When developing graph-based applications, it can become hard to manage different database server instances. Using the new instance_runner module, you will learn how to start, stop, connect to and monitor Memgraph instances with GQLAlchemy directly from your Python scripts.

First, perform all the necessary imports:

from gqlalchemy.instance_runner import (
    DockerImage,
    MemgraphInstanceDocker
)

Start the Memgraph instance

The following code will create a Memgraph instance, start it and return a connection object:

memgraph_instance = MemgraphInstanceDocker(
    docker_image=DockerImage.MEMGRAPH, docker_image_tag="latest", host="0.0.0.0", port=7687
)
memgraph = memgraph_instance.start_and_connect(restart=False)

We used the default values for the arguments:

• docker_image=DockerImage.MEMGRAPH: This will start the memgraph/memgraph Docker image.
• docker_image_tag="latest": We use the latest tag to start the most recent version of Memgraph.
• host="0.0.0.0": This is the wildcard address which indicates that the instance should accept connections from all interfaces.
• port=7687: This is the default port Memgraph listens to.
• restart=False: If the instance is already running, it won’t be stopped and started again.

After we have created the connection, we can start querying the database:

memgraph.execute_and_fetch("RETURN 'Memgraph is running' AS result"))[0]["result"]

Pass configuration flags

You can pass configuration flags using a dictionary:

config={"--log-level": "TRACE"}
memgraph_instance = MemgraphInstanceDocker(config=config)

Stop the Memgraph instance

To stop a Memgraph instance, call the stop() method:

memgraph_instance.stop()

Check if a Memgraph instance is running

To check if a Memgraph instance is running, call the is_running() method:

memgraph_instance.is_running()

Where to next?

Hopefully, this guide has taught you how to manage Memgraph Docker instances. If you have any more questions, join our community and ping us on Discord.