Skip to main content

A Python library for quantitative models.

Project description

Momba Logo

PyPi Package Tests Docs Code Style: Black Gitter DOI

Momba is a Python framework for dealing with quantitative models centered around the JANI-model interchange format. Momba strives to deliver an integrated and intuitive experience to aid the process of model construction, validation, and analysis. It provides convenience functions for the modular construction of models effectively turning Python into a syntax-aware macro language for quantitative models. Momba's built-in exploration engine allows gaining confidence in a model, for instance, by rapidly prototyping a tool for interactive model exploration and visualization, or by connecting it to a testing framework. Finally, thanks to the JANI-model interchange format, several state-of-the-art model checkers and other tools are readily available for model analysis.

Please cite Momba as follows:

Maximilian A. Köhl, Michaela Klauck, and Holger Hermanns: Momba: JANI Meets Python. In: Jan Friso Groote and Kim G. Larsen (eds.) 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021.

Features

  • first-class import and export of JANI models
  • syntax-aware macros for the modular construction of models with Python code
  • built-in exploration engine for PTAs, MDPs and other model types
  • interfaces to state-of-the-art model checkers, e.g., The Modest Toolset and Storm
  • pythonic and statically typed APIs to thinker with formal models

Getting Started

Momba is available from the Python Package Index:

pip install momba[all]

Installing Momba with the all feature flag will install all optional dependencies unleashing the full power and all features of Momba. Check out the examples or read the user guide to learn more.

Rust Crates

The exploration engine of Momba is written in Rust levering PyO3 for Python bindings. In case you are a Rust developer you might find some of the crates in engine/crates useful. In particular, the crate momba-explore allows developing model analysis tools with JANI support in Rust based on Momba's explicit state space exploration engine. The Rust command line tool momba-sidekick directly exposes some of this functionality.

Acknowledgements

This project is partially supported by the ERC Advanced Investigators Grant 695614 (POWVER), by the German Research Foundation (DFG) under grant No. 389792660, as part of TRR 248, and by the Key-Area Research and Development Program Grant 2018B010107004 of Guangdong Province.

Thanks to Sarah Sterz for the awesome Momba logo.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

momba-0.3.2.tar.gz (60.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

momba-0.3.2-py3-none-any.whl (76.2 kB view details)

Uploaded Python 3

File details

Details for the file momba-0.3.2.tar.gz.

File metadata

  • Download URL: momba-0.3.2.tar.gz
  • Upload date:
  • Size: 60.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.9.2

File hashes

Hashes for momba-0.3.2.tar.gz
Algorithm Hash digest
SHA256 2bcbe72af2f6d928cb2f20e4041091c231291163ae420c3cc5bce3d4c00b874c
MD5 909473b2b57fc4a1912c77a5fc262e40
BLAKE2b-256 b4ea1ad8f4e5c49cbc66fee6457548733d4ab79d269c1eb8bb563a1fcc564463

See more details on using hashes here.

File details

Details for the file momba-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: momba-0.3.2-py3-none-any.whl
  • Upload date:
  • Size: 76.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.9.2

File hashes

Hashes for momba-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 14b42594c362818a5d9bea214b46edaec543472644bd14a2435046ec08246800
MD5 422fc14e93b150bdddb9100c2e9b5706
BLAKE2b-256 b7c12cf07b0cc3393df809948d5d556eb3d39d062a49fa8f8a4d4ea06fcbcd05

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page