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This project has been archived.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.
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.
3A. When you cloned this whole repo
For CLI, run run_cli.py with some arguments.
If you installed dependencies in your virtual environment, make sure you enabled it before.
python run_cli.py -d (YOUR_DATA_FOLDER) -o (OUTPUT_FOLDER) -n (YOUR_GG_NICKNAME)
For GUI, simply run run_gui.py or you can directly download binaries from Releases to execute compiled program directly.
When you start the GUI program, then you will be able to view something like above image.
Choose data directory and output directory, input your nickname, then run the process by clicking the bottom button.
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)/dist/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
- Net Profit & Rake chart
- Profitable Tournaments Ratio chart (This is different from ITM; If you made profits by bounty killing without being ITM, then it is also counted as "profitable")
- Average Buy In Amount chart
- Relative Prize Return chart
- ITM Scatters chart
- Bankroll Simulation Analysis chart
- Prize Pie chart
Project details
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