Trading-Simulator

Features

• Used Asynchrous version of Binancev3 rest api for fetching of data and live streaming of data.
• Built an ML model using Gradient boosting, Random Forests, KNN in sklearn and numba.

# install dependencies
pip install -r requirements.txt

Getting a ticker's data

Fetches the data from Binance and stores in sqlite.

# you can pass in an argument 
# consisting of the ticker that you want

In Binance Connector
$ python historical.py BTCUSDT "1 Dec, 2017" "16 Jan, 2022" 1HOUR

Traning ML Ensemble Model

In ML model 

$ python train.py

# show entries as a graph
$ python read_db.py --graph

Executing the trade bot

Please let the asyncio_run_ticker.py script run for a few minutes first before initialising this script. WARNING: Please check that you have set the correct ENV in .env file before running the following.

$ python trade_bot.py