new-scanner

To add a new data scanner, you create a Python scanner module under the scanners directory and implement a corresponding test file, ensuring integration with the existing pipeline for automated opportunity discovery. This enforces standard patterns for data collection and ticker validation.

The best way to structure a market data scanner is to follow conventional scaffolding with a dedicated scanner file and a matching test file, maintaining consistency with existing repository patterns for error handling and deduplication.

Ticker deduplication works by enforcing repository scanner patterns within the pipeline, ensuring that duplicate trading tickers extracted from external data sources are automatically filtered out during the data collection process.

Yes, you can use this scanner scaffolding to pull data from external sources like social media. It provides a structured blueprint to create scanners for platforms like Reddit or StockTwits and integrate them into your trading pipeline.

Yes, you need to write tests when creating a new Python scanner module. The process requires adding corresponding tests under a specific test file path to validate the scanner's logic before it integrates with the broader pipeline.