--- 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. ![TG_Cloud_COVID19](/images/databases/tigergraph-1.png) Once it is started, ensure your data is downloaded and queries are installed. ![TG_Cloud_Schema](/images/databases/tigergraph-2.png) ## 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" ``` Add this file to `.gitignore` and don't commit it to your GitHub repo! ## 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). ![Secrets manager screenshot](/images/databases/edit-secrets.png) ## 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: ![Final_App](/images/databases/tigergraph-3.png)