gradual-mining 0.3.0

Unified Python package for gradual pattern mining with multiple algorithms

GPMF — Gradual Pattern Mining Framework

A Python library for gradual pattern mining with a unified scikit-learn-style API.

Installation

pip install gradual-mining

Pre-built wheels are available for Linux, macOS and Windows (x86_64 and arm64). The ParaMiner algorithm includes an optional Rust extension for multi-core acceleration — it is compiled into the wheel automatically and falls back to a pure-Python implementation if unavailable.

Quick start

from gpmf.algorithms.graank import GRAANK

model = GRAANK(min_support=0.5)
patterns = model.mine("data.csv")

for p in patterns:
    print(p.to_string(), ":", p.support)

All algorithms share the same interface:

model.fit(data)              # data can be a CSV path, DataFrame, or GradualDataset
patterns = model.get_patterns()
result   = model.get_result()  # includes execution time, metadata

ParaMiner with Rust acceleration

from gpmf.algorithms.closed.paraminer_algorithm import ParaMiner

model = ParaMiner(min_support=0.5, use_rust=True, num_threads=4)
patterns = model.mine("data.csv")

Available algorithms

Algorithm	Key	Authors	Reference
GRAANK	graank	Laurent, Lesot & Rifqi (2010)	paper
GRITE	grite	Di-Jorio, Laurent & Teisseire (2009)	paper
SGrite	sgrite / sgopt / sg1 / sgb1 / sgb2	Tayou Djamegni, Tabueu Fotso & Kenmogne (2021)	paper
ParaMiner	paraminer	Négrevergne, Termier, Rousset & Méhaut (2014)	paper
ACO-GRAANK	ant-graank	Owuor, Laurent & Orero (2019)	paper
TGrad	tgrad	Owuor, Laurent & Orero (2019)	paper
MSGP	msgp	Lonlac, Doniec, Lujak & Lecoeuche (2020)	paper
GLCM	glcm	Do, Termier, Laurent et al. (2015)	paper
PGLCM	pglcm	Do, Termier, Laurent et al. (2015)	paper

Pruning criterion

Criterion	Applies to	Authors
Row–Column pruning (--use-rc-pruning)	GRITE, SGrite, GLCM	Kamga Nguifo, Lonlac, Fleury & Mephu Nguifo (2025) — paper

CLI

# List available algorithms
gradual-mine --list

# Mine patterns
gradual-mine graank data.csv --min-support 0.5

# Save results
gradual-mine graank data.csv --min-support 0.5 --output results.json --csv results.csv

# Parallel execution
gradual-mine paraminer data.csv --min-support 0.5 --n-jobs -1

Development

git clone https://github.com/your-org/gpmf
cd gpmf
uv sync --dev
uv run pytest

To build with the Rust extension locally:

pip install maturin
maturin develop --release

License

MIT