection deep-dive (absorption 2-method, initiative 5-criteria) - Composite scoring system breakdown with SL/TP calculation table - Signal output examples (entry, daily bias, strategy status) - Badges: Python 3.10+, MIT, 29 instruments, ~12K lines, 16 API endpoints - Added: LICENSE (MIT), CONTRIBUTING.md, issue templates (bug, feature, new instrument), PR template
48 lines
1.1 KiB
Markdown
48 lines
1.1 KiB
Markdown
# Contributing to OrderFlow Analysis Pro
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Thank you for your interest in contributing!
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## Getting Started
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1. Fork the repository
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2. Create a feature branch (`git checkout -b feature/my-feature`)
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3. Make your changes
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4. Run tests: `pytest orderflow_system/test_integration.py`
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5. Submit a pull request
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## Development Setup
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```bash
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pip install -e ".[dev]"
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```
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## Areas for Contribution
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- **New pattern detectors** — add to `patterns/` directory
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- **Additional instruments** — add config in `config/settings.py`
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- **Dashboard improvements** — frontend or API enhancements
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- **Documentation** — guides, tutorials, API docs
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- **Bug fixes** — check GitHub Issues
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## Code Style
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- Python 3.10+ with type hints
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- Dataclasses for data models
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- Async/await for I/O operations
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- Follow existing patterns in each module
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## Reporting Issues
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Use GitHub Issues to report:
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- Bugs or unexpected behavior
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- Feature requests
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- Documentation errors
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- Instrument configuration issues
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## Pull Request Process
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1. Ensure tests pass
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2. Add tests for new features
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3. Update documentation if needed
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4. Keep PRs focused — one feature or fix per PR
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