%global _empty_manifest_terminate_build 0
Name: python-momba
Version: 0.6.7
Release: 1
Summary: A Python library for quantitative models.
License: MIT OR Apache-2.0
URL: https://momba.dev/
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/8a/11/89a1b70b51d46eaeaa36f01830439e1325ded86a7db01a82e5bf4b66071f/momba-0.6.7.tar.gz
BuildArch: noarch
Requires: python3-click
Requires: python3-docker
Requires: python3-gym
Requires: python3-immutables
Requires: python3-momba_engine
Requires: python3-mxu
Requires: python3-torch
%description
_Momba_ is a Python framework for dealing with quantitative models centered around the [JANI-model](http://www.jani-spec.org/) 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.
For academic publications, please cite Momba as follows:
Maximilian A. KΓΆhl, Michaela Klauck, and Holger Hermanns: _Momba: JANI Meets Python_. In: J. F. Groote and K. G. Larsen (eds.) 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021. DOI: https://doi.org/10.1007/978-3-030-72013-1_23.
In case you made anything with Momba or plan to do so, we would highly appreciate if you let us know about your exciting project by [opening a discussion](https://github.com/koehlma/momba/discussions/new?category=show-and-tell) or dropping us a message. π
## β¨ 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](http://www.modestchecker.net/) and [Storm](https://www.stormchecker.org/)
- **an [OpenAI Gym](https://gym.openai.com) compatible interface** for training agents on formal models
- pythonic and **statically typed** APIs to tinker with formal models
- hassle-free out-of-the-box support for **Windows, Linux, and MacOS**
## π Getting Started
Momba is available from the [Python Package Index](https://pypi.org/):
```sh
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](https://koehlma.github.io/momba/examples) or read the [user guide](https://koehlma.github.io/momba/guide) to learn more.
If you aim at a fully reproducible modeling environment, we recommend using [Pipenv](https://pypi.org/project/pipenv/) or [Poetry](https://python-poetry.org/) for dependency management.
We also provide a [GitHub Template](https://github.com/koehlma/momba-pipenv-template) for Pipenv.
## π Contributing
We welcome all kinds of contributions!
For minor changes and bug fixes feel free to simply open a pull request. For major changes impacting the overall design of Momba, please first [start a discussion](https://github.com/koehlma/momba/discussions/new?category=ideas) outlining your idea.
To get you started, we provide a [development container for VS Code](https://code.visualstudio.com/docs/remote/containers) containing everything you need for development. The easiest way to get up and running is by clicking on the following badge:
[](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/koehlma/momba.git)
Opening the link in VS Code will clone this repository into its own Docker volume and then start the provided development container inside VS Code so you are ready to start coding.
## βοΈ Licensing
Momba is licensed under either [MIT](https://github.com/koehlma/momba/blob/main/LICENSE-MIT) or [Apache 2.0](https://github.com/koehlma/momba/blob/main/LICENSE-APACHE) at your opinion.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project by you, as defined in the Apache 2.0 license, shall be dual licensed as above, without any additional terms or conditions.
## π¦ Rust Crates
The exploration engine of Momba is written in [Rust](https://rust-lang.org) levering [PyO3](https://pyo3.rs/) for Python bindings.
In case you are a Rust developer you might find some of the crates in [engine/crates](engine/crates) useful.
In particular, the crate [momba-explore](https://crates.io/crates/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`](https://crates.io/crates/momba-sidekick) directly exposes some of this functionality.
## π Acknowledgements
This project is partially supported by the German Research Foundation (DFG) under grant No. 389792660, as part of [TRR 248](https://perspicuous-computing.science).
Thanks to Sarah Sterz for the awesome Momba logo.
%package -n python3-momba
Summary: A Python library for quantitative models.
Provides: python-momba
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-momba
_Momba_ is a Python framework for dealing with quantitative models centered around the [JANI-model](http://www.jani-spec.org/) 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.
For academic publications, please cite Momba as follows:
Maximilian A. KΓΆhl, Michaela Klauck, and Holger Hermanns: _Momba: JANI Meets Python_. In: J. F. Groote and K. G. Larsen (eds.) 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021. DOI: https://doi.org/10.1007/978-3-030-72013-1_23.
In case you made anything with Momba or plan to do so, we would highly appreciate if you let us know about your exciting project by [opening a discussion](https://github.com/koehlma/momba/discussions/new?category=show-and-tell) or dropping us a message. π
## β¨ 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](http://www.modestchecker.net/) and [Storm](https://www.stormchecker.org/)
- **an [OpenAI Gym](https://gym.openai.com) compatible interface** for training agents on formal models
- pythonic and **statically typed** APIs to tinker with formal models
- hassle-free out-of-the-box support for **Windows, Linux, and MacOS**
## π Getting Started
Momba is available from the [Python Package Index](https://pypi.org/):
```sh
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](https://koehlma.github.io/momba/examples) or read the [user guide](https://koehlma.github.io/momba/guide) to learn more.
If you aim at a fully reproducible modeling environment, we recommend using [Pipenv](https://pypi.org/project/pipenv/) or [Poetry](https://python-poetry.org/) for dependency management.
We also provide a [GitHub Template](https://github.com/koehlma/momba-pipenv-template) for Pipenv.
## π Contributing
We welcome all kinds of contributions!
For minor changes and bug fixes feel free to simply open a pull request. For major changes impacting the overall design of Momba, please first [start a discussion](https://github.com/koehlma/momba/discussions/new?category=ideas) outlining your idea.
To get you started, we provide a [development container for VS Code](https://code.visualstudio.com/docs/remote/containers) containing everything you need for development. The easiest way to get up and running is by clicking on the following badge:
[](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/koehlma/momba.git)
Opening the link in VS Code will clone this repository into its own Docker volume and then start the provided development container inside VS Code so you are ready to start coding.
## βοΈ Licensing
Momba is licensed under either [MIT](https://github.com/koehlma/momba/blob/main/LICENSE-MIT) or [Apache 2.0](https://github.com/koehlma/momba/blob/main/LICENSE-APACHE) at your opinion.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project by you, as defined in the Apache 2.0 license, shall be dual licensed as above, without any additional terms or conditions.
## π¦ Rust Crates
The exploration engine of Momba is written in [Rust](https://rust-lang.org) levering [PyO3](https://pyo3.rs/) for Python bindings.
In case you are a Rust developer you might find some of the crates in [engine/crates](engine/crates) useful.
In particular, the crate [momba-explore](https://crates.io/crates/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`](https://crates.io/crates/momba-sidekick) directly exposes some of this functionality.
## π Acknowledgements
This project is partially supported by the German Research Foundation (DFG) under grant No. 389792660, as part of [TRR 248](https://perspicuous-computing.science).
Thanks to Sarah Sterz for the awesome Momba logo.
%package help
Summary: Development documents and examples for momba
Provides: python3-momba-doc
%description help
_Momba_ is a Python framework for dealing with quantitative models centered around the [JANI-model](http://www.jani-spec.org/) 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.
For academic publications, please cite Momba as follows:
Maximilian A. KΓΆhl, Michaela Klauck, and Holger Hermanns: _Momba: JANI Meets Python_. In: J. F. Groote and K. G. Larsen (eds.) 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021. DOI: https://doi.org/10.1007/978-3-030-72013-1_23.
In case you made anything with Momba or plan to do so, we would highly appreciate if you let us know about your exciting project by [opening a discussion](https://github.com/koehlma/momba/discussions/new?category=show-and-tell) or dropping us a message. π
## β¨ 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](http://www.modestchecker.net/) and [Storm](https://www.stormchecker.org/)
- **an [OpenAI Gym](https://gym.openai.com) compatible interface** for training agents on formal models
- pythonic and **statically typed** APIs to tinker with formal models
- hassle-free out-of-the-box support for **Windows, Linux, and MacOS**
## π Getting Started
Momba is available from the [Python Package Index](https://pypi.org/):
```sh
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](https://koehlma.github.io/momba/examples) or read the [user guide](https://koehlma.github.io/momba/guide) to learn more.
If you aim at a fully reproducible modeling environment, we recommend using [Pipenv](https://pypi.org/project/pipenv/) or [Poetry](https://python-poetry.org/) for dependency management.
We also provide a [GitHub Template](https://github.com/koehlma/momba-pipenv-template) for Pipenv.
## π Contributing
We welcome all kinds of contributions!
For minor changes and bug fixes feel free to simply open a pull request. For major changes impacting the overall design of Momba, please first [start a discussion](https://github.com/koehlma/momba/discussions/new?category=ideas) outlining your idea.
To get you started, we provide a [development container for VS Code](https://code.visualstudio.com/docs/remote/containers) containing everything you need for development. The easiest way to get up and running is by clicking on the following badge:
[](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/koehlma/momba.git)
Opening the link in VS Code will clone this repository into its own Docker volume and then start the provided development container inside VS Code so you are ready to start coding.
## βοΈ Licensing
Momba is licensed under either [MIT](https://github.com/koehlma/momba/blob/main/LICENSE-MIT) or [Apache 2.0](https://github.com/koehlma/momba/blob/main/LICENSE-APACHE) at your opinion.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project by you, as defined in the Apache 2.0 license, shall be dual licensed as above, without any additional terms or conditions.
## π¦ Rust Crates
The exploration engine of Momba is written in [Rust](https://rust-lang.org) levering [PyO3](https://pyo3.rs/) for Python bindings.
In case you are a Rust developer you might find some of the crates in [engine/crates](engine/crates) useful.
In particular, the crate [momba-explore](https://crates.io/crates/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`](https://crates.io/crates/momba-sidekick) directly exposes some of this functionality.
## π Acknowledgements
This project is partially supported by the German Research Foundation (DFG) under grant No. 389792660, as part of [TRR 248](https://perspicuous-computing.science).
Thanks to Sarah Sterz for the awesome Momba logo.
%prep
%autosetup -n momba-0.6.7
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-momba -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon May 15 2023 Python_Bot - 0.6.7-1
- Package Spec generated