Ranking Python Packages

rank-bm25

A Collection of BM25 Algorithms in Python

flashrank

Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.

openskill

Multiplayer Rating System. No Friction.

tensorflow-ranking

Learning to Rank in TensorFlow

choix

Inference algorithms for models based on Luce's choice axiom

recommenders

Best Practices on Recommendation Systems

evalica

Evalica, your favourite evaluation toolkit

futuresearch

Your team of research agents. Or give researchers to your AI.

torchsort

Fast, differentiable sorting and ranking in PyTorch

caserecommender

Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems

rstt

Ranking Simulation Testing Tool

dep-rank

Rank a GitHub project's dependents by stars or trust — CLI that scrapes dependents and enriches via GraphQL.

allrank

allRank is a framework for training learning-to-rank neural models

ranklab

Learning to Rank: differentiable ranking, LTR losses (RankNet, LambdaRank, ApproxNDCG, ListNet, ListMLE), and IR evaluation metrics.

rexmex

A general purpose recommender metrics library for fair evaluation.

ranking-table-tennis

Ranking system based on rating points for table tennis players.

discordlevelingcard

A library with leveling cards for your discord bot.

georank

Generic weighted-criteria ranking engine — score and rank places by normalized, weighted factors. Zero deps, JS + Python. Powers georank.place.

scorio

Bayes@N [ICLR'26], Ranking LLMs [ACL'26 Main]: Statistical evaluation, comparison, and ranking of Large Language Models

fast-forward-indexes

Efficient interpolation-based ranking on CPUs

kickscore

Pairwise comparisons with flexible time-dynamics.

bm25-rs

A Collection of BM25 Algorithms in Python

mallows-models

Mallows Kendall. A python package to for Mallows Model with top-k and complete rankings using Kendall's-tau distance. By Ahmed Boujaada, Fabien Collas and Ekhine Irurozki. We present methods for inference in the Mallows Model (MM), the best-known distribution for permutations. This is short tutorial for top-k rankings and complete rankings under the Kendall's-tau distance. Theoretical details are given in Fabien Collas and Ekhine Irurozki (2020). Concentric mixtures of Mallows Models for top-k rankings: sampling and identifiability. In: International Conference on Machine Learning (ICML 21). 2021.

bwsample

Sampling algorithm for best-worst scaling sets.