Metadata-Version: 2.1
Name: yacu
Version: 1.0.7
Summary: Predict crypto prices with ML.
Home-page: https://github.com/1103s/crypto-bot
Author: Yet Another Crypto Util Team
Author-email: 
License: GPL3
Description: [![Code Is Passing All Unit Tests?](https://github.com/1103s/crypto-bot/actions/workflows/python-app.yml/badge.svg)](https://github.com/1103s/crypto-bot/actions/workflows/python-app.yml) [![Documentation Is Generated?](https://github.com/1103s/crypto-bot/actions/workflows/gh-pages.yml/badge.svg)](https://github.com/1103s/crypto-bot/actions/workflows/gh-pages.yml) [![Publish To Docker](https://github.com/1103s/crypto-bot/actions/workflows/publish.yml/badge.svg)](https://github.com/1103s/crypto-bot/actions/workflows/publish.yml) [![Publish To PyPi](https://github.com/1103s/crypto-bot/actions/workflows/publish-pypi.yml/badge.svg)](https://github.com/1103s/crypto-bot/actions/workflows/publish-pypi.yml)
        
        # Crypto Util
        
        Real time cryptocurrency price data prediction command line utility using machine learning regression. Cross platform compatible on Linux, macOS, and Windows. Written in Python 3. 
        
        ## Install
        
        ### Python
            
        - `pip3 install yacu` or
        
        - `python3 -m pip install yacu`
        
        ### Docker or Podman (CLI ONLY!)
        
        
        - `docker pull yetanothercryptoutil/yacu` or
        
        - `podman pull yetanothercryptoutil/yacu`
        
        **NOTE:** If you use this method, only the CLI features of the program will be
        available.
        
        ### Local installation via anaconda (for development)
        - Download and install anaconda
        - `git clone https://github.com/1103s/crypto-bot.git`
        - `cd crypto-bot`
        - `conda create --name crypto_util python=3.9.7`
        - `source activate crypto_util`
        - `python3 -m pip install -r requirements.txt`
        
        ## Usage
        
        ### GUI
        
        - Default: `yacu`
        
        - Anaconda: `python3 src/gui.py`
        
        - Once installed via pip you will be able to initialize the GUI using the command `yacu` in the command line.
          - In some cases, such as in Linux Mint installations, this will fail. If the happens it means that `.bin` is not in your path (which you can check using `echo $PATH`). Therefore you need to add `.bin` to your path in order to fix this. 
        
        
        ### CLI
        
        - Default: `yacu-cli`
        
        - Podman: `podman run yacu`
        
        - Docker: `docker run yacu`
        
        - Anaconda: `python3 src/crypto_util.py`
        
        #### Local command line usage
        
        - `python3 crypto_util.py --crypto BTC`: The basic functionality requires the user to input at least the cryptocurrency symbol. Note that by default images of the data and predictions are saved to `figures/`
        - `python3 crypto_util.py --crypto ETH --days 10 --lags 80`: More specific flags can be specified, such as the number of days into the future to predict the price.
        - `python3 crypto_util.py --crypto ETH --days 50 --lags 400`: The larger `lags` is the longer the training time, but also the higher the accuracy will be. 
        - `python3 crypto_util.py --ls --source kraken`: In order for the user to see what cryptocurrency symbols are available for an API source, the utility allows for this listing argument with no additional flags. 
        - `python3 crypto_util.py --help`: Prints the usage instructions. 
        
        #### Docker or podman
        
        - `docker run yacu` or
        - `podman run yacu`
        
        ### Example Docker or podman Usage
        - `podman run yacu --crypto ETH`: In this case the settings are set to default. However, the cryptocurrency you want to analyze is a required flag. 
        
        - `podman run yacu --help` displays the usage and required arguments for the utility to work. 
        
        ## Documentation
        
        Documentation can be found [here](https://1103s.github.io/crypto-bot/).
        
        ## Requirements
        
        - docker, podman, or Python3 and pip (or pip3)
        
        ## Installation problems
        - On some Linus distributions the PySide6 import will throw an error like this: `ImportError: /lib/x86_64-linux-gnu/libc.so.6: version GLIBC_2.28 not found`
          - A possible fix for this is `sudo apt-get install libc6`
        
        
        ## Future TODOs and improvements
        
        - Add method to save and load previously trained ML model files using the python library `pickle`.
        - More color palettes for the MainWindow (variations of dark mode)
        - Add moving averages toggling to graph
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
