Use Firestore in Datastore mode (Datastore)

Firestore is a NoSQL document database built for automatic scaling, high performance, and ease of application development. It is the newest version of Datastore and introduces several improvements over Datastore. Because Firestore in Datastore mode (Datastore) is optimized for server use cases and for App Engine, we recommend using Datastore for databases that will be used primarily by App Engine apps. Firestore in Native mode is most useful for mobile and real-time notification use cases. For more information about Firestore modes, see Choosing between Native Mode and Datastore mode.

This document describes how to use the Cloud Client Libraries to store and retrieve data in a Datastore mode database. You can use the sample application in this guide for any supported version of Python by specifying the runtime version and operating system in your app.yaml file.

Prerequisites and setup

Set up your environment and project to understand how apps are structured in App Engine. Write down and save your project ID, because you will need it to run the sample application described in this document.

Clone the repository

Download (clone) the sample:

  git clone https://github.com/GoogleCloudPlatform/python-docs-samples
  cd python-docs-samples/appengine/flexible/datastore

Edit project configuration and set dependencies

Include the google-cloud-datastore library in requirements.txt file. This is the client library for Datastore mode.

Flask==3.0.3
google-cloud-datastore==2.20.1
gunicorn==23.0.0

Application code

The sample application logs, retrieves, and displays visitor IPs. You can see that a log entry is a two-field class that is given the type visit, and is saved to Datastore mode using the put command. Then, the ten most recent visits are retrieved in descending order using the query() command.

@app.route("/")
def index():
    ds = datastore.Client()

    user_ip = request.remote_addr

    # Keep only the first two octets of the IP address.
    if is_ipv6(user_ip):
        user_ip = ":".join(user_ip.split(":")[:2])
    else:
        user_ip = ".".join(user_ip.split(".")[:2])

    entity = datastore.Entity(key=ds.key("visit"))
    entity.update(
        {
            "user_ip": user_ip,
            "timestamp": datetime.datetime.now(tz=datetime.timezone.utc),
        }
    )

    ds.put(entity)
    query = ds.query(kind="visit", order=("-timestamp",))

    results = []
    for x in query.fetch(limit=10):
        try:
            results.append("Time: {timestamp} Addr: {user_ip}".format(**x))
        except KeyError:
            print("Error with result format, skipping entry.")

    output = "Last 10 visits:\n{}".format("\n".join(results))

    return output, 200, {"Content-Type": "text/plain; charset=utf-8"}

Using `index.yaml` files

The sample app performs queries. More elaborate Datastore mode queries require one or more indexes, which you must specify in an index.yaml file that you upload along with your app. This file may be created manually, or generated automatically while testing your app locally.

Local testing

If you need to develop and test your application locally, you can use the Datastore mode emulator.

For more information

For complete information on Datastore mode, including optimizations and concepts, see the Firestore in Datastore mode documentation.