gradio/guides/05_tabular-data-science-and-plots/creating-a-dashboard-from-supabase-data.md

Create a Dashboard from Supabase Data

Tags: TABULAR, DASHBOARD, PLOTS

Supabase is a cloud-based open-source backend that provides a PostgreSQL database, authentication, and other useful features for building web and mobile applications. In this tutorial, you will learn how to read data from Supabase and plot it in real-time on a Gradio Dashboard.

Prerequisites: To start, you will need a free Supabase account, which you can sign up for here: https://app.supabase.com/

In this end-to-end guide, you will learn how to:

• Create tables in Supabase
• Write data to Supabase using the Supabase Python Client
• Visualize the data in a real-time dashboard using Gradio

If you already have data on Supabase that you'd like to visualize in a dashboard, you can skip the first two sections and go directly to visualizing the data!

Create a table in Supabase

First of all, we need some data to visualize. Following this excellent guide, we'll create fake commerce data and put it in Supabase.

1. Start by creating a new project in Supabase. Once you're logged in, click the "New Project" button

2. Give your project a name and database password. You can also choose a pricing plan (for our purposes, the Free Tier is sufficient!)

3. You'll be presented with your API keys while the database spins up (can take up to 2 minutes).

4. Click on "Table Editor" (the table icon) in the left pane to create a new table. We'll create a single table called Product, with the following schema:

product_id	int8
inventory_count	int8
price	float8
product_name	varchar

5. Click Save to save the table schema.

Our table is now ready!

Write data to Supabase

The next step is to write data to a Supabase dataset. We will use the Supabase Python library to do this.

6. Install supabase by running the following command in your terminal:

pip install supabase

7. Get your project URL and API key. Click the Settings (gear icon) on the left pane and click 'API'. The URL is listed in the Project URL box, while the API key is listed in Project API keys (with the tags service_role, secret)

8. Now, run the following Python script to write some fake data to the table (note you have to put the values of SUPABASE_URL and SUPABASE_SECRET_KEY from step 7):

import supabase

# Initialize the Supabase client
client = supabase.create_client('SUPABASE_URL', 'SUPABASE_SECRET_KEY')

# Define the data to write
import random

main_list = []
for i in range(10):
    value = {'product_id': i, 
             'product_name': f"Item {i}",
             'inventory_count': random.randint(1, 100), 
             'price': random.random()*100
            }
    main_list.append(value)

# Write the data to the table
data = client.table('Product').insert(main_list).execute()

Return to your Supabase dashboard and refresh the page, you should now see 10 rows populated in the Product table!

Visualize the Data in a Real-Time Gradio Dashboard

Finally, we will read the data from the Supabase dataset using the same supabase Python library and create a realtime dashboard using gradio.

Note: We repeat certain steps in this section (like creating the Supabase client) in case you did not go through the previous sections. As described in Step 7, you will need the project URL and API Key for your database.

9. Write a function that loads the data from the Product table and returns it as a pandas Dataframe:

import supabase
import pandas as pd

client = supabase.create_client('SUPABASE_URL', 'SUPABASE_SECRET_KEY')

def read_data():
    response = client.table('Product').select("*").execute()
    df = pd.DataFrame(response.data)
    return df

10. Create a small Gradio Dashboard with 2 Barplots that plots the prices and inventories of all of the items every minute and updates in real-time:

import gradio as gr

with gr.Blocks() as dashboard:
    with gr.Row():
        gr.BarPlot(read_data, x="product_id", y="price", title="Prices", every=60)
        gr.BarPlot(read_data, x="product_id", y="inventory_count", title="Inventory", every=60)

dashboard.queue().launch()

Notice that by passing in a function to gr.BarPlot(), we have the BarPlot query the database as soon as the web app loads (and then again every 60 seconds because of the every parameter). Your final dashboard should look something like this:

Conclusion

That's it! In this tutorial, you learned how to write data to a Supabase dataset, and then read that data and plot the results as bar plots. If you update the data in the Supabase database, you'll notice that the Gradio dashboard will update within a minute.

Try adding more plots and visualizations to this example (or with a different dataset) to build a more complex dashboard!