Library to load data sets to Neo4j.
A Python library to quickly build data sets and load them to Neo4j. Built by Kaiser & Preusse.
Docs available at: https://graphio.readthedocs.io/
Tutorial with real data: https://graphdb-bio.com/graphio-tutorial-idmapping
Install graphio from PyPI:
pip install graphio
Install the latest build version from github:
pip install git+https://github.com/kaiserpreusse/graphio.git
This is an early release with a focus on data loading.
You need Docker to run the test suite. Two Neo4j Docker containers will be started before running the tests, one for version 3.5 and another for version 4.
All tests that use the
graph fixture found in
tests/conftest.py will run against both databases.
Run test suite with local environment
- create a new Python environment
- install package dependencies with
pip install -r requirements.txt
- install test dependencies with
pip install -r test_requirements.txt
- run the script
run_test_local_env.sh, the script will start two Docker containers with Neo4j and run pytest against the source files
Run test suite with tox
tox is a test automation tool that automatically creates new virtual environments, installs dependencies and runs the tests. It can run the tests against multiple Python versions. You have to install all Python versions that are tested and they have to be discoverable by tox. The suggested way to install multiple Python versions is pyenv.
- install Python 3.5, 3.6, 3.7, 3.8 with pyenv
- allow tox to discover the Python executables by using
pyenv localin the graphio source directory
- run the script
run_test_tox.sh, the script will start two Docker containers with Neo4j and run
Please provide feedback, ideas and bug reports through github issues.
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