- Dev dependencies
- FastAPI: https://fastapi.tiangolo.com
- Docker: https://docs.docker.com/
- SQLAlchemy-Core: https://docs.sqlalchemy.org/en/14/core
- Databases (Async SQLAlchemy Core queries): https://github.com/encode/databases
- fbprophet (Time Series forecasting): https://facebook.github.io/prophet
- yfinance (market data downloader): https://github.com/ranaroussi/yfinance
- Testing:
- pytest: https://docs.pytest.org/en/stable
- pytest-cov: https://github.com/pytest-dev/pytest-cov
- Codecov: https://docs.codecov.io
- Linting and Formatting:
- black: https://github.com/psf/black
- flake8: https://flake8.pycqa.org/en/latest
- isort: https://pycqa.github.io/isort
- Continuous Integration by Github Actions
- Train the model for a ticker
- Check the weekly prediction for a previously trained ticker
- Check the weekly prediction for all the trained tickers
- Create prediction for that ticker
- Read results for all tickers or for individual ones
- Updating the info for a ticker should be done by creating a new one due to its time-sensitiveness
- Delete a specific ticker
- Authentication
- Extra information fields based on third-party content
- Add plots and images if available from source
- Input training timeframe
- User Interface