bencheval

Benchmark evaluation for tabular machine learning: turns a table of per-task results into a leaderboard with Elo, win-rates, average ranks, improvability, and bootstrap confidence intervals. It is the leaderboard engine behind TabArena and is developed in the TabArena repository, but it does not depend on the tabarena package, so any benchmark that produces (method, task, metric_error) rows can use it.

Experimental. The API is still moving. Pin the version you evaluate with; every tabarena release pins the matching bencheval release.

Install

pip install --pre bencheval          # metrics + leaderboards
pip install --pre "bencheval[plot]"  # + matplotlib / seaborn / plotly for the plotting mixin

Releases on PyPI are pre-releases for now, so --pre (or uv pip install --prerelease=allow) is needed. The git checkout is the recommended install for development; see the TabArena README.

Usage

import pandas as pd
from bencheval.evaluator import BenchmarkEvaluator

# One row per (method, task[, seed]); lower `metric_error` is better.
data = pd.DataFrame(
    {
        "method": ["A", "B", "A", "B"],
        "task": ["t1", "t1", "t2", "t2"],
        "seed": [0, 0, 0, 0],
        "metric_error": [0.10, 0.12, 0.30, 0.25],
        "time_train_s": [1.0, 2.0, 1.5, 2.5],
        "time_infer_s": [0.1, 0.2, 0.1, 0.2],
    }
)

evaluator = BenchmarkEvaluator(seed_column="seed")
leaderboard = evaluator.leaderboard(data, include_error=True)
print(leaderboard)

examples/plots/run_generate_custom_leaderboard.py in the TabArena repository shows custom leaderboard metrics, Elo calibration against a reference method, and seed averaging.

License

Apache-2.0. See the LICENSE file shipped with the distribution.

Release files for bencheval 0.1.1.dev20260921091036

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Source distribution (sdist)

Source distribution for bencheval 0.1.1.dev20260921091036
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bencheval-0.1.1.dev20260921091036.tar.gz	55.3 kB	Sep 21, 2026	Details

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Table of built distributions (wheels) for bencheval 0.1.1.dev20260921091036
File	Interpreter	ABI	Platform	Reset
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Total release size: 112.9 kB

Release files / bencheval-0.1.1.dev20260921091036.tar.gz

Download URL	bencheval-0.1.1.dev20260921091036.tar.gz
Size	55.3 kB
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SHA-256 checksum How to use checksums	`2078e44cb02eaad8be8c6876222196ccff1d2f8bc81a21f56e80a69e4214ac76`
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Uploaded via	`uv/0.12.17 {"installer":{"name":"uv","version":"0.12.17","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}`

Release files / bencheval-0.1.1.dev20260921091036-py3-none-any.whl

Download URL	bencheval-0.1.1.dev20260921091036-py3-none-any.whl
Size	57.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`5d4da4145a87d1447b2b3cb01fbfe62335869c2bbeb6e8d82cd8564bcf6ed8bd`
BLAKE2b-256 checksum How to use checksums	`29efc307161913fcc31d12654d1471cd4bc85fbe70fa524bae32232d3af651b9`
Upload date	Sep 21, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`uv/0.12.17 {"installer":{"name":"uv","version":"0.12.17","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}`