`bayesianbandits`

Bayesian Multi-Armed Bandits for Python

Problem: Despite having a conceptually simple interface, putting together a multi-armed bandit in Python is a daunting task.

Solution: bayesianbandits is a Python package that provides a simple interface for creating and running Bayesian multi-armed bandits. It is built on top of scikit-learn and scipy, taking advantage of conjugate priors to provide fast and accurate inference.

While the API is still evolving, this library is already being used in production for marketing optimization, dynamic pricing, and other applications. Are you using bayesianbandits in your project? Let us know!

Features

Simple API: bayesianbandits provides a simple interface - most users will only need to call pull and update to get started.
Hybrid bandits with cross-arm learning: Share knowledge across similar arms for faster learning and better sample efficiency.
Fast: bayesianbandits is built on top of already fast scientific Python libraries, but, if installed, will also use SuiteSparse to further speed up matrix operations on sparse matrices. Handling tens or even hundreds of thousands of features in a sparse model is no problem.
sklearn pipeline integration: Use sklearn pipelines and transformers to preprocess data before feeding it into your bandit.
Adversarial bandits (EXP3A): Robust performance in non-stationary and adversarial environments.
Information-directed sampling: InformationDirectedSampling exploits cross-arm correlation under shared learners, balancing expected regret against information gain.
Empirical Bayes estimators: Automatic hyperparameter tuning via evidence maximization, for when you don't want to hand-tune priors or the environment may be non-stationary.
Flexible: Pick from a variety of policy algorithms, including Thompson sampling, upper confidence bound, epsilon-greedy, and information-directed sampling. Pick from a variety of prior distributions, including beta, gamma, normal, normal-inverse-gamma, and GLM posteriors.
Extensible: bayesianbandits provides simple interfaces for creating custom policies and priors.
Well-tested: bayesianbandits is well-tested, with nearly 100% test coverage.

Compatibility

bayesianbandits is tested with Python 3.10, 3.11, 3.12, 3.13, and 3.14 with scikit-learn 1.6.1, 1.7.2, 1.8.0, and 1.9.0.

Requires NumPy >= 2.0 and SciPy >= 1.14. For CHOLMOD sparse support, requires scikit-sparse >= 0.5.0, which in turn requires SuiteSparse >= 7.4.0.

Getting Started

Install this package from PyPI.

pip install -U bayesianbandits

Define a LinearUCB contextual bandit with a normal prior.

import numpy as np
from bayesianbandits import (
    Arm,
    NormalInverseGammaRegressor,
    ContextualAgent,
    UpperConfidenceBound,
)

arms = [
    Arm(1, learner=NormalInverseGammaRegressor()),
    Arm(2, learner=NormalInverseGammaRegressor()),
    Arm(3, learner=NormalInverseGammaRegressor()),
    Arm(4, learner=NormalInverseGammaRegressor()),
]

policy = UpperConfidenceBound(alpha=0.84)

Instantiate the agent and pull an arm with context.

agent = ContextualAgent(arms, policy)

context = np.array([[1, 0, 0, 0]])

# Can be constructed with sklearn, formulaic, patsy, etc...
# context = formulaic.Formula("1 + article_number").get_model_matrix(data)
# context = sklearn.preprocessing.OneHotEncoder().fit_transform(data)

agent.pull(context)

Update the bandit with the reward.

agent.update(context, np.array([15.0]))

For shared learning across arms via the design matrix:

from bayesianbandits import LipschitzContextualAgent, ArmColumnFeaturizer, NormalRegressor, ThompsonSampling

# Single shared learner across all arms
agent = LipschitzContextualAgent(
    arms=[Arm(i) for i in range(100)],  # 100 arms sharing knowledge
    learner=NormalRegressor(alpha=1.0, beta=1.0),
    arm_featurizer=ArmColumnFeaturizer(column_name='article_id'),
    policy=ThompsonSampling()
)

That's it! Check out the documentation for more examples.

Metadata

Release files for bayesianbandits 1.5.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for bayesianbandits 1.5.0
File	Size	Uploaded	Provenance
bayesianbandits-1.5.0.tar.gz	489.0 kB	Oct 22, 2026	Without provenance	Details

Built distributions (wheels)

Table of built distributions (wheels) for bayesianbandits 1.5.0
File	Interpreter	ABI	Platform	Reset
bayesianbandits-1.5.0-cp314-cp314-win_amd64.whl 426.8 kB Oct 22, 2026 Without provenance	CPython 3.14	CPython 3.14	Windows x86-64	Details
bayesianbandits-1.5.0-cp314-cp314-musllinux_1_2_x86_64.whl 919.6 kB Oct 22, 2026 Without provenance	CPython 3.14	CPython 3.14	Linux musl 1.2+ x86-64	Details
bayesianbandits-1.5.0-cp314-cp314-musllinux_1_2_aarch64.whl 903.4 kB Oct 22, 2026 Without provenance	CPython 3.14	CPython 3.14	Linux musl 1.2+ ARM64	Details
bayesianbandits-1.5.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 918.1 kB Oct 22, 2026 Without provenance	CPython 3.14	CPython 3.14	Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64	Details
bayesianbandits-1.5.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl 911.7 kB Oct 22, 2026 Without provenance	CPython 3.14	CPython 3.14	Linux glibc 2.17+ ARM64, Linux glibc 2.28+ ARM64	Details
bayesianbandits-1.5.0-cp314-cp314-macosx_11_0_arm64.whl 439.7 kB Oct 22, 2026 Without provenance	CPython 3.14	CPython 3.14	macOS 11.0+ ARM64	Details
bayesianbandits-1.5.0-cp313-cp313-win_amd64.whl 425.6 kB Oct 22, 2026 Without provenance	CPython 3.13	CPython 3.13	Windows x86-64	Details
bayesianbandits-1.5.0-cp313-cp313-musllinux_1_2_x86_64.whl 924.1 kB Oct 22, 2026 Without provenance	CPython 3.13	CPython 3.13	Linux musl 1.2+ x86-64	Details
bayesianbandits-1.5.0-cp313-cp313-musllinux_1_2_aarch64.whl 903.8 kB Oct 22, 2026 Without provenance	CPython 3.13	CPython 3.13	Linux musl 1.2+ ARM64	Details
bayesianbandits-1.5.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 922.1 kB Oct 22, 2026 Without provenance	CPython 3.13	CPython 3.13	Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64	Details
bayesianbandits-1.5.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl 913.9 kB Oct 22, 2026 Without provenance	CPython 3.13	CPython 3.13	Linux glibc 2.17+ ARM64, Linux glibc 2.28+ ARM64	Details
bayesianbandits-1.5.0-cp313-cp313-macosx_11_0_arm64.whl 439.2 kB Oct 22, 2026 Without provenance	CPython 3.13	CPython 3.13	macOS 11.0+ ARM64	Details
bayesianbandits-1.5.0-cp312-cp312-win_amd64.whl 425.9 kB Oct 22, 2026 Without provenance	CPython 3.12	CPython 3.12	Windows x86-64	Details
bayesianbandits-1.5.0-cp312-cp312-musllinux_1_2_x86_64.whl 936.0 kB Oct 22, 2026 Without provenance	CPython 3.12	CPython 3.12	Linux musl 1.2+ x86-64	Details
bayesianbandits-1.5.0-cp312-cp312-musllinux_1_2_aarch64.whl 910.0 kB Oct 22, 2026 Without provenance	CPython 3.12	CPython 3.12	Linux musl 1.2+ ARM64	Details
bayesianbandits-1.5.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 935.7 kB Oct 22, 2026 Without provenance	CPython 3.12	CPython 3.12	Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64	Details
bayesianbandits-1.5.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl 920.1 kB Oct 22, 2026 Without provenance	CPython 3.12	CPython 3.12	Linux glibc 2.17+ ARM64, Linux glibc 2.28+ ARM64	Details
bayesianbandits-1.5.0-cp312-cp312-macosx_11_0_arm64.whl 439.4 kB Oct 22, 2026 Without provenance	CPython 3.12	CPython 3.12	macOS 11.0+ ARM64	Details
bayesianbandits-1.5.0-cp311-cp311-win_amd64.whl 425.9 kB Oct 22, 2026 Without provenance	CPython 3.11	CPython 3.11	Windows x86-64	Details
bayesianbandits-1.5.0-cp311-cp311-musllinux_1_2_x86_64.whl 935.6 kB Oct 22, 2026 Without provenance	CPython 3.11	CPython 3.11	Linux musl 1.2+ x86-64	Details
bayesianbandits-1.5.0-cp311-cp311-musllinux_1_2_aarch64.whl 921.9 kB Oct 22, 2026 Without provenance	CPython 3.11	CPython 3.11	Linux musl 1.2+ ARM64	Details
bayesianbandits-1.5.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 932.7 kB Oct 22, 2026 Without provenance	CPython 3.11	CPython 3.11	Linux glibc 2.28+ x86-64, Linux glibc 2.17+ x86-64	Details
bayesianbandits-1.5.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl 928.4 kB Oct 22, 2026 Without provenance	CPython 3.11	CPython 3.11	Linux glibc 2.28+ ARM64, Linux glibc 2.17+ ARM64	Details
bayesianbandits-1.5.0-cp311-cp311-macosx_11_0_arm64.whl 439.0 kB Oct 22, 2026 Without provenance	CPython 3.11	CPython 3.11	macOS 11.0+ ARM64	Details
bayesianbandits-1.5.0-cp310-cp310-win_amd64.whl 426.4 kB Oct 22, 2026 Without provenance	CPython 3.10	CPython 3.10	Windows x86-64	Details
bayesianbandits-1.5.0-cp310-cp310-musllinux_1_2_x86_64.whl 910.9 kB Oct 22, 2026 Without provenance	CPython 3.10	CPython 3.10	Linux musl 1.2+ x86-64	Details
bayesianbandits-1.5.0-cp310-cp310-musllinux_1_2_aarch64.whl 897.8 kB Oct 22, 2026 Without provenance	CPython 3.10	CPython 3.10	Linux musl 1.2+ ARM64	Details
bayesianbandits-1.5.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 909.3 kB Oct 22, 2026 Without provenance	CPython 3.10	CPython 3.10	Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64	Details
bayesianbandits-1.5.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl 904.7 kB Oct 22, 2026 Without provenance	CPython 3.10	CPython 3.10	Linux glibc 2.17+ ARM64, Linux glibc 2.28+ ARM64	Details
bayesianbandits-1.5.0-cp310-cp310-macosx_11_0_arm64.whl 440.3 kB Oct 22, 2026 Without provenance	CPython 3.10	CPython 3.10	macOS 11.0+ ARM64	Details

Total release size: 23.2 MB

Release files / bayesianbandits-1.5.0.tar.gz

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Size	439.2 kB
Tags	CPython 3.13 macOS 11.0+ ARM64
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Release files / bayesianbandits-1.5.0-cp312-cp312-win_amd64.whl

Download URL	bayesianbandits-1.5.0-cp312-cp312-win_amd64.whl
Size	425.9 kB
Tags	CPython 3.12 Windows x86-64
SHA-256 checksum How to use checksums	`631790a1a0324d0a1b2e0b2840a074a63f908d373d1ed210c754fe1f3d5e232a`
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Release files / bayesianbandits-1.5.0-cp312-cp312-musllinux_1_2_x86_64.whl

Download URL	bayesianbandits-1.5.0-cp312-cp312-musllinux_1_2_x86_64.whl
Size	936.0 kB
Tags	CPython 3.12 Linux musl 1.2+ x86-64
SHA-256 checksum How to use checksums	`7a3e67ad5012fcc835e706a7d382357634b6baa727922b36a54add22b486b662`
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Release files / bayesianbandits-1.5.0-cp312-cp312-musllinux_1_2_aarch64.whl

Download URL	bayesianbandits-1.5.0-cp312-cp312-musllinux_1_2_aarch64.whl
Size	910.0 kB
Tags	CPython 3.12 Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`c45096101566553c8ce5f6a9bb863b5562a6ee5d5611b7659c51c2fe16bf1226`
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Release files / bayesianbandits-1.5.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

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Size	935.7 kB
Tags	CPython 3.12 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum How to use checksums	`31cfe9c294dfbeb55bdb083f16010bfe76dad8516eda47364de392bb5ecee647`
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Release files / bayesianbandits-1.5.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl

Download URL	bayesianbandits-1.5.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Size	920.1 kB
Tags	CPython 3.12 Linux glibc 2.17+ ARM64 Linux glibc 2.28+ ARM64
SHA-256 checksum How to use checksums	`214ab83ac18a28d3e13b144fa86458fa4d4bd780baeab122313280d0f31be1b5`
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Release files / bayesianbandits-1.5.0-cp312-cp312-macosx_11_0_arm64.whl

Download URL	bayesianbandits-1.5.0-cp312-cp312-macosx_11_0_arm64.whl
Size	439.4 kB
Tags	CPython 3.12 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`a5ee884f4457a1ba8fda940f4fa6cad5743b42088ddcc83a4f792a262ceceecc`
BLAKE2b-256 checksum How to use checksums	`0d5d78e682bfbf2358abbf27ebb9ff3ed7893139911b200bde39503dbf8e8153`
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Release files / bayesianbandits-1.5.0-cp311-cp311-win_amd64.whl

Download URL	bayesianbandits-1.5.0-cp311-cp311-win_amd64.whl
Size	425.9 kB
Tags	CPython 3.11 Windows x86-64
SHA-256 checksum How to use checksums	`8fc2082191614e213eacc848669b6bca459e3bbd806c823c542469d12719aa4e`
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Release files / bayesianbandits-1.5.0-cp311-cp311-musllinux_1_2_x86_64.whl

Download URL	bayesianbandits-1.5.0-cp311-cp311-musllinux_1_2_x86_64.whl
Size	935.6 kB
Tags	CPython 3.11 Linux musl 1.2+ x86-64
SHA-256 checksum How to use checksums	`d54eb3caacec6e6e6aae667bcca85dcf44bd79f2f00db78db5d66a2189c3aa09`
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Release files / bayesianbandits-1.5.0-cp311-cp311-musllinux_1_2_aarch64.whl

Download URL	bayesianbandits-1.5.0-cp311-cp311-musllinux_1_2_aarch64.whl
Size	921.9 kB
Tags	CPython 3.11 Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`45da010598d08823cc784aefdb36a03de513d7e299e63abdbbd141f0035e7c88`
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Release files / bayesianbandits-1.5.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL	bayesianbandits-1.5.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size	932.7 kB
Tags	CPython 3.11 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum How to use checksums	`0e236df50c545797cbf5e522a40c5b70dddafbd953b6a335e8b704293444c5bc`
BLAKE2b-256 checksum How to use checksums	`eba2f75d8f7d9379310f6fe576f24948e970b6273afcd35483d34aae5ca9a8d1`
Upload date	Oct 22, 2026
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Release files / bayesianbandits-1.5.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl

Download URL	bayesianbandits-1.5.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Size	928.4 kB
Tags	CPython 3.11 Linux glibc 2.17+ ARM64 Linux glibc 2.28+ ARM64
SHA-256 checksum How to use checksums	`20be51123004faa1104449a0288af14a35d4f9ca2fdde58243d821abf27d983e`
BLAKE2b-256 checksum How to use checksums	`7b86c96fca1eedafcadd56d0b0b0b6f607f4a5708cc8da86640f6ce9eb699f94`
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Release files / bayesianbandits-1.5.0-cp311-cp311-macosx_11_0_arm64.whl

Download URL	bayesianbandits-1.5.0-cp311-cp311-macosx_11_0_arm64.whl
Size	439.0 kB
Tags	CPython 3.11 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`9d2efe4b80dd295e5e4c7bbd1094cca8590aa9e3fce8c408e3882ce2818ef9d2`
BLAKE2b-256 checksum How to use checksums	`f87b3ce3c0fc7799dfa093cbfee76869a5f4b72bfb50644dbde82a9ad631faaa`
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Release files / bayesianbandits-1.5.0-cp310-cp310-win_amd64.whl

Download URL	bayesianbandits-1.5.0-cp310-cp310-win_amd64.whl
Size	426.4 kB
Tags	CPython 3.10 Windows x86-64
SHA-256 checksum How to use checksums	`50124afb821bf57083d924441da6e685d4f46788da3ed8616ff6e20b3693d202`
BLAKE2b-256 checksum How to use checksums	`685fb3994176361603fbcdd1297bdd37f0f6a17fa82a5ab41af4a49e55af03b3`
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Release files / bayesianbandits-1.5.0-cp310-cp310-musllinux_1_2_x86_64.whl

Download URL	bayesianbandits-1.5.0-cp310-cp310-musllinux_1_2_x86_64.whl
Size	910.9 kB
Tags	CPython 3.10 Linux musl 1.2+ x86-64
SHA-256 checksum How to use checksums	`579482c9933a17d4bdb4a6837c87992f4bdf5d3abe2a1a97cdcabe7d5d6e716f`
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Release files / bayesianbandits-1.5.0-cp310-cp310-musllinux_1_2_aarch64.whl

Download URL	bayesianbandits-1.5.0-cp310-cp310-musllinux_1_2_aarch64.whl
Size	897.8 kB
Tags	CPython 3.10 Linux musl 1.2+ ARM64
SHA-256 checksum How to use checksums	`61c8c8e29d4d8af1f89841f9d43455eaaf8f83ba7dc22e197692e78468198631`
BLAKE2b-256 checksum How to use checksums	`4414255cec6fb55bf44571a46c641fd17030a468269d25e317cb4463738e32da`
Upload date	Oct 22, 2026
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Uploaded via	`uv/0.13.4 {"installer":{"name":"uv","version":"0.13.4","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 / bayesianbandits-1.5.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL	bayesianbandits-1.5.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size	909.3 kB
Tags	CPython 3.10 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum How to use checksums	`83a13a77d4b0cfbbbff6549a3433b88e760b663ad792b587560ff7647bd1a8e0`
BLAKE2b-256 checksum How to use checksums	`8741379d9d4bc1d16e96e5b1c67173941d5666fda9025622b8d0913d5c0235f9`
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Uploaded via	`uv/0.13.4 {"installer":{"name":"uv","version":"0.13.4","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 / bayesianbandits-1.5.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl

Download URL	bayesianbandits-1.5.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Size	904.7 kB
Tags	CPython 3.10 Linux glibc 2.17+ ARM64 Linux glibc 2.28+ ARM64
SHA-256 checksum How to use checksums	`f0205a536aa1abd5ae8b1c8d70d30a4c3de014a345a0bf646560c2d14f1908c7`
BLAKE2b-256 checksum How to use checksums	`5765ee1513a464f9970501e808184481b45a85078421aa32de0b3d4afd992a38`
Upload date	Oct 22, 2026
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Uploaded via	`uv/0.13.4 {"installer":{"name":"uv","version":"0.13.4","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 / bayesianbandits-1.5.0-cp310-cp310-macosx_11_0_arm64.whl

Download URL	bayesianbandits-1.5.0-cp310-cp310-macosx_11_0_arm64.whl
Size	440.3 kB
Tags	CPython 3.10 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`cb5a4f3522306f1795baf95b8b6d73f2df47a86e811e42cb82198dea387141d8`
BLAKE2b-256 checksum How to use checksums	`f1b00ea183e36a4f17d629f642b23b962bc093a094eabf07f17d473e44d8eadf`
Upload date	Oct 22, 2026
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Uploaded via	`uv/0.13.4 {"installer":{"name":"uv","version":"0.13.4","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}`

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