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jupyter-memgraph-tutorials
Learn to use Memgraph and GQLAlchemy quickly with the help of Jupyter Notebooks
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GQLAlchemy is a library developed with the purpose of assisting in writing and running queries on Memgraph. GQLAlchemy supports high-level connection to Memgraph as well as modular query builder.
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Are you considering moving from table data to a graph database, but it seems like a complicated migration? With this short tutorial, we are going to show you how to do just that using GQLAlchemy. You will learn how to import table data from files stored in local or online storage to a Memgraph graph database. You can find the original Jupyter Notebook in our open-source GitHub repository.
For any other service provider, it is possible to implement your custom importer class, here's how. Don't forget that GQLAlchemy is an open source project, so you can submit your extended functionality on our GitHub repository.
If you want to do more with your graph data, visit the Memgraph MAGE graph library (and throw us a star ⭐) and take a look at all of the graph algorithms that have been implemented. You can also implement and submit your own algorithms and utility procedures.
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