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Getting Started

Use Supabase with Python

Learn how to create a Supabase project, add some sample data to your database, and query the data from a Python app.

1. Create a Supabase project#

Before you can use Supabase, you need a Supabase project. You can create a project visually in the Dashboard or programmatically using the Management API.

Create a new Supabase project from the Dashboard of any organization you belong to.

2. Install agent skills (optional)#

Agent Skills are curated instruction sets that give your AI agent procedural knowledge about working with Supabase.

Install them in your project with:

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npx skills add supabase/agent-skills

3. Set up your database#

When your Supabase project is up and running, create an instruments table with some sample data. Then set only the privileges each Postgres role needs, add Row Level Security (RLS) for enhanced security for database data by default, and create an RLS policy to make the data in the table publicly readable.

Or do this manually in your project's SQL Editor, by pasting the SQL below, and clicking Run.

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-- Create the table
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create table instruments (
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  id bigint primary key generated always as identity,
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  name text not null
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);
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-- Insert sample data into the table
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insert into instruments (name)
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values
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  ('violin'),
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  ('viola'),
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  ('cello');
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-- Grant the privileges the role needs, which is read access
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grant select on public.instruments to anon;
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-- Enable row level security for the table
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alter table instruments enable row level security;
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-- Create a policy to allow the anon role to read from the instruments table
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create policy "public can read instruments"
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on public.instruments
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for select to anon
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using (true);

4. Create a Python app with Flask#

Create a new directory for your Python app and set up a virtual environment.

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mkdir my-app && cd my-app
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python3 -m venv venv
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source venv/bin/activate

5. Install Flask and the Supabase client library#

The fastest way to get started is to use Flask for the web framework and the supabase-py client library which provides a convenient interface for working with Supabase from a Python app.

Install both packages using pip.

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pip install flask supabase

Get API details#

To interact with data in database tables, you use the client libraries that wrap the auto-generated Data API endpoints, authenticating using the Project URL and key from the project Connect dialog.

Project URL
Publishable key

6. Create environment variables file#

Create a .env file in your project root and populate it with your Supabase connection variables that you can get from the helper above, or from the project Connect panel:

Open Connect panel
.env
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SUPABASE_URL=<SUBSTITUTE_SUPABASE_URL>
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SUPABASE_PUBLISHABLE_KEY=<SUBSTITUTE_SUPABASE_PUBLISHABLE_KEY>

7. Query data from the app#

Install the python-dotenv package to load environment variables:

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pip install python-dotenv

Create an app.py file and add a route that fetches data from your instruments table using the Supabase client.

app.py
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import os
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from flask import Flask
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from supabase import create_client, Client
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from dotenv import load_dotenv
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load_dotenv()
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app = Flask(__name__)
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supabase: Client = create_client(
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    os.environ.get("SUPABASE_URL"),
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    os.environ.get("SUPABASE_PUBLISHABLE_KEY")
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)
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@app.route('/')
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def index():
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    response = supabase.table('instruments').select("*").execute()
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    instruments = response.data
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    html = '<h1>Instruments</h1><ul>'
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    for instrument in instruments:
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        html += f'<li>{instrument["name"]}</li>'
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    html += '</ul>'
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    return html
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if __name__ == '__main__':
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    app.run(debug=True)

8. Start the app#

Run the Flask development server, and go to http://localhost:5000 in your browser, you should see the list of instruments.

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python app.py

Next steps#