An object mapper for the neo4j graph database.
Project description
An Object Graph Mapper (OGM) for the neo4j graph database, built on the awesome neo4j_driver
If you need assistance with neomodel, please create an issue on the GitHub repo found at https://github.com/neo4j-contrib/neomodel/.
- Familiar class based model definitions with proper inheritance.
- Powerful query API.
- Schema enforcement through cardinality restrictions.
- Full transaction support.
- Thread safe.
- Pre/post save/delete hooks.
- Django integration via django_neomodel
Requirements
For neomodel releases 5.x :
- Python 3.7+
- Neo4j 5.x, 4.4 (LTS)
For neomodel releases 4.x :
- Python 3.7 -> 3.10
- Neo4j 4.x (including 4.4 LTS for neomodel version 4.0.10)
Documentation
(Needs an update, but) Available on readthedocs.
Upcoming breaking changes notice - >=5.3
Based on Python version status, neomodel will be dropping support for Python 3.7 in the next release (5.3). This does not mean neomodel will stop working on Python 3.7, but it will no longer be tested against it. Instead, we will try to add support for Python 3.12.
Another potential breaking change coming up is adding async support to neomodel. But we do not know when this will happen yet, or if it will actually be a breaking change. We will definitely push this in a major release though. More to come on that later.
Finally, we are looking at refactoring some standalone methods into the Database() class. More to come on that later.
Installation
Install from pypi (recommended):
$ pip install neomodel ($ source dev # To install all things needed in a Python3 venv)
# Neomodel has some optional dependencies (including Shapely), to install these use:
$ pip install neomodel['extras']
To install from github:
$ pip install git+git://github.com/neo4j-contrib/neomodel.git@HEAD#egg=neomodel-dev
Contributing
Ideas, bugs, tests and pull requests always welcome. Please use GitHub's Issues page to track these.
If you are interested in developing neomodel further, pick a subject
from the Issues page and open a Pull Request (PR) for it. If you are
adding a feature that is not captured in that list yet, consider if the
work for it could also contribute towards delivering any of the existing
issues too.
Running the test suite
Make sure you have a Neo4j database version 4 or higher to run the tests on.:
$ export NEO4J_BOLT_URL=bolt://<username>:<password>@localhost:7687 # check your username and password
Ensure dbms.security.auth_enabled=true in your database configuration
file. Setup a virtual environment, install neomodel for development and
run the test suite: :
$ pip install -e '.[dev,pandas,numpy]'
$ pytest
The tests in "test_connection.py" will fail locally if you don't specify the following environment variables:
$ export AURA_TEST_DB_USER=username
$ export AURA_TEST_DB_PASSWORD=password
$ export AURA_TEST_DB_HOSTNAME=url
If you are running a neo4j database for the first time the test suite
will set the password to 'test'. If the database is already populated,
the test suite will abort with an error message and ask you to re-run it
with the --resetdb switch. This is a safeguard to ensure that the test
suite does not accidentally wipe out a database if you happen to not
have restarted your Neo4j server to point to a (usually named)
debug.db database.
If you have docker-compose installed, you can run the test suite
against all supported Python interpreters and neo4j versions: :
# in the project's root folder:
$ sh ./tests-with-docker-compose.sh
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