molgenis-py-bbmri-eric 1.18.1

MOLGENIS Python tooling for BBMRI-ERIC

molgenis-py-bbmri-eric

MOLGENIS Python tooling for BBMRI-ERIC.

Description

This library contains tools for the MOLGENIS BBMRI-ERIC Directory that help with staging and publishing the data of the national nodes. Staging is the process of copying data from a national node's external server (for example BBMRI-NL) to the staging area on the ERIC directory. Not all national nodes have external servers; these do not need to be staged. Publishing is the process of copying and combining the data from the staging areas to the public combined tables of the directory.

Usage

These tools can be used as a library in a script. Start by installing the library with pip install molgenis-py-bbmri-eric.

For an example of how to use this library to stage and publish nodes, see example.py.

If you just want to retrieve the data of a node for another purpose, you can use the EricSession and ExternalServerSession directly:

from molgenis.bbmri_eric.bbmri_client import EricSession, ExternalServerSession
from molgenis.bbmri_eric.model import NodeData

# Get the staging and published data of NL from the directory
session = EricSession(url="<DIRECTORY_URL")
nl = session.get_external_node("NL")
nl_staging_data: NodeData = session.get_staging_node_data(nl)
nl_published_data: NodeData = session.get_published_node_data(nl)

# Get the data from the external server of NL
external_session = ExternalServerSession(nl)
nl_external_data: NodeData = external_session.get_node_data()

# Now you can use the NodeData objects as you wish
for person in nl_external_data.persons.rows:
    print(person)

For developers

This project uses pre-commit and pipenv for the development workflow.

Install pre-commit and pipenv if you haven't already:

pip install pre-commit
pip install pipenv

Install the git commit hooks:

pre-commit install

Create an environment and install the package including all (dev) dependencies:

pipenv install --dev

Enter the environment:

pipenv shell

Build and run the tests:

tox

Note

This project has been set up using PyScaffold 4.0.2. For details and usage information on PyScaffold see https://pyscaffold.org/.