Sibyl Documentation
Introduction
Welcome to the documentation for Sibyl, a Python app for trading using Machine Learning algorithms. This documentation provides an overview of the app's features and how to use them.
Supported APIs
Binance API
Binance Testnet API
Kraken API
Coinbase API
Getting Started
Installation
Clone the repository that contains all the code.
# git clone https://github.com/nMaroulis/sibyl.git
Conda Environment
Install the conda environment found in the conda_env.yml file.
# conda env create -f conda_env.yml
# conda activate sibyl
Python Pip
Install the pip libraries found in the requirements.txt file in the home folder.
# pip install -r requirements.txt
Python Virtual Environment
Create a separate Virtual Environment
Install the pip libraries found in the requirements.txt file.
# python3 -m venv sibyl
# source sibyl/bin/activate
# pip install -r requirements.txt
Docker Container
Open the Project directory through the terminal and locate the Dockerfile
# docker build --tag 'sibyl_image' .
This will give you an image on your local machine that you can create a container from. To do so, you'll need to run the following docker run command.
# docker run --detach 'sibyl_image'
Running the App
First navigate to the sibyl folder in your system and run the main.py script which starts the Frontend and the Backend.
# cd ./sibyl
# python3.11 main.py
Once the app is running, you can access it by opening the provided URL in your web browser.
Features
Algorithmic Trading
Sibyl provides a range of algorithms for generating trade orders based on Machine Learning models. You can choose from different strategies and customize the parameters.
# Example code snippet
Data Analysis
With Sibyl, you can analyze historical data, perform technical analysis, and generate insights to inform your trading decisions.
# Example code snippet
API Reference
Sibyl provides a RESTful API for programmatic access. Use the API endpoints to retrieve data, place trade orders, and more.
# Example API endpoint