Access legacy bundled services for Python 3

This page describes how to install and use legacy bundled services with the Python 3 runtime for the standard environment. Your app must access the bundled services through the App Engine services SDK for Python 3.

Before you begin

Installing the App Engine services SDK

To install the App Engine services SDK, follow these steps:

  1. Include the SDK with your app by adding the following line to your requirements.txt file:

    appengine-python-standard>=1.0.0
    

    You can find the SDK on GitHub under the appengine-python-standard repo, and on PyPI.

  2. Add the following code in your main Python script. This code creates WSGI middleware that sets the variables required to enable your API calls.

    Flask

    from flask import Flask
    from google.appengine.api import wrap_wsgi_app
    
    app = Flask(__name__)
    app.wsgi_app = wrap_wsgi_app(app.wsgi_app)
    

    Django

    from DJANGO_PROJECT_NAME.wsgi import application
    from google.appengine.api import wrap_wsgi_app
    
    app = wrap_wsgi_app(application)
    

    Pyramid

    from pyramid.config import Configurator
    from google.appengine.api import wrap_wsgi_app
    
    config = Configurator()
    # make configuration settings
    app = config.make_wsgi_app()
    app = wrap_wsgi_app(app)
    

    WSGI

    import google.appengine.api
    
    def app(environ, start_response):
        start_response('200 OK', [('Content-Type', 'text/plain')])
        yield b'Hello world!\n'
    
    app = google.appengine.api.wrap_wsgi_app(app)
    
  3. Add the following line to your app.yaml file before deploying your app:

    app_engine_apis: true
    
  4. To deploy your app, use the gcloud app deploy command.

Migration considerations

You should be aware of the following considerations if you are migrating to the Python 3 runtime and your app uses legacy bundled services.

Testing

To locally test the legacy bundled services functionality in your Python 3 app, use the local development server. When running the dev_appserver.py command, you must set the --runtime_python_path argument to include a path to the Python 3 interpreter. For example:

   python3 CLOUD_SDK_ROOT/bin/dev_appserver.py --runtime_python_path=/usr/bin/python3

You can also set the argument to a comma-separated list of [RUNTIME_ID]=[PYTHON_INTERPRETER_PATH] pairs. For example:

   python3 CLOUD_SDK_ROOT/bin/dev_appserver.py --runtime_python_path="python27=/user/bin/python2.7,python3=/usr/bin/python3"

Pickle Compatibility

Shared services including Memcache, Cloud NDB and deferred use the pickle module to serialize and share Python objects. If your App Engine environment uses both Python 2 and Python 3, which is common during a migration, you must ensure that shared serialized objects written by one version of Python can be reconstitued by the other. You can find guidance on implementing cross version pickle compatibility in the guide.

By default, Python 3 uses pickling protocols that are not supported in Python 2. This can cause failures when your app tries to reconstitute a Python object in a Python 2 environment that was written in a Python 3 environment. To avoid this issue, set the following environment variables in the app.yaml file for your Python 3 app as needed:

  • For apps that use Memcache including apps that use NDB, set: MEMCACHE_USE_CROSS_COMPATIBLE_PROTOCOL: 'True'
  • For apps that use NDB to connect to Datastore, set: NDB_USE_CROSS_COMPATIBLE_PICKLE_PROTOCOL: 'True'
  • For apps that use deferred, set: DEFERRED_USE_CROSS_COMPATIBLE_PICKLE_PROTOCOL: 'True'

In Python 2, string objects hold a sequence of 8 bit byte values. In Python 3, string objects hold a sequence of unicode characters. By default Python 3 pickle translates a Python 2 string to unicode by interpreting the Python 3 string as ASCII. This can lead to errors for values outside the ASCII character range of 0 to 127. Memcache supports overriding this default mapping.

from google.appengine.api import memcache
import six.moves.cPickle as pickle

def _unpickle_factory(file):
    return pickle.Unpickler(file, encoding='latin1')

memcache.setup_client(memcache.Client(unpickler=_unpickle_factory))

The latin1 encoding, defines a mapping for each of the 256 possible values of each byte in a Python 2 string. This prevents decoding errors. However, if your Python 2 string contains actual unicode data outside of the latin1 range, such as data read from a file, cPickle won't map the data correctly. Therefore, it is important that you update your Python 2 code to hold unicode data with unicode objects and not string objects, for objects you Pickle. The compatibility guide includes details on the needed updates.

The previous described method for updating your Python 2 code to produce Python 3 compatible serializations addresses short-lived serializations, such as those stored in Memcache. You might need to update or rewrite long-lived Python 2 serializations, such as those stored in Datastore as part of your migration. For example, serialization written using google.appengine.ext.ndb.model.PickleProperty might require an upgrade.

See the compatibility guide to learn more about limitations and less common issues.

Web frameworks

webapp2 is not bundled or supported in Python 3, so any application needs to be rewritten to make use of any WSGI-compatible framework (such as Flask).

A recommended migration strategy is to first replace the use of webapp2 in your Python 2.7 app with Flask (or an alternative web framework such as Django, Pyramid, Bottle, or web.py), while remaining on Python 2.7. Then, when your updated app is stable, migrate the code to Python 3 and deploy and test using App Engine for Python 3.

For examples of how to convert Python 2.7 apps which use webapp2 to use the Flask framework, you can refer to these additional resources.

Using handlers

A Python 3 app can only have one script associated with it, so if your app.yaml has multiple script handlers mapping URLs to different scripts, you will need to combine those scripts into one which handles the URL routing.

The following example shows the handler differences in the app.yaml file for the respective runtimes.

Python 2

runtime: python27
api_version: 1
threadsafe: true

handlers:
- url: /
  script: home.app

- url: /index\.html
  script: home.app

- url: /stylesheets
  static_dir: stylesheets

- url: /(.*\.(gif|png|jpg))$
  static_files: static/\1
  upload: static/.*\.(gif|png|jpg)$

- url: /admin/.*
  script: admin.app
  login: admin

- url: /.*
  script: not_found.app

Python 3

runtime: python312
app_engine_apis: true

handlers:
- url: /stylesheets
  static_dir: stylesheets

- url: /(.*\.(gif|png|jpg))$
  static_files: static/\1
  upload: static/.*\.(gif|png|jpg)$

- url: /admin/.*
  script: auto
  login: admin

Your Python 3 app must handle URL routing (for example, with Flask decorators).

If you want to use multiple script handlers with different URL patterns, or if you want to use other attributes in your handlers, each handler must specify script: auto.

You can also override the default startup behavior by specifying an entrypoint field in your app.yaml file.

See the Blobstore, Deferred, and Mail overviews for more information on how to use specific handlers.

Thread safety

Apps are assumed to be thread safe. API calls must be made on the request thread. If you use a legacy bundled services API when the app is starting, this can lead to security errors.

To learn more, see Security errors when using legacy bundled services for Python.

Using URL Fetch

To use URL Fetch for Python, you need to explicitly call the URL Fetch library.

If your Python 3 app uses the URL Fetch API, the X-Appengine-Inbound-Appid request header is added when your app sends a request to another App Engine app. This allows the receiving app to verify the calling app's identity. To learn more, see Migrating outbound requests.

Example (App Engine ndb)

Below is a basic Python 2 app registering page visits using App Engine ndb to access Datastore. Its companion is a Python 3 equivalent app where webapp2 usage has been replaced by Flask, and the required changes described above to access bundled services in Python 3 have been implemented.

Python 2 (webapp2)

import os
import webapp2
from google.appengine.ext import ndb
from google.appengine.ext.webapp import template

class Visit(ndb.Model):
    'Visit entity registers visitor IP address & timestamp'
    visitor   = ndb.StringProperty()
    timestamp = ndb.DateTimeProperty(auto_now_add=True)

def store_visit(remote_addr, user_agent):
    'create new Visit entity in Datastore'
    Visit(visitor='{}: {}'.format(remote_addr, user_agent)).put()

def fetch_visits(limit):
    'get most recent visits'
    return Visit.query().order(-Visit.timestamp).fetch(limit)

class MainHandler(webapp2.RequestHandler):
    'main application (GET) handler'
    def get(self):
        store_visit(self.request.remote_addr, self.request.user_agent)
        visits = fetch_visits(10)
        tmpl = os.path.join(os.path.dirname(__file__), 'index.html')
        self.response.out.write(template.render(tmpl, {'visits': visits}))

app = webapp2.WSGIApplication([
    ('/', MainHandler),
], debug=True)

Python 3 (Flask)

from flask import Flask, render_template, request
from google.appengine.api import wrap_wsgi_app
from google.appengine.ext import ndb

app = Flask(__name__)
app.wsgi_app = wrap_wsgi_app(app.wsgi_app)


class Visit(ndb.Model):
    'Visit entity registers visitor IP address & timestamp'
    visitor   = ndb.StringProperty()
    timestamp = ndb.DateTimeProperty(auto_now_add=True)

def store_visit(remote_addr, user_agent):
    'create new Visit entity in Datastore'
    Visit(visitor='{}: {}'.format(remote_addr, user_agent)).put()

def fetch_visits(limit):
    'get most recent visits'
    return Visit.query().order(-Visit.timestamp).fetch(limit)


@app.route('/')
def root():
    'main application (GET) handler'
    store_visit(request.remote_addr, request.user_agent)
    visits = fetch_visits(10)
    return render_template('index.html', visits=visits)

Both of these apps can be found in the open source repo for the Python App Engine migration content (code samples, videos, codelabs), specifically in the mod0 and mod1b folders, respectively.