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# Using the Datastore

Storing data in a scalable web application can be tricky. A user could be interacting with any of dozens of web servers at a given time, and the user's next request could go to a different web server than the one that handled the previous request. All web servers need to be interacting with data that is also spread out across dozens of machines, possibly in different locations around the world.

Thanks to Google App Engine, you don't have to worry about any of that. App Engine's infrastructure takes care of all of the distribution, replication and load balancing of data behind a simple API—and you get a powerful query engine and transactions as well.

The default datastore for an application is now the High Replication datastore. This datastore uses the Paxos algorithm to replicate data across datacenters. The High Replication datastore is extremely resilient in the face of catastrophic failure.

One of the consequences of this is that the consistency guarantee for the datastore may differ from what you are familiar with. It also differs slightly from the Master/Slave datastore, the other datastore option that App Engine offers. In the example code comments, we highlight some ways this might affect the design of your app. For more detailed information, see Using the High Replication Datastore (HRD).

The datastore writes data in objects known as entities, and each entity has a key that identifies the entity. Entities can belong to the same entity group, which allows you to perform a single transaction with multiple entities. Entity groups have a parent key that identifies the entire entity group.

In the High Replication Datastore, entity groups are also a unit of consistency. Queries over multiple entity groups may return stale, eventually consistent results. Queries over a single entity group return up-to-date, strongly consistent, results. Queries over a single entity group are called ancestor queries. Ancestor queries use the parent key (instead of a specific entity's key).

The code samples in this guide organize like entities into entity groups, and use ancestor queries on those entity groups to return strongly consistent results. In the example code comments, we highlight some ways this might affect the design of your app. For more detailed information, see Using the High Replication Datastore.

## A Complete Example Using the Datastore

Here is a new version of `helloworld/helloworld.py` that stores greetings in the datastore. The rest of this page discusses the new pieces.

    import cgi
    import datetime
    import urllib
    import webapp2

    from google.appengine.ext import db
    from google.appengine.api import users

    class Greeting(db.Model):
      """Models an individual Guestbook entry with an author, content, and date."""
      author = db.UserProperty()
      content = db.StringProperty(multiline=True)
      date = db.DateTimeProperty(auto_now_add=True)

    def guestbook_key(guestbook_name=None):
      """Constructs a datastore key for a Guestbook entity with guestbook_name."""
      return db.Key.from_path('Guestbook', guestbook_name or 'default_guestbook')

    class MainPage(webapp2.RequestHandler):
      def get(self):
        self.response.out.write('<html><body>')
        guestbook_name=self.request.get('guestbook_name')

        # Ancestor Queries, as shown here, are strongly consistent with the High
        # Replication datastore. Queries that span entity groups are eventually
        # consistent. If we omitted the ancestor from this query there would be a
        # slight chance that Greeting that had just been written would not show up
        # in a query.
        greetings = db.GqlQuery("SELECT * "
                                "FROM Greeting "
                                "WHERE ANCESTOR IS :1 "
                                "ORDER BY date DESC LIMIT 10",
                                guestbook_key(guestbook_name))

        for greeting in greetings:
          if greeting.author:
            self.response.out.write(
                '<b>%s</b> wrote:' % greeting.author.nickname())
          else:
            self.response.out.write('An anonymous person wrote:')
          self.response.out.write('<blockquote>%s</blockquote>' %
                                  cgi.escape(greeting.content))

        self.response.out.write("""
              <form action="/sign?%s" method="post">
                <div><textarea name="content" rows="3" cols="60"></textarea></div>
                <div><input type="submit" value="Sign Guestbook"></div>
              </form>
              <hr>
              <form>Guestbook name: <input value="%s" name="guestbook_name">
              <input type="submit" value="switch"></form>
            </body>
          </html>""" % (urllib.urlencode({'guestbook_name': guestbook_name}),
                              cgi.escape(guestbook_name)))

    class Guestbook(webapp2.RequestHandler):
      def post(self):
        # We set the same parent key on the 'Greeting' to ensure each greeting is in
        # the same entity group. Queries across the single entity group will be
        # consistent. However, the write rate to a single entity group should
        # be limited to ~1/second.
        guestbook_name = self.request.get('guestbook_name')
        greeting = Greeting(parent=guestbook_key(guestbook_name))

        if users.get_current_user():
          greeting.author = users.get_current_user()

        greeting.content = self.request.get('content')
        greeting.put()
        self.redirect('/?' + urllib.urlencode({'guestbook_name': guestbook_name}))

    app = webapp2.WSGIApplication([('/', MainPage),
                                   ('/sign', Guestbook)],
                                  debug=True)

Replace `helloworld/helloworld.py` with this, then reload http://localhost:8080/ in your browser. Post a few messages to verify that messages get stored and displayed correctly.

Warning! Exercising the queries in your application locally causes App Engine to create or update `index.yaml`. If `index.yaml` is missing or incomplete, you will see index errors when your uploaded application executes queries for which necessary indexes have not been specified. To avoid missing index errors in production, always test new queries at least once locally before uploading your application. See Python Datastore Index Configuration for more information.

## Storing the Submitted Greetings

App Engine includes a data modeling API for Python. It's similar to Django's data modeling API, but uses App Engine's scalable datastore behind the scenes.

For the guestbook application, we want to store greetings posted by users. Each greeting includes the author's name, the message content, and the date and time the message was posted so we can display messages in chronological order.

To use the data modeling API, import the `google.appengine.ext.db` module:

    from google.appengine.ext import db

The following defines a data model for a greeting:

    class Greeting(db.Model):
        author = db.UserProperty()
        content = db.StringProperty(multiline=True)
        date = db.DateTimeProperty(auto_now_add=True)

This defines a `Greeting` model with three properties: `author` whose value is a `User` object, `content` whose value is a string, and `date` whose value is a `datetime.datetime`.

Some property constructors take parameters to further configure their behavior. Giving the `db.StringProperty` constructor the `multiline=True` parameter says that values for this property can contain newline characters. Giving the `db.DateTimeProperty` constructor a `auto_now_add=True` parameter configures the model to automatically give new objects a `date` of the time the object is created, if the application doesn't otherwise provide a value. For a complete list of property types and their options, see the Datastore reference.

Now that we have a data model for greetings, the application can use the model to create new `Greeting` objects and put them into the datastore. The following new version of the `Guestbook` handler creates new greetings and saves them to the datastore:

    class Guestbook(webapp2.RequestHandler):
        def post(self):
          guestbook_name = self.request.get('guestbook_name')
          greeting = Greeting(parent=guestbook_key(guestbook_name))

          if users.get_current_user():
            greeting.author = users.get_current_user()

          greeting.content = self.request.get('content')
          greeting.put()
          self.redirect('/?' + urllib.urlencode({'guestbook_name': guestbook_name}))

This new `Guestbook` handler creates a new `Greeting` object, then sets its `author` and `content` properties with the data posted by the user. The parent has an entity kind "Guestbook". There is no need to create the "Guestbook" entity before setting it to be the parent of another entity. In this example, the parent is used as a placeholder for transaction and consistency purposes. See Transactions and Entity Groups for more information. Objects that share a common ancestor belong to the same entity group. It does not set the `date` property, so `date` is automatically set to "now," as we configured the model to do.

Finally, `greeting.put()` saves our new object to the datastore. If we had acquired this object from a query, `put()` would have updated the existing object. Since we created this object with the model constructor, `put()` adds the new object to the datastore.

Because querying in the High Replication datastore is only strongly consistent within entity groups, we assign all Greetings to the same entity group in this example by setting the same parent for each Greeting. This means a user will always see a Greeting immediately after it was written. However, the rate at which you can write to the same entity group is limited to 1 write to the entity group per second. When you design a real application you'll need to keep this fact in mind. Note that by using services such as Memcache, you can mitigate the chance that a user won't see fresh results when querying across entity groups immediately after a write.

## Retrieving the Stored Greetings With GQL

The App Engine datastore has a sophisticated query engine for data models. Because the App Engine datastore is not a traditional relational database, queries are not specified using SQL. Instead, you can prepare queries using a SQL-like query language we call GQL. GQL provides access to the App Engine datastore query engine's features using a familiar syntax.

The following new version of the `MainPage` handler queries the datastore for greetings:

    class MainPage(webapp2.RequestHandler):
        def get(self):
            self.response.out.write('<html><body>')
            guestbook_name=self.request.get('guestbook_name')

            greetings = db.GqlQuery("SELECT * "
                                    "FROM Greeting "
                                    "WHERE ANCESTOR IS :1 "
                                    "ORDER BY date DESC LIMIT 10",
                                    guestbook_key(guestbook_name))

            for greeting in greetings:
                if greeting.author:
                    self.response.out.write('<b>%s</b> wrote:' % greeting.author.nickname())
                else:
                    self.response.out.write('An anonymous person wrote:')
                self.response.out.write('<blockquote>%s</blockquote>' %
                                        cgi.escape(greeting.content))

            # Write the submission form and the footer of the page
            self.response.out.write("""
                  <form action="/sign" method="post">
                    <div><textarea name="content" rows="3" cols="60"></textarea></div>
                    <div><input type="submit" value="Sign Guestbook"></div>
                  </form>
                </body>
              </html>""")

The query happens here:

        greetings = db.GqlQuery("SELECT * "
                                "FROM Greeting "
                                "WHERE ANCESTOR IS :1 "
                                "ORDER BY date DESC LIMIT 10",
                                 guestbook_key(guestbook_name))

Alternatively, you can call the `gql(...)` method on the `Greeting` class, and omit the `SELECT * FROM Greeting` from the query:

        greetings = Greeting.gql("WHERE ANCESTOR IS :1 ORDER BY date DESC LIMIT 10",
                                 guestbook_key(guestbook_name))

As with SQL, keywords (such as `SELECT`) are case insensitive. Names, however, are case sensitive.

Because the query returns full data objects, it does not make sense to select specific properties from the model. All GQL queries start with `SELECT * FROM model` (or are so implied by the model's gql(...) method) so as to resemble their SQL equivalents.

A GQL query can have a `WHERE` clause that filters the result set by one or more conditions based on property values. Unlike SQL, GQL queries may not contain value constants: Instead, GQL uses parameter binding for all values in queries. For example, to get only the greetings posted by the current user:

        if users.get_current_user():
            greetings = Greeting.gql(
                "WHERE ANCESTOR IS :1 AND author = :2 ORDER BY date DESC",
                guestbook_key(guestbook_name), users.get_current_user())

You can also use named parameters instead of positional parameters:

            greetings = Greeting.gql("WHERE ANCESTOR = :ancestor AND author = :author ORDER BY date DESC",
                                     ancestor=guestbook_key(guestbook_name), author=users.get_current_user())

In addition to GQL, the datastore API provides another mechanism for building query objects using methods. The query above could also be prepared as follows:

            greetings = Greeting.all()
            greetings.ancestor(guestbook_key(guestbook_name))
            greetings.filter("author =", users.get_current_user())
            greetings.order("-date")

For a complete description of GQL and the query APIs, see the Datastore reference.

### A Word About Datastore Indexes

Every query in the App Engine datastore is computed from one or more indexes. Indexes are tables that map ordered property values to entity keys. This is how App Engine is able to serve results quickly regardless of the size of your application's datastore. Many queries can be computed from the builtin indexes, but the datastore requires you to specify a custom index for some, more complex, queries. Without a custom index, the datastore can't execute the query efficiently.

Our guest book example above, which filters results by `author` and orders by `date`, uses an ancestor query, an equality filter, and a sort order. This query requires a custom index to be specified in your application's `index.yaml` file. When you upload your application, the custom index definition will be automatically uploaded, too. You will need to add an entry to your `index.yaml` file for this query that looks like:

    indexes:
    - kind: Greeting
      ancestor: yes
      properties:
      - name: author
      - name: date
        direction: desc

You can read all about datastore indexes in the Introduction to Indexes section. You can read about the proper specification for your `index.yaml` file in Python Datastore Index Configuration.

## Next...

We now have a working guest book application that authenticates users using Google accounts, lets them submit messages, and displays messages other users have left. Because App Engine handles scaling automatically, we will not need to revisit this code as our application gets popular.

This latest version mixes HTML content with the code for the `MainPage` handler. This will make it difficult to change the appearance of the application, especially as our application gets bigger and more complex. Let's use templates to manage the appearance, and introduce static files for a CSS stylesheet.

Continue to Using Templates.