Metadata-Version: 2.1
Name: kgsteward
Version: 1.0.22
Summary: Knwowledge Graph Steward - Command line tool to help manage RDF store
Author-email: Marco Pagni <marco.pagni@sib.swiss>
Project-URL: Homepage, https://github.com/sib-swiss/kgsteward
Project-URL: Bug Tracker, https://github.com/sib-swiss/kgsteward/issues
Project-URL: Documentation, https://github.com/sib-swiss/kgsteward
Project-URL: Source, https://github.com/sib-swiss/kgsteward
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: dumper
Requires-Dist: requests
Requires-Dist: pathlib
Requires-Dist: PyYAML
Requires-Dist: termcolor
Requires-Dist: pydantic>=2.0.0
Requires-Dist: pydantic-yaml

# kgsteward - Knowledge Graph Steward

A command line tool to help manage RDF store (GraphDB). Written in python.

## Installation

The code only depends on very standard Python packages.
Its installation should be straightforward.
The easiest option is to install `kgsteward` with `pip3`:

```shell
pip3 install git+https://github.com/sib-swiss/kgsteward

# To update your installation to a newer version.
pip3 install --upgrade git+https://github.com/sib-swiss/kgsteward
```

Alternatively, you can also clone/download the content of this repo to your
local machine, and then run kgsteward using the script `./kgsteward`.

**Important:** if the above installation fails or does not build properly
(e.g. the package name is set to `UNKNOWN`), make sure that your versions of
`pip` and `setuptools` are up-to-date:

```shell
pip install --upgrade pip
pip install --upgrade setuptools
```

## Running kgsteward

```shell
kgsteward -h
```

## Documentation

The syntax of the YAML configuration file is given [here](doc/yamldoc.md)

## References

__`kgsteward`__ was developped to manage experimental chemical data (LC-MS2) and experimental biological data (bio-activity) data together with reference chemical structures derived from public database (LOTUS, wikidata) as reported in [A Sample-Centric and Knowledge-Driven Computational Framework for Natural Products Drug Discovery](https://doi.org/10.1021/acscentsci.3c00800).


