GQLAlchemy is a fully open-source Python library and Object Graph Mapper (OGM) - a link between graph database objects and Python objects.
An Object Graph Mapper or OGM provides a developer-friendly workflow that allows for writing object-oriented notation to communicate with graph databases. Instead of writing Cypher queries, you will be able to write object-oriented code, which the OGM will automatically translate into Cypher queries.
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Python 3.8 - 3.11
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- Install
pymgclientbuild prerequisites - Install
pymgclientvia pip:
pip install --user pymgclient
- Install
Warning
Python 3.11 users: On Windows, GQLAlchemy is not yet compatible with this Python version. Linux users can install GQLAlchemy without the DGL extra (due to its dependencies not supporting Python 3.11 yet). If this is currently a blocker for you, please let us know by opening an issue.
After you’ve installed the prerequisites, run the following command to install GQLAlchemy:
pip install gqlalchemyWith the above command, you get the default GQLAlchemy installation which doesn’t include import/export support for certain formats (see below). To get additional import/export capabilities, use one of the following install options:
pip install gqlalchemy[arrow] # Support for the CSV, Parquet, ORC and IPC/Feather/Arrow formats
pip install gqlalchemy[dgl] # DGL support (also includes torch)
pip install gqlalchemy[docker] # Docker support
pip install gqlalchemy[all] # All of the aboveIf you intend to use GQLAlchemy with PyTorch Geometric support, that library must be installed manually:
pip install gqlalchemy[torch_pyg] # prerequisite
pip install torch-scatter torch-sparse torch-cluster torch-spline-conv torch-geometric -f https://data.pyg.org/whl/torch-1.13.0+cpu.html"If you are using the zsh terminal, surround gqlalchemy[$extras] with quotes:
pip install 'gqlalchemy[arrow]'If you are using Conda for Python environment management, you can install GQLAlchemy through pip.
The project uses Poetry to build the library. Clone or download the GQLAlchemy source code locally and run the following command to build it from source with Poetry:
poetry install --all-extrasThe poetry install --all-extras command installs GQLAlchemy with all extras
(optional dependencies). Alternatively, you can use the -E option to define
what extras to install:
poetry install # No extras
poetry install -E arrow # Support for the CSV, Parquet, ORC and IPC/Feather/Arrow formats
poetry install -E dgl # DGL support (also includes torch)
poetry install -E docker # Docker supportTo run the tests, make sure you have an active Memgraph instance, and execute one of the following commands:
poetry run pytest . -k "not slow" # If all extras installed
poetry run pytest . -k "not slow and not extras" # OtherwiseIf you’ve installed only certain extras, it’s also possible to run their associated tests:
poetry run pytest . -k "arrow"
poetry run pytest . -k "dgl"
poetry run pytest . -k "docker"poetry run flake8 .
poetry run black .
poetry run pytest . -k "not slow and not extras"The GQLAlchemy documentation is available on GitHub.
The reference guide can be generated from the code by executing:
pip3 install pydoc-markdown
pydoc-markdown
Other parts of the documentation are written and located at docs directory. To test the documentation locally execute:
pip3 install mkdocs
pip3 install mkdocs-material
pip3 install pymdown-extensions
mkdocs serve
Copyright (c) 2016-2023 Memgraph Ltd.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.