Ranking system for table tennis players.
The system keeps a record of championship points and rating points.
Championship points aim at tracking the tournament achievements of players. Their computation is based on the best rounds reached by players in each tournament.
Rating points aim at tracking the relative skill level of players. Their computation is based on the outcomes of one-versus-one matches.
This system has been developed for a Linux environment.
Poetry installation (recommended)
poetry install
System-wide installation
sudo pip install ranking-table-tennis
Single-user installation
pip install --user ranking-table-tennis
Uninstallation
[sudo] pip uninstall ranking-table-tennis
To start using the upload spreadsheets capabilities, gspread requires authentication. Please, follow the recommended steps to get your system ready to upload.
System-wide update
sudo pip install -U ranking-table-tennis
Single-user update (recommended)
pip install --user -U ranking-table-tennis
The commands must be run in a bash terminal.
Fill a sheet with the tournament matches. It must be saved in the Tournaments spreadsheet (xlsx).
Players and Initial Ranking sheets must be in the same spreadsheet (it is used as a database).
Run rtt preprocess
.
The scripts will read the Tournament spreadsheet and will ask for missing information of new players (city, affiliation, initial rating points, and category). This information will be saved in the Players and Initial Ranking sheets.
Run rtt compute
.
It will ask for the tournament that you want to process. 0 will compute all from the beggining. The outcome will be saved in the Ranking spreadsheet.
Run rtt publish
.
It will ask for the index of the tournament that you want to publish. The outcome will be saved in a new spreadsheet.
Install locally from source (source directory will immediately affect the installed package without needing to re-install):
pip install --user --editable .
sudo apt install graphviz (still required?)
Update version at pyproject.toml
and then create a source distribution
poetry build
Upload to PyPI
poetry publish [--dry-run] [--build]
Upload to TestPyPI
poetry publish -r testpypi [--dry-run] [--build]