tasks.md

Phase 1: Alpha Release (Current state)

Focus areas:

Deliver a working implementation capable of detecting VCP, double tops, and double bottoms.

Include full documentation and a PyPI-ready package distribution.

Ensure all core features are unit tested.

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🚧 Core Tasks

• Implement Candle aggregation modules for EOD and minute based timeframes.

• Implement Pivot detection modules

• Setup pyproject and prepare for packaging & publishing

• State management

  • Maintain internal state to detect and correctly handle duplicate candle or pivot events
  • Prevent redundant processing or repeated event emissions

• Tick aggregation

  • Implement a TickAggregator that converts real-time websocket tick data into 1-minute OHLC candles

• Data storage

  • Develop a storage layer for:
    • Multi-timeframe OHLC
    • Pivot points
    • Detected patterns
  • Support both incremental and bulk inserts
  • Default backend: SQLite or DuckDB
  • Designed to be extensible to other storage engines

• Pattern detection

  • Implement first-phase detection modules:
    • Volatility Contraction Pattern (VCP)
    • Double Tops
    • Double Bottoms

Phase 2: Beta Release

This phase begins once Phase 1 (Alpha) is complete.

Focus areas:

• Expand the set of supported chart patterns beyond the initial prototypes.
• Improve reliability, resolve edge cases, and address remaining bugs.
• Validate performance and stability under real-time data flow.
• Finalize documentation, usage guides, and prepare workflow for online docs.
• Prepare packaging workflow for the first public release to pypi.