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Library to load data sets to Neo4j.

Project description


Build Status PyPI License Neo4j

A Python library to quickly build data sets and load them to Neo4j. Built by Kaiser & Preusse.


Documentation Status

Docs available at:

Tutorial with real data:


Install graphio from PyPI:

pip install graphio

Install the latest build version from github:

pip install 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/ 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, 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 local in the graphio source directory
  • run the script, the script will start two Docker containers with Neo4j and run tox with the --recreate flag.


Please provide feedback, ideas and bug reports through github issues.

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