Famapy
FaMaPy is a Python-based AAFM framework that takes into consideration previous AAFM tool designs and enables multi-solver and multi-metamodel support for the integration of AAFM tooling on the Python ecosystem.
The main features of the framework are:
- Easy to extend by enabling the creation of new plugins following a semi-automatic generator approach.
- Support multiple variability models. Currently, it provides support for cardinality-based feature models. However, it is easy to integrate others such as attributed feature models
- Support multiple solvers. Currently, it provides support for the PySAT metasolver, which enables more than ten different solvers.
- Support multiple operations. It is developed, having in mind multi-model operations such as those depicted by Familiar and single-model operations.
Available plugins
Documentation
All the proyect related documentation can be found in wiki format at wiki
Changelog
Detailed changes for each release are documented in the release notes
Contributing
See CONTRIBUTING.md
2 maintainers
Release files for famapy 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| famapy-1.0.0.tar.gz | 14.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| famapy-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 38.1 kB
Release files / famapy-1.0.0.tar.gz
| Download URL | famapy-1.0.0.tar.gz |
|---|---|
| Size | 14.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.13
|
Release files / famapy-1.0.0-py3-none-any.whl
| Download URL | famapy-1.0.0-py3-none-any.whl |
|---|---|
| Size | 23.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.13
|
