Check out v4 of the Fauna CLI

v4 of the Fauna CLI is now in beta.

The new version introduces enhancements to the developer experience, including an improved authentication workflow. To get started, check out the CLI v4 quick start.

Python quick start

Use Fauna’s Python driver to query e-commerce demo data in a Python app. The driver requires Python 3.9 or later.

 

  1. Create a database with demo data

    Log in to the Fauna Dashboard, and create a database with the following configuration:

    • Region Group: Choose your preferred region group, which determines where your data resides.

    • Use demo data: Enabled.

    • Enable backups: Disabled.

    Leave the other options as is.

    Create demo database

  2. Create an authentication secret

    Fauna supports several types of authentication secrets. For this quick start, create a key, which is a type of secret, with the built-in server-readonly` role:

    1. In the Dashboard’s Explorer page, select your demo database.

    2. In the database’s Keys tab, click Create Key.

    3. Choose a Role of server (read-only).

    4. Click Save.

    5. Copy the Key Secret.

    Create a key

  3. Set the FAUNA_SECRET environment variable

    Set the FAUNA_SECRET environment variable to your key’s secret. Fauna’s client drivers can access the secret from this variable.

    export FAUNA_SECRET=<KEY_SECRET>

  4. Install the Python driver

    Create a new directory for your app and install the Python driver:

    mkdir app
cd app
pip install fauna

  5. Create a query script

    In the app directory, create an app.py file and add the following code:

    from fauna import fql
from fauna.client import Client
from fauna.encoding import QuerySuccess
from fauna.errors import FaunaException

# Initialize the client to connect to Fauna
# using the `FAUNA_SECRET` environment variable.
client = Client(secret='FAUNA_SECRET')

try:
    # Compose a query using an FQL template string.
    # The query calls the `Product` collection's
    # `sortedByPriceLowToHigh()` index. It projects the `name`,
    # `description`, and `price` fields covered by the index.
    query = fql(
        """
        Product.sortedByPriceLowToHigh() {
            name,
            description,
            price
            }"""
    )

    # Run the query.
    res: QuerySuccess = client.query(query)
    print(res.data)
except FaunaException as e:
    print(e)
finally:
    client.close()

  6. Run the script

    Run the script from the app directory. The script prints a list of e-commerce products from the demo data in the terminal.

    python app.py

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