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Local analysis tool for Pokercraft in GGNetwork

This project has been archived.

The maintainers of this project have marked this project as archived. No new releases are expected.

Project description

Pokercraft Local

This is a customized visualization tool using downloaded data from Pokercraft in GGNetwork.

Here is working demo.

Dependencies

  • Python 3.12
    • plotly, pandas

I develop most stuffs on WSL and did not tested on other operating systems yet.

How to run

1. Installation

Clone this git repo and install dependencies with pip install -r requirements.txt, optionally on virtual environment. If you want the library files only, you can download from PyPI. Run pip install pokercraft-local.

pip install -r requirements.txt  # When you cloned the whole repo
pip install pokercraft-local  # When you install library only via pip

Or alternatively, you can just download compiled binaries from Releases page. This is the best decision when you don't know programming.

2. Collect your data files from Pokercraft

Download "Game summaries" file by pressing green button on your pokercraft tournament section. If there are too many tournament records on your account, GGNetwork will prevent you from bulk downloading, therefore you may have to download separately monthly or weekly records.

pokercraft_download

After you downloaded, unzip your downloaded .zip files, and put all of them under single folder. The library finds all GG(blabla).txt files recursively by default, so it's ok to make multiple folders inside to make better organization of files.

3. Running a program

For GUI, if you successfully run the program, you will be able to view something like following image.

gui_screen

3A. When you cloned this whole repo

Run run_cli.py with some arguments. Make sure you installed all dependencies before running.

python run_cli.py \
    -d (YOUR_DATA_FOLDER) \  # Specify your data directory
    -o (OUTPUT_FOLDER) \     # Specify your output directory
    -n (YOUR_GG_NICKNAME) \  # Specify your GG nickname
    --lang en \              # Specify your language for the report
    --export-csv \           # Export CSV data file (optional)

Or alternatively, you can run run_gui.py instead.

python run_gui.py

3B. When you installed libraries via pip

Run following Python code to start GUI, and you are good to go.

from pokercraft_local.gui import PokerCraftLocalGUI

if __name__ == "__main__":
    PokerCraftLocalGUI().run_gui()

To do something programatic, check run_cli.py for example references.

3C. When you directly downloaded releases

Execute run_gui-(YOUR_OS)/run_gui/run_gui.exe from downloaded zip file on your local machine.

4. Check results

Go to your output folder and open generated .html file. Note that plotly javascripts are included by CDN, so you need working internet connection to properly view it.

Features

Each plots are now described in plot, so please read when you generated a file. There are 4 sections;

  1. Historical Performance
  2. Relative Prize Returns
  3. Bankroll Analysis with Monte-Carlo simulation
  4. Your Prizes

Project details


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