Morph-KGC is an engine that constructs RDF knowledge graphs from heterogeneous data sources with the R2RML and RML mapping languages. Morph-KGC is built on top of pandas and it leverages mapping partitions to significantly reduce execution times and memory consumption for large data sources.
Features :sparkles:
- User-friendly mappings with YARRRML.
- Transformation functions with RML-FNML, including Python UDFs.
- RDF-star generation with RML-star.
- RML views over tabular data sources and JSON files.
- Integration with RDFLib, Oxigraph and Kafka.
- Optimized to materialize large knowledge graphs.
- Remote data and mapping files.
- Input data formats:
- Relational databases: MySQL, PostgreSQL, Oracle, Microsoft SQL Server, MariaDB, SQLite.
- Tabular files: CSV, TSV, Excel, Parquet, Feather, ORC, Stata, SAS, SPSS, ODS.
- Hierarchical files: JSON, XML.
- In-memory data structures: Python Dictionaries, DataFrames.
- Cloud data lake solutions: Databricks, Snowflake.
- Property graph databases: Neo4j, Kùzu.
Documentation :bookmark_tabs:
Tutorial :woman_teacher:
Learn quickly with the tutorial in Google Colaboratory!
Getting Started :rocket:
PyPI is the fastest way to install Morph-KGC:
pip install morph-kgc
We recommend to use virtual environments to install Morph-KGC.
To run the engine via command line you just need to execute the following:
python3 -m morph_kgc config.ini
Check the documentation to see how to generate the configuration INI file. Here you can also see an example INI file.
It is also possible to run Morph-KGC as a library with RDFLib and Oxigraph:
import morph_kgc
# generate the triples and load them to an RDFLib graph
g_rdflib = morph_kgc.materialize('/path/to/config.ini')
# work with the RDFLib graph
q_res = g_rdflib.query('SELECT DISTINCT ?classes WHERE { ?s a ?classes }')
# generate the triples and load them to Oxigraph
g_oxigraph = morph_kgc.materialize_oxigraph('/path/to/config.ini')
# work with Oxigraph
q_res = g_oxigraph.query('SELECT DISTINCT ?classes WHERE { ?s a ?classes }')
# the methods above also accept the config as a string
config = """
[DataSource1]
mappings: /path/to/mapping/mapping_file.rml.ttl
db_url: mysql+pymysql://user:password@localhost:3306/db_name
"""
g_rdflib = morph_kgc.materialize(config)
License :unlock:
Morph-KGC is available under the Apache License 2.0.
Author & Contact :mailbox_with_mail:
Ontology Engineering Group, Universidad Politécnica de Madrid.
Citing :speech_balloon:
If you used Morph-KGC in your work, please cite the SWJ paper:
@article{arenas2024morph,
title = {{Morph-KGC: Scalable knowledge graph materialization with mapping partitions}},
author = {Arenas-Guerrero, Julián and Chaves-Fraga, David and Toledo, Jhon and Pérez, María S. and Corcho, Oscar},
journal = {Semantic Web},
year = {2024},
volume = {15},
number = {1},
pages = {1-20},
issn = {2210-4968},
publisher = {IOS Press},
doi = {10.3233/SW-223135}
}
Sponsor :shield:
1 maintainer
Metadata
1 maintainer
Release files for morph-kgc 2.10.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| morph_kgc-2.10.0.tar.gz | 257.6 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| morph_kgc-2.10.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 329.8 kB
Release files / morph_kgc-2.10.0.tar.gz
| Download URL | morph_kgc-2.10.0.tar.gz |
|---|---|
| Size | 257.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
a8d01d4c2118821ed46490bc6445d0d06f0f5dd23e29eeeee1da64ea99e1a124
|
|
BLAKE2b-256 checksum How to use checksums |
09b12306c3bf858186c1cb1b872fbae45ad5b820a2af7d5755766b9ad91b087a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.2
|
Release files / morph_kgc-2.10.0-py3-none-any.whl
| Download URL | morph_kgc-2.10.0-py3-none-any.whl |
|---|---|
| Size | 72.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8ce01d8db014a3cbe9d2e77f61c543ea8d19a7f9ec7cd6ad4abf203bd9ce9ba7
|
|
BLAKE2b-256 checksum How to use checksums |
c9c48edb7ec3b0602ffcfad2670cfb5eb2af2c40196695b440b636fc5a50b311
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.2
|
Security for morph-kgc 2.10.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
