sambo

SAMBO: Sequential And Model-Based (Bayesian) Optimization of black-box objective functions.

Installation

$ pip install sambo
# or
$ pip install 'sambo[all]'   # Pulls in Matplotlib, scikit-learn

Python 3+
Simple usage, standard API.
Algorithms prioritize to minimize number of evaluations of the objective function: SHGO, SCE-UA and SMBO available.
Minimal dependencies: NumPy, SciPy (scikit-learn & Matplotlib optional).
State-of-the-art performance—see benchmark results against other common optimizer implementations.
Integral, real (floating), and categorical dimensions.
Fast approximate global black-box optimization.
Beautiful Matplotlib charts.

Check CONTRIBUTING.md for hacking details.

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

Source distribution for sambo 1.25.2
File	Size	Uploaded
sambo-1.25.2.tar.gz	60.2 kB	Jul 10, 2025	Details

Table of built distributions (wheels) for sambo 1.25.2
File	Interpreter	ABI	Platform	Reset
sambo-1.25.2-py3-none-any.whl 54.6 kB Jul 10, 2025	Python 3	none	any	Details

Total release size: 114.8 kB

Download URL	sambo-1.25.2.tar.gz
Size	60.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`58e08d3eb4c83c9ebb305284a210de256be9e333c13efa26ae919663818a37e5`
BLAKE2b-256 checksum How to use checksums	`dcc83d649256cf8316157a60f03f94db3ac3bdc79b8a8af4de8b3d2e3f244269`
Upload date	Jul 10, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.0.1 CPython/3.11.2`

Download URL	sambo-1.25.2-py3-none-any.whl
Size	54.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`e67206342c3ee6ce5ef2b25b7ff3176139d073f35a4493b8067355694b721602`
BLAKE2b-256 checksum How to use checksums	`b1b8fac47182d5735cdf8f02a378ad96052e67d748a685e9243ae4934a0bfcba`
Upload date	Jul 10, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.0.1 CPython/3.11.2`