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---
title: Connect Streamlit to TigerGraph
slug: /develop/tutorials/databases/tigergraph
---
# Connect Streamlit to TigerGraph
## Introduction
This guide explains how to securely access a TigerGraph database from Streamlit Community Cloud. It uses the [pyTigerGraph](https://pytigergraph.github.io/pyTigerGraph/GettingStarted/) library and Streamlit's [Secrets management](/deploy/streamlit-community-cloud/deploy-your-app/secrets-management).
## Create a TigerGraph Cloud Database
First, follow the official tutorials to create a TigerGraph instance in TigerGraph Cloud, either as a [blog](https://www.tigergraph.com/blog/getting-started-with-tigergraph-3-0/) or a [video](https://www.youtube.com/watch?v=NtNW2e8MfCQ). Note your username, password, and subdomain.
For this tutorial, we will be using the COVID-19 starter kit. When setting up your solution, select the “COVID-19 Analysis" option.
Once it is started, ensure your data is downloaded and queries are installed.
## Add username and password to your local app secrets
Your local Streamlit app will read secrets from a file `.streamlit/secrets.toml` in your app’s root directory. Create this file if it doesn’t exist yet and add your TigerGraph Cloud instance username, password, graph name, and subdomain as shown below:
```toml
# .streamlit/secrets.toml
[tigergraph]
host = "https://xxx.i.tgcloud.io/"
username = "xxx"
password = "xxx"
graphname = "xxx"
```
<Important>
Add this file to `.gitignore` and don't commit it to your GitHub repo!
</Important>
## Copy your app secrets to the cloud
As the `secrets.toml` file above is not committed to GitHub, you need to pass its content to your deployed app (on Streamlit Community Cloud) separately. Go to the [app dashboard](https://share.streamlit.io/) and in the app's dropdown menu, click on Edit Secrets. Copy the content of `secrets.toml` into the text area. More information is available at [Secrets management](/deploy/streamlit-community-cloud/deploy-your-app/secrets-management).
## Add PyTigerGraph to your requirements file
Add the pyTigerGraph package to your `requirements.txt` file, preferably pinning its version (replace `x.x.x` with the version you want installed):
```bash
# requirements.txt
pyTigerGraph==x.x.x
```
## Write your Streamlit app
Copy the code below to your Streamlit app and run it. Make sure to adapt the name of your graph and query.
```python
# streamlit_app.py
import streamlit as st
import pyTigerGraph as tg
# Initialize connection.
conn = tg.TigerGraphConnection(**st.secrets["tigergraph"])
conn.apiToken = conn.getToken(conn.createSecret())
# Pull data from the graph by running the "mostDirectInfections" query.
# Uses st.cache_data to only rerun when the query changes or after 10 min.
@st.cache_data(ttl=600)
def get_data():
most_infections = conn.runInstalledQuery("mostDirectInfections")[0]["Answer"][0]
return most_infections["v_id"], most_infections["attributes"]
items = get_data()
# Print results.
st.title(f"Patient {items[0]} has the most direct infections")
for key, val in items[1].items():
st.write(f"Patient {items[0]}'s {key} is {val}.")
```
See `st.cache_data` above? Without it, Streamlit would run the query every time the app reruns (e.g. on a widget interaction). With `st.cache_data`, it only runs when the query changes or after 10 minutes (that's what `ttl` is for). Watch out: If your database updates more frequently, you should adapt `ttl` or remove caching so viewers always see the latest data. Learn more in [Caching](/develop/concepts/architecture/caching).
If everything worked out (and you used the example data we created above), your app should look like this:
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