fquiachon / plutus_eye

Plutus Eye project Is a Global Market prediction web API that aims to improve and automate analysis of the stock market price direction based on available historical data.

Plutus Eye

Is a Global Market prediction web API that aims to improve and automate analysis of the stock market price direction based on available historical data.

Development

Setup Development environment

1. Create a python 3.x virtual environment

   $ python3 -m venv env

2. Activate virtual environment

   $ <project-dir>\env\Scripts\activate

3. Install the python modules listed in requirements.txt

   • Python Libraries
     • flask==1.1.2
     • flask-jwt-extended==3.25.0
     • flask-pymongo==2.3.0
     • pymongo==3.11.2
     • python-dotenv==0.15.0
     • dnspython==2.0.0
     • pyopenssl==20.0.0

• Environment Variables on .env file
  • FLASK_APP=plutus_eye
  • FLASK_ENV=development
  • MONGO_URI=mongodb+srv://dbuser:dbpassword@<mongodb-host>/<dbname>?retryWrites=true&w=majority
  • JWT_SECRET_KEY='super-secret'
  • GATEWAY_TOKEN = 'bv1io9f48v6o8DemoX'

Database Setup

See https://cloud.mongodb.com for the instruction

API Endpoints

https://<host>:<port>/<API Endpoints>

User Registration and Login End Points

POST /register 201

POST /login 200

Global Markets

Ticker End Points

POST /global/tickers 201

GET /global/tickers 200

DELETE /global/tickers 200

Candlestick Patterns End Points

GET /candle/global/string:ticker 200

POST /candle/global 201

GET /candle/transaction/string:transaction 200

DELETE /candle/transaction/string:transaction 200

DELETE /candle/transaction/ALL 200

High Volume Stock End Point

GET /volume/global/string:ticker 200

POST /volume/global 201

GET /volume/transaction/string:transaction 200

DELETE /volume/transaction/string:transaction 200

DELETE /volume/transaction/ALL 200

PSE Market Tickers

POST /candle/pse 201

GET /candle/pse/string:ticker 200

GET /candle/transaction/string:transaction 200

DELETE /candle/transaction/string:transaction 200

POST /pse/tickers 201

GET /pse/tickers 200

GET /pse/tickers/default 200

DELETE /pse/tickers 200

Volume

POST /volume/global 201

GET /volume/global/string:ticker 200

GET /volume/transaction/string:transaction 200

DELETE /volume/transaction/string:transaction 200

POST /volume/pse 201

GET /volume/pse/string:ticker 200

GET /volume/transaction/string:transaction 200

DELETE /volume/transaction/string:transaction 200

Execution

1. Generate cert.pem and key.pem certificates see https://blog.miguelgrinberg.com/post/running-your-flask-application-over-https

   openssl req -x509 -newkey rsa:4096 -nodes -out cert.pem -keyout key.pem -days 365

2. Run flask app with --cert and --key parameters

   flask run --cert=plutus_eye\cert.pem --key=plutus_eye\key.pem

plutus_eye's Issues

new

My name is Luis, I'm a big-data machine-learning developer, I'm a fan of your work, and I usually check your updates.

I was afraid that my savings would be eaten by inflation. I have created a powerful tool that based on past technical patterns (volatility, moving averages, statistics, trends, candlesticks, support and resistance, stock index indicators).
All the ones you know (RSI, MACD, STOCH, Bolinger Bands, SMA, DEMARK, Japanese candlesticks, ichimoku, fibonacci, williansR, balance of power, murrey math, etc) and more than 200 others.

The tool creates prediction models of correct trading points (buy signal and sell signal, every stock is good traded in time and direction).
For this I have used big data tools like pandas python, stock market libraries like: tablib, TAcharts ,pandas_ta... For data collection and calculation.
And powerful machine-learning libraries such as: Sklearn.RandomForest , Sklearn.GradientBoosting, XGBoost, Google TensorFlow and Google TensorFlow LSTM.

With the models trained with the selection of the best technical indicators, the tool is able to predict trading points (where to buy, where to sell) and send real-time alerts to Telegram or Mail. The points are calculated based on the learning of the correct trading points of the last 2 years (including the change to bear market after the rate hike).

I think it could be useful to you, to improve, I would like to share it with you, and if you are interested in improving and collaborating I am also willing, and if not file it in the box.

If tou want, Please read the readme , and in case of any problem you can contact me ,
If you are convinced try to install it with the documentation.
https://github.com/Leci37/LecTrade/tree/develop I appreciate the feedback