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---
title: Connect Streamlit to Supabase
slug: /develop/tutorials/databases/supabase
---
# Connect Streamlit to Supabase
## Introduction
This guide explains how to securely access a Supabase instance from Streamlit Community Cloud. It uses [st.connection](/develop/api-reference/connections/st.connection), [Streamlit Supabase Connector](https://github.com/SiddhantSadangi/st_supabase_connection/tree/main) (a community-built connection developed by [@SiddhantSadangi](https://github.com/SiddhantSadangi)) and Streamlit's [Secrets management](/deploy/streamlit-community-cloud/deploy-your-app/secrets-management). Supabase is the open source Firebase alternative and is based on PostgreSQL.
<Note>
Community-built connections, such as the [Streamlit Supabase Connector](https://github.com/SiddhantSadangi/st_supabase_connection/tree/main), extend and build on the `st.connection` interface and make it easier than ever to build Streamlit apps with a wide variety of data sources. These type of connections work exactly the same as [the ones built into Streamlit](/develop/api-reference/connections) and have access to all the same capabilities.
</Note>
## Sign in to Supabase and create a project
First, head over to [Supabase](https://app.supabase.io/) and sign up for a free account using your GitHub.
<Flex>
<Image caption="Sign in with GitHub" src="/images/databases/supabase-1.png" />
<Image caption="Authorize Supabase" src="/images/databases/supabase-2.png" />
</Flex>
Once you're signed in, you can create a project.
<Flex>
<Image caption="Your Supabase account" src="/images/databases/supabase-3.png" />
<Image caption="Create a new project" src="/images/databases/supabase-4.png" />
</Flex>
Your screen should look like this once your project has been created:
<Image src="/images/databases/supabase-5.png" />
<Important>
Make sure to note down your Project API Key and Project URL highlighted in the above screenshot. ☝️
You will need these to connect to your Supabase instance from Streamlit.
</Important>
## Create a Supabase database
Now that you have a project, you can create a database and populate it with some sample data. To do so, click on the **SQL editor** button on the same project page, followed by the **New query** button in the SQL editor.
<Flex>
<Image caption="Open the SQL editor" src="/images/databases/supabase-6.png" />
<Image caption="Create a new query" src="/images/databases/supabase-7.png" />
</Flex>
In the SQL editor, enter the following queries to create a database and a table with some example values:
```sql
CREATE TABLE mytable (
name varchar(80),
pet varchar(80)
);
INSERT INTO mytable VALUES ('Mary', 'dog'), ('John', 'cat'), ('Robert', 'bird');
```
Click **Run** to execute the queries. To verify that the queries were executed successfully, click on the **Table Editor** button on the left menu, followed by your newly created table `mytable`.
<Flex>
<Image caption="Write and run your queries" src="/images/databases/supabase-8.png" />
<Image caption="View your table in the Table Editor" src="/images/databases/supabase-9.png" />
</Flex>
With your Supabase database created, you can now connect to it from Streamlit!
### Add Supabase Project URL and API key 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 the `SUPABASE_URL` and `SUPABASE_KEY` here:
```toml
# .streamlit/secrets.toml
[connections.supabase]
SUPABASE_URL = "xxxx"
SUPABASE_KEY = "xxxx"
```
Replace `xxxx` above with your Project URL and API key from [Step 1](/develop/tutorials/databases/supabase#sign-in-to-supabase-and-create-a-project).
<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).
![Secrets manager screenshot](/images/databases/edit-secrets.png)
## Add st-supabase-connection to your requirements file
Add the [`st-supabase-connection`](https://pypi.org/project/st-supabase-connection/) community-built connection library to your `requirements.txt` file, preferably pinning its version (replace `x.x.x` with the version you want installed):
```bash
# requirements.txt
st-supabase-connection==x.x.x
```
<Tip>
We've used the `st-supabase-connection` library here in combination with `st.connection` to benefit from the ease of setting up the data connection, managing your credentials, and Streamlit's caching capabilities that native and community-built connections provide.
You can however still directly use the [Supabase Python Client Library](https://pypi.org/project/supabase/) library if you prefer, but you'll need to write more code to set up the connection and cache the results. See [Using the Supabase Python Client Library](/develop/tutorials/databases/supabase#using-the-supabase-python-client-library) below for an example.
</Tip>
## Write your Streamlit app
Copy the code below to your Streamlit app and run it.
```python
# streamlit_app.py
import streamlit as st
from st_supabase_connection import SupabaseConnection
# Initialize connection.
conn = st.connection("supabase",type=SupabaseConnection)
# Perform query.
rows = conn.query("*", table="mytable", ttl="10m").execute()
# Print results.
for row in rows.data:
st.write(f"{row['name']} has a :{row['pet']}:")
```
See `st.connection` above? This handles secrets retrieval, setup, query caching and retries. By default, `query()` results are cached without expiring. In this case, we set `ttl="10m"` to ensure the query result is cached for no longer than 10 minutes. You can also set `ttl=0` to disable caching. Learn more in [Caching](/develop/concepts/architecture/caching).
If everything worked out (and you used the example table we created above), your app should look like this:
![Finished app screenshot](/images/databases/supabase-10.png)
As Supabase uses PostgresSQL under the hood, you can also connect to Supabase by using the connection string Supabase provides under Settings > Databases. From there, you can refer to the [PostgresSQL tutorial](/develop/tutorials/databases/postgresql) to connect to your database.
## Using the Supabase Python Client Library
If you prefer to use the [Supabase Python Client Library](https://pypi.org/project/supabase/) directly, you can do so by following the steps below.
1. Add your Supabase Project URL and API key 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 the SUPABASE_URL and SUPABASE_KEY here:
```toml
# .streamlit/secrets.toml
SUPABASE_URL = "xxxx"
SUPABASE_KEY = "xxxx"
```
2. Add `supabase` to your requirements file:
Add the [`supabase`](https://github.com/supabase-community/supabase-py) Python Client Library to your `requirements.txt` file, preferably pinning its version (replace `x.x.x` with the version you want installed):
```bash
# requirements.txt
supabase==x.x.x
```
3. Write your Streamlit app:
Copy the code below to your Streamlit app and run it.
```python
# streamlit_app.py
import streamlit as st
from supabase import create_client, Client
# Initialize connection.
# Uses st.cache_resource to only run once.
@st.cache_resource
def init_connection():
url = st.secrets["SUPABASE_URL"]
key = st.secrets["SUPABASE_KEY"]
return create_client(url, key)
supabase = init_connection()
# Perform query.
# Uses st.cache_data to only rerun when the query changes or after 10 min.
@st.cache_data(ttl=600)
def run_query():
return supabase.table("mytable").select("*").execute()
rows = run_query()
# Print results.
for row in rows.data:
st.write(f"{row['name']} has a :{row['pet']}:")
```
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).