https://github.com/rafapi/fastapi-prophet

Stock Market predictions with Prophet and FastAPI
https://github.com/rafapi/fastapi-prophet

async docker fastapi fbprophet python

Last synced: 4 days ago
JSON representation

Stock Market predictions with Prophet and FastAPI

• Host: GitHub
• URL: https://github.com/rafapi/fastapi-prophet
• Owner: rafapi
• License: mit
• Created: 2020-07-15T08:16:19.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2021-12-22T07:41:53.000Z (about 3 years ago)
• Last Synced: 2023-09-02T17:23:53.931Z (over 1 year ago)
• Topics: async, docker, fastapi, fbprophet, python
• Language: Python
• Homepage:
• Size: 9.27 MB
• Stars: 11
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Stock Market predictions with Prophet and FastAPI



   

   

      

   

   

   

   



Train prophet models and run stock market predictions for a given ticker


## Details

* 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

## 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

#### CRUD

   * 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

## Future additions

* Authentication

* Extra information fields based on third-party content

* Add plots and images if available from source

* Input training timeframe

* User Interface