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How to install GQLAlchemy

There are two main ways of installing GQLAlchemy: with package managers such as pip and Poetry, and by building it from source.


To install GQLAlchemy, you will need the following:


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.

Install with pip

After you’ve installed the prerequisites, run the following command to install GQLAlchemy:

pip install gqlalchemy

With 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 above

If 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"


If you are using the zsh terminal, surround gqlalchemy[$extras] with quotes:

pip install 'gqlalchemy[arrow]'

Build from source

Clone or download the GQLAlchemy source code locally and run the following command to build it from source with Poetry:

poetry install --all-extras

The 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 support

To 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" # Otherwise

If 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"