Python based 'Easy Representation of Knowledge' (pyERK)
Project description
Overview: pyerk
Pyerk is the python implementation of the emergent representation of knowledge framework.
- Designed to formally represent knowledge (including meta levels)
- Implementation-status: "early alpha"
- Inspired by OWL, but much more expressive
- ... at the cost of guarantied computability
- Inspired by Wikidata, but much simpler
- Inspired by SUO-KIF, but with less brackets
- Represented directly in python: → imperative instaead of declarative knowledge representation
Pyerk originated and is currently (2022) mainly developed with focus on representing knowledge from the domain of control theory as part of the Automatic Control Knowledge Repository (ACKREP). However, in principle, it aims to be applicable wo a wide range of domains.
Assumed Directory Structure
<erk-root>/
├── pyerk/ ← repo with the code of the core package
│ ├── .git/
│ ├── README.md ← the currently displayed file (README.md)
│ ├── setup.py ← deployment script
│ ├── src/pyerk/auxiliary.py ← module containing function get_erk_root_dir()
│ └── ...
│
├── django-erk-gui/ ← repo with the code for the django gui (project and! app)
│ │ (this package is optional)
│ ├── .git/
│ ├── manage.py
│ └── ...
│
├── erk-data/ ← directory that contains erk-knowledge packages (for actual usage)
│ ├── ocse/ ← a knowledge package (ontology of control systems engineering)
│ │ ├── .git/
│ │ ├── README.md
│ │ ├── ocse.py ← a knowledge module
│ │ │ (this one is currently used for unit testing)
│ │ └── ...
│ ├── xyz123/ ← another knowledge package
│ │ └── ...
│ └── ...
├── erk-data-for-unittests/ ← directory that contains erk-knowledge packages
│ └── ... (unittest version, probably older and different from
│ production data.)
└──...
Documentation
Rudimentary documentation is available at https://pyerk-core.readthedocs.io (generated from the /docs
directory). To get an overview of the most importent features you might also want to have a look at the source code, especially at the files builtin_entities.py and the test_core.py.
Coding style
We use black -l 120 ./
to ensure coding style consistency.
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