Skip to content

Stock prediction with Machine Learning (Ongoing Project)

License

Notifications You must be signed in to change notification settings

dalenguyen/stockai

Repository files navigation

Stock AI

PyPI version Build Status

Python module to get stock data from Yahoo! Finance

This is an ongoing project. If you have any requests or contributions, please create a ticket

Install

From PyPI with pip

pip install stockai

Development

Create a virtual environment

python3 -m venv venv
source env/bin/activate

pip3 install -r requirements.txt

For MacOS, you may need to use this command in order to install ciso8601

ARCHFLAGS="-arch x86_64" pip install ciso8601

Running Tests

python -m unittest tests/*

Running Jupyter Notebook

pip install jupyter
jupyter notebook

Usage examples

from stockai import Stock
td = Stock('TD.TO')

print(td.get_summary_profile())
print(td.get_price())
print(td.get_currency())

Get Historical Prices

### The date format should be yyyy-mm-dd
td.get_historical_prices('2019-01-01', '2019-01-05')

### The result is a dictionary with ['volumn', 'low', 'open', 'hight', 'close', 'date', 'adjclose']
{
   'volume':[
      3930300,
      5407700,
      5103400
   ],
   'low':[
      67.12000274658203,
      67.12000274658203,
      67.66999816894531
   ],
   'open':[
      67.51000213623047,
      68.11000061035156,
      68.0
   ],
   'high':[
      68.43000030517578,
      68.11000061035156,
      68.1500015258789
   ],
   'close':[
      68.25,
      67.30000305175781,
      67.9800033569336
   ],
   'date':[
      1546439400,
      1546525800,
      1546612200
   ],
   'adjclose':[
      67.57575225830078,
      66.63513946533203,
      67.30841827392578
   ]
}

Disclaimer

This project is for learning purpose. This is not intended to be investment advice for trading purposes.

  • USE AT YOUR OWN RISK.
  • DO NOT LEVERAGE THIS IN ATTEMPT TO DISRUPT ORDERLY MARKET FUNCTIONS.