> ## Documentation Index
> Fetch the complete documentation index at: https://docs.turingdb.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Use TuringDB Community
> Start using TuringDB Community Version with the TuringDB python SDK.
[Checkout the Github of the TuringDB Community Version](https://github.com/turing-db/turingdb) If you want to support TuringDB leave us a star on Github !
**Quick install.** The fastest way to install TuringDB in your home directory.
```bash theme={null}
curl https://install.turingdb.ai | bash
```
**Using Claude Code?** Install the TuringDB skill once and let Claude handle the rest of this quickstart for you:
```bash theme={null}
npx skills add https://github.com/turing-db/turingdb-skills
```
Then in Claude Code run `/turingdb install turingdb and create a first graph`. See the [Claude Code Skill](/claude-skill) page for more.
## Create a Python project with TuringDB
The steps below walk you through setting up a Python project, installing the TuringDB SDK, and running your first graph.
Create a new directory for your project and initialize it with `uv`:
```bash theme={null}
mkdir my_app
cd my_app
uv init
```
Using `uv` package manager:
```bash theme={null}
uv add turingdb
```
or using the `pip` :
```bash theme={null}
pip install turingdb
```
You can also install TuringDB using cmake: instructions on Github ([link](https://github.com/turing-db/turingdb/blob/main/README.md#how-to-build))
If you want to launch TuringDB instantly in the CLI
```bash theme={null}
turingdb
```
If you want to launch TuringDB in the background as a daemon
```bash theme={null}
turingdb -demon
```
To stop TuringDB running in the background:
```bash theme={null}
turingdb stop
```
Create graph → list graph → create node & create edge → commit → list graphs → match query
### Python SDK
```python theme={null}
from turingdb import TuringDB
# Create TuringDB client
# set host parameter to the URL (as string) on which TuringDB is running,
# default "http://localhost:6666"
client = TuringDB(host="http://localhost:6666")
# Create a new graph called my_graph
client.create_graph("mygraph")
# Set working graph
client.set_graph("mygraph")
# Create a new change on the graph
change = client.new_change()
# 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")
# Checkout back to main
client.checkout()
# Query graph
client.query("MATCH (n) RETURN n")
```
TuringDB has a built-in visualiser to explore your graphs in the browser. Launch it with the `-ui` flag:
```bash theme={null}
turingdb -ui
```
Then open [http://localhost:8080](http://localhost:8080) in your browser.
### Exploring your graph:
1. Launch the UI with `turingdb -ui`
2. Choose on the top right the graph you want to explore
3. Search a node of interest using the search tool or type a CYPHER query
4. Click on nodes to inspect nodes, double click to expand neighbors..etc.
You are done!