Use TuringDB Community

Start using TuringDB Community Version with the TuringDB python SDK.

Checkout the Github of the TuringDB Community Version If you want to support TuringDB leave us a star on Github !

1. Install TuringDB

   Using pip:

   pip install turingdb
   

   or using the uv package manager (you will need to create a project first):

   uv add turingdb
   

   You can also install TuringDB using cmake: [instructions on Github](https://github.com/turing-db/turingdb/blob/main/README.md

2. Running TuringDB

   If you want to launch TuringDB instantly in the CLI

   turingdb
   

   If you want to launch TuringDB in the background as a daemon

   turingdb -demon
   
3. Example to create and query a graph

   Create graph → list graph → create node & create edge → commit → list graphs → match query

   Python SDK

   from turingdb import TuringDB
   
   client = TuringDB(http://localhost)
   
   # Create a new graph
   client.query('CREATE GRAPH mygraph')
   client.set_graph('mygraph')
   
   # Create a new change on the graph
   change = client.query("CHANGE NEW")["Change ID"][0]
   
   # Checkout into the change
   client.checkout(change=change)
   
   # Create a node Person (Jane) - Edge (knows) - node (John)
   client.query('CREATE (n:Person {Name:"Jane"})-[e:knows]-(m:Person {Name:"John"})')
   
   # Commit the change
   client.query("COMMIT")
   client.query("CHANGE SUBMIT")
   
4. Visualise the graph you have created in TuringDB

   TuringDB has a high performance visualiser that you can download here:

   TuringDB Visualiser

   Exemple of a biological interaction graph built in TuringDB:

   1. Choose on the top right the graph

   2. Search & select a node(s) of interest (magnifying glass button on the left)

   3. Then go to visualiser (network logo) and you can start exploring paths, expanding neighbours, inspect nodes (parameters, hyperlinks, and texts stored on the nodes)

      

You are done!