Python XLSX extractor & Supabase table seed example

This project is a crude example of how you can use Python to extract data from an Excel spreadsheet (.xlsx) and then seed a Supabase database table with the extracted data.

The spreadsheet example used in this project is equity instrument data from the London Stock Exchange. Simply put, the data is list of tradable securities (such as stocks, bonds & ETFs) on the London Stock Exchange.

Setup, Install & Use

Prerequisites

You will need to be able to setup a simple Supabase database and have the URL & KEY ready.

Setup

After you have cloned the repository:

• Install required Python packages: pip install -r requirements.txt
• Copy the .env.example file contents into a new file called .env
• Alter the SUPABASE_URL & SUPABASE_KEY to your respective Supabase database values

Extract data from spreadsheet

Run python ./main.py and once it has completed you should now see headings.txt and instruments.json

• headings.txt: A text file containing the column headings relative to the spreadsheet data. You can use these to create the table column names in the database.
• instruments.json: Each of the spreadsheet rows formatted into JSON, this will be used to seed the database

Supabase Table Setup

• Add a table named lse_instruments and create the respective columns from headings.txt
• Note:
  • The TIDM column should be set as the primary key
  • For simplicity add all of the columns as a text datatype and allow each of them to be nullable

Seed Supabase table with extracted spreadsheet data

• Finally to seed the newly created table with the data extracted from the Spreadsheet simply run python ./seed.py and wait for it to complete

Once these steps have been completed you should now be able to browse to your Supabase table on the web ui and see the populated data.