Skip to content

Latest commit

 

History

History
66 lines (44 loc) · 2.37 KB

README.md

File metadata and controls

66 lines (44 loc) · 2.37 KB
Raw

Kriptomist

Python3 Framework for Crypto-Currency Price Prediction using Fundamental Analysis.

Bitcoin price, supply with reddit subscribers, Tether supply, transactions squared, difficulty and hashrate

Author:

  • Jure V. <jure42@protonmail.com>

Base metrics

  • price (in USD and BTC)
  • supply
  • subreddit subscribers
  • twitter followers
  • transaction count
  • mining difficulty
  • hashrate

Derived metrics

  • daily, weekly and monthly change in subscribers/followers
  • price prediction based on current price change versus subscriber/follower count change

Setup

To setup and play with Kriptomist we recommend using the IPython shell.

Requirements

  • If you are on a Windows machine, we recommend Anaconda Python distribution

  • IPython shell ($ sudo apt install ipython3)

  • Open a terminal (Anaconda Prompt on Windows) and install required Python modules:

    pip install -r requirements.txt

Database

Usage

Using IPython, you can run scripts using run IPython command. The advantage is that you keep the global namespace in the shell after the script was executed.

Updating data for the current day

In [1]: run kriptomist.py

This populates the database with (reddit, twitter, ...) data at the time the command was executed. It also outputs 2 HTML files:

  • html/table_{day}.html (all coins)
  • html/binance_table_{day}.html (only coins traded on Binance are listed here)

Setting NUM_COINS

The default number of coins to process is initialy set to 10. To process more coins, create a file named local_config.py and specify number of coins you want to process:

NUM_COINS = 100

The maximum value for NUM_COINS is 5000.

Displaying chart for a specific coin

In [1]: run kriptomist.py bitcoin

Once you've looked at the html table and want to analyze a specific coin (in this case - bitcoin), you can run the above command (replace bitcoin with the name of your chosen coin).

Customizing chart metrics

Look for CHART_METRICS in config.py, copy it to local_config.py and comment/uncomment desired metrics - that's it. Feel free to suggest improvements / create pull requests. Have fun.