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 thememgraph/memgraphDocker image.docker_image_tag="latest": We use thelatesttag 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.
