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https://github.com/SDM-TIB/Dragoman
An Optimized Interpreter for RML Functional Mappings!
https://github.com/SDM-TIB/Dragoman
Last synced: about 1 month ago
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An Optimized Interpreter for RML Functional Mappings!
- Host: GitHub
- URL: https://github.com/SDM-TIB/Dragoman
- Owner: SDM-TIB
- License: apache-2.0
- Created: 2019-11-19T16:18:00.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2023-05-10T10:12:51.000Z (over 1 year ago)
- Last Synced: 2024-11-06T02:52:38.284Z (about 2 months ago)
- Language: Python
- Homepage:
- Size: 19.2 MB
- Stars: 6
- Watchers: 5
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-kgc-tools - Dragoman - An efficient RML+FnO-compliant engine for translating and executing complex functions in RML mapping rules and transfer the data integration system into a function-free one. (KGC Pre-processors)
README
# 
An Optimized, RML-engine-agnostic Interpreter for Functional Mappings. It planns the optimized execution of FnO functions integrated in RML mapping rules, interprets and transforms the rules into function-free ones efficiently. Since Dragoman is engine-agnostic it can be adopted by any RML-compliant Knowledge Graph creation framework. Read more about [Dragoman](https://doi.org/10.15488/13537)
## You can use Dragoman with your own library of functions! Here is [how](https://tib.eu/cloud/s/ikjiHyf8RNrEHSY):
1. Make a copy of functions.py that is located in ./Interpreter/ and rename it (we consider it as new_function_script.py)
2. Edit new_function_script.py by adding your functions definitions following the sctructure provided in the script and save the chnages
3. Go to the connection.py and replace ".functions" with ".new_function_script" at line 6 and save the changes
That's it! You are ready to go :)
# Installing and Running the Dragoman
## Installing Requirements
```
pip install -r requirements.txt
```
## Executing Dragoman
```
python run_translator.py /path/to/config
```
## Version
```
1.0
```
## License
This work is licensed under Apache 2.0
# Authors
- Samaneh Jozashoori ([email protected])
- Enrique Iglesias ([email protected])
- Maria-Esther Vidal ([email protected])