mirror of
https://github.com/supabase/supabase.git
synced 2026-07-05 21:14:30 +08:00
186 lines
7.9 KiB
Plaintext
186 lines
7.9 KiB
Plaintext
---
|
||
title: Python data loading with Supabase
|
||
description: An example of how to load data into Supabase using supabase-py
|
||
author: ant_wilson
|
||
image: python-1/python.jpg
|
||
thumb: python-1/python.jpg
|
||
tags:
|
||
- python
|
||
- open-source
|
||
- community
|
||
date: '2022-06-17'
|
||
toc_depth: 3
|
||
---
|
||
|
||
Python is an excellent choice when it comes to data science. With a wide selection of libraries and built-in analytics tools, you can crunch data with ease, analyze even the most complex datasets, and visualize your results in beautiful charts and graphs.
|
||
|
||
Supabase is backend-as-a-service built on top of PostgreSQL. It’s an excellent choice for building modern data-intensive apps and tooling.
|
||
|
||
Thanks to our incredible community, Supabase now has a powerful and open source [Python SDK](https://github.com/supabase-community/supabase-py). With Supabase and Python, you can automate tasks such as CRUD operations with only a few lines of code. This guide will first create a simple schema in Supabase, then we’ll use the Supabase Python SDK to show how you can load sample data.
|
||
|
||
## Prerequisites
|
||
|
||
Before we dive in, let’s look at some prerequisites you'll need:
|
||
- Python version > 3.7
|
||
- The SDK only supports version > 3.7. You can download a supported Python version from [here](https://www.python.org/downloads/).
|
||
- Python virtual environment
|
||
- This is optional, but it will avoid issues of package dependencies and version conflicts. You can find the steps to create a virtual environment [here](https://uoa-eresearch.github.io/eresearch-cookbook/recipe/2014/11/26/python-virtual-env/). We will be using PyCharm to harness its venv creation capabilities.
|
||
- Faker python package
|
||
- We will be using the [faker-commerce](https://pypi.org/project/faker-commerce/) package from the Faker library in Python to generate realistic sample data.
|
||
|
||
|
||
## Loading data into Supabase using Python
|
||
Supabase is built for developers, and you can [get started for free](https://app.supabase.com) using your existing Github account. Once your Supabase account is set up, you will access the Supabase dashboard. From here, go to All Project > New Project.
|
||
|
||
|
||
|
||
Give your project a name and set the database password. You can also choose the region and adjust the pricing plan based on the requirements of your project.
|
||
|
||
|
||
|
||
Your project will spin up within 2 minutes.
|
||
|
||
## Creating tables in Supabase
|
||
|
||
In this example, we’ll be creating 2 tables in Supabase:
|
||
- Vendor (fields are vendor_name, vendor_location, and total_employees)
|
||
- Product (vendor_id as FK, product_name, price, and total orders)
|
||
|
||
The database schema will look like the following:
|
||
|
||
|
||
|
||
Let us now begin creating the tables. Once you create a project, you will need to go to Table Editor > New Table
|
||
|
||
|
||
|
||
Now, you can create a table according to the defined schema.
|
||
|
||
|
||
Click on Save to create your vendor table. Similarly, create the product table.
|
||
|
||
|
||
|
||
Before you click Save, you need to set up the foreign key relationship between the Product and Vendor table. To do this, select the button next to “vendor_id”
|
||
|
||
|
||
Select the vendor_id primary key from the “Vendor” table.
|
||
|
||
|
||
|
||
Click on Save and you are good to go. You should now see the 2 tables under Table Editor.
|
||
|
||
|
||
|
||
## Installing the Python SDK
|
||
|
||
Once you have set up the tables and installed the prerequisites, you can now start playing around with the [Python SDK](https://github.com/supabase-community/supabase-py). To install the SDK, run the following command:
|
||
|
||
`pip3 install supabase`
|
||
|
||
Ensure that you are running this inside your python virtual environment. This will take a few minutes to complete.
|
||
|
||
## Using Supabase API keys
|
||
|
||
The SDK authentication uses API keys pointing to a project URL. To find out your project URL and APIs, go to Settings > API.
|
||
|
||
|
||
|
||
## Setting up the environment variables
|
||
|
||
API credentials and project URL can be stored in environment variables. Setting the environment variables in bash/zsh is very simple. All we need to do is run:
|
||
|
||
```bash
|
||
export <variable_name>=<variable_value>
|
||
```
|
||
|
||
So for our example we will set them up like this:
|
||
|
||
```bash
|
||
export SUPABASE_URL=<<the value under config > URL>>
|
||
export SUPABASE_KEY=<<the value present in Project API keys > anon public>>
|
||
export SUPABASE_SECRET_KEY=<<the value present in Project API keys > service_role secret>>
|
||
```
|
||
|
||
## Inserting data into Supabase
|
||
|
||
Here is a snippet of the code we will be using to insert random data into our tables:
|
||
|
||
```python
|
||
import os
|
||
import json
|
||
from dotenv import load_dotenv
|
||
from supabase import create_client, Client
|
||
from faker import Faker
|
||
import faker_commerce
|
||
|
||
|
||
def add_entries_to_vendor_table(supabase, vendor_count):
|
||
fake = Faker()
|
||
foreign_key_list = []
|
||
fake.add_provider(faker_commerce.Provider)
|
||
main_list = []
|
||
for i in range(vendor_count):
|
||
value = {'vendor_name': fake.company(), 'total_employees': fake.random_int(40, 169),
|
||
'vendor_location': fake.country()}
|
||
|
||
main_list.append(value)
|
||
data = supabase.table('Vendor').insert(main_list).execute()
|
||
data_json = json.loads(data.json())
|
||
data_entries = data_json['data']
|
||
for i in range(len(data_entries)):
|
||
foreign_key_list.append(int(data_entries[i]['vendor_id']))
|
||
return foreign_key_list
|
||
|
||
|
||
def add_entries_to_product_table(supabase, vendor_id):
|
||
fake = Faker()
|
||
fake.add_provider(faker_commerce.Provider)
|
||
main_list = []
|
||
iterator = fake.random_int(1, 15)
|
||
for i in range(iterator):
|
||
value = {'vendor_id': vendor_id, 'product_name': fake.ecommerce_name(),
|
||
'inventory_count': fake.random_int(1, 100), 'price': fake.random_int(45, 100)}
|
||
main_list.append(value)
|
||
data = supabase.table('Product').insert(main_list).execute()
|
||
|
||
|
||
def main():
|
||
vendor_count = 10
|
||
load_dotenv()
|
||
url: str = os.environ.get("SUPABASE_URL")
|
||
key: str = os.environ.get("SUPABASE_KEY")
|
||
supabase: Client = create_client(url, key)
|
||
fk_list = add_entries_to_vendor_table(supabase, vendor_count)
|
||
for i in range(len(fk_list)):
|
||
add_entries_to_product_table(supabase, fk_list[i])
|
||
|
||
|
||
main()
|
||
```
|
||
|
||
To summarize what we have done using this code snippet:
|
||
- We have inserted 10 random vendors to the table.
|
||
- For each of the 10 vendors, we have inserted a number of different products
|
||
|
||
## Reading the data stored in Supabase
|
||
|
||
Data can also be viewed directly from the Supabase dashboard. To do this, go to `Table Editor > All tables`
|
||
|
||
|
||
|
||
|
||
Note: In case you cannot see any of the data, you should hit the Refresh button.
|
||
|
||
## Conclusion
|
||
With Python, data loading into Supabase is easy. It just takes a few easy steps to get started with the Python SDK and Supabase. In the next part of this blog series, we will learn [how to visualize the data that we just loaded into Supabase using Metabase](/blog/visualizing-supabase-data-using-metabase). Stay tuned!
|
||
|
||
If you have any questions please reach out via [Twitter](https://twitter.com/supabase) or join our [Discord](https://discord.supabase.com).
|
||
|
||
## More Python and Supabase resources
|
||
- [supabase-py](https://github.com/supabase-community/supabase-py)
|
||
- [Slack Consolidate: a slackbot built with Python and Supabase](blog/slack-consolidate-slackbot-to-consolidate-messages)
|
||
- [Supabase-py (Database) on Replit](https://replit.com/@Supabase/Supabase-py-Database?v=1)
|
||
|
||
|