AlgOS: Algorithm Operating System
Algorithm Operating System (AlgOS) is an unopinionated, extensible, modular framework for algorithmic implementations. AlgOS offers numerous features: integration with Optuna for automated hyperparameter tuning; automated argument parsing for generic command-line interfaces; automated registration of new classes; and a centralised database for logging experiments and studies. These features are designed to reduce the overhead of implementing new algorithms and to standardise the comparison of algorithms. The standardisation of algorithmic implementations is crucial for reproducibility and reliability in research. AlgOS combines Abstract Syntax Trees with a novel implementation of the Observer pattern to control the logical flow of algorithmic segments.
Installation
Install via pip:
pip install algos_core
Install from cloned repository:
pip install -e .
Use in python via
import algos
Modules
AlgOS is designed to be extensible for any algorithm that can be constructed as a cyclic or acyclic graph.
Currently the available modules are:
- Reinforcement Learning: AlgOSRL
The intention is to expand this in the future. If you use this library and would like to include a module please let us know.
Examples
The tests contain some examples of how to construct basic algorithms using AlgOS. AlgOSRL contains concrete examples of how to construct reinforcement learning algorithms using AlgOS.
Documentation
TBA
Citing the Project
To cite this repository in publications:
@misc{algos,
title={AlgOS: Algorithm Operating System},
author={Llewyn Salt and Marcus Gallagher},
year={2025},
eprint={2504.04909},
archivePrefix={arXiv},
primaryClass={cs.SE},
url={https://arxiv.org/abs/2504.04909},
}
Metadata
Release files for algos 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| algos-0.1.0.tar.gz | 65.1 kB | Without provenance | Details for algos-0.1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| algos-0.1.0-py3-none-any.whl | Python 3 | none | any | Details for algos-0.1.0-py3-none-any.whl |
Total release size: 141.3 kB
Release files / algos-0.1.0.tar.gz
| Download URL | algos-0.1.0.tar.gz |
|---|---|
| Size | 65.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
9beec74ddcf410e7ff2bae17ed6b2821f64c3d41f1205155c1dfd780118fccb3
|
|
BLAKE2b-256 checksum How to use checksums |
a86b35f09fd933017d755fc691b5f9b77ad6f5eff49597aa3d09027a289ac72c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.12
|
Release files / algos-0.1.0-py3-none-any.whl
| Download URL | algos-0.1.0-py3-none-any.whl |
|---|---|
| Size | 76.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
3f348f32ed02eec5439c1e28e49d2b6aa9fdce8573dcc357e0b92059264e22f9
|
|
BLAKE2b-256 checksum How to use checksums |
7dd92c9c97424bbf769e79aafa11364bb14b72d033c6b3081009ebeedb135b48
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.12
|
Security for algos 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.