The App Engine Python 2.7 runtime includes several third-party libraries that your application can use.

Third-party libraries must be specified in app.yaml , and this configuration is different than in Python 2.5 (see Configuring Libraries for details).

Django Notes

Django is a full-featured web application framework for Python. It provides a full stack of interchangable components, including dispatch, views, middleware, and templating components, and many others.

The Django data modeling interface is not compatible with the App Engine datastore. You can use the App Engine data modeling libraries ( db or ndb ) in your Django applications. However, third-party Django applications that use the Django data modeling interface—most notably Django's Admin application—may not work with App Engine directly.

To use Django with the NDB storage API , add 'google.appengine.ext.ndb.django_middleware.NdbDjangoMiddleware', to the MIDDLEWARE_CLASSES entry in your Django settings.py file. It's best to insert it in front of any other middleware classes, since some other middleware may make datastore calls and those won't be handled properly if that middleware is invoked before this middleware. (You can learn more about Django middleware .)

To use Django, specify the WSGI application and Django library in app.yaml :

...
handlers:
- url: /.*
  script: main.app  # a WSGI application in the main module's global scope

libraries:
- name: django
  version: "1.2"

The DJANGO_SETTINGS_MODULE environment variable must be set to the name of your Django settings module, typically 'settings' , before packages are imported.

If your Django settings module is something other than settings.py , set the DJANGO_SETTINGS_MODULE environment variable accordingly either in your app.yaml file:

env_variables:
  DJANGO_SETTINGS_MODULE: 'myapp.settings'

or in your Python code:

import os
# specify the name of your settings module
os.environ['DJANGO_SETTINGS_MODULE'] = 'myapp.settings'

import django.core.handlers.wsgi
app = django.core.handlers.wsgi.WSGIHandler()

Matplotlib Notes

Note: The experimental release of matplotlib is not supported on the development server. You can still add matplotlib to the libraries list, but it will raise an ImportError exception when imported.

Matplotlib is a plotting library that produces graphs and figures in a variety of image formats. On App Engine, the interactive modes of matplotlib are not supported, and a number of other features are also unavailable. This means you cannot use pyplot.show() as many matplotlib tutorials suggest. Instead, you should use pyplot.savefig() to write image data to the output stream, a cStringIO.StringIO instance, or the Blobstore using the Files API .

Matplotlib allows extensive customization through the use of the matplotlibrc configuration file, which should be placed in the application's top-level directory. Alternatively, you can set the MATPLOTLIBRC environment variable to a path relative to your application's directory.

The default backend is AGG, which allows writing files of all supported formats: PNG (the default format), RAW, PS, PDF, SVG and SVGZ. If you make the PIL library available by adding PIL to the libraries section of app.yaml , then the AGG backend will automatically support writing JPEG and TIFF image formats as well.

Matplotlib comes with a number of fonts which are automatically available. You can use custom fonts by uploading them (in TTF format) along with your application, and setting the TTFPATH environment variable to the path where they are located, relative to your application's directory. (See Defining Environment Variables .)

A number of matplotlib features are not supported on App Engine. In particular:

• There is no ~/.matplotlib directory (however, there are alternative locations to place the matplotlibrc configuration file, as described above).
• Interactive backends and GUI elements are not supported.
• The EMF, Cairo and GDK backends are not supported.
• There is no caching, and therefore a number of mechanisms will re-calculate or re-download data that would normally be cached. Specific caching mechanisms that have been disabled include font data (calculated by matplotlib.font_manager.FontManager.findfont ), sample data (downloaded by matplotlib.cbook.get_sample_data ) and financial data (downloaded by matplotlib.finance.fetch_historical_yahoo ).
  • Because there is no caching, it is not possible to call matplotlib.cbook.get_sample_data with asfileobj=False unless examples.download is set to False .
• All features that invoke external commands have been disabled.
  • Use of fontconfig has been disabled. Fonts are found through the mechanism described above.
  • Use of LaTeX for text rendering is not supported. Setting text.usetex to True will not work.
  • Use of an external PostScript distiller program is not supported. Setting ps.usedistiller to ghostscript or xpdf will not work.
  • Use of an external video encoding program is not supported. The matplotlib.animation.Animation.save method will not work, and therefore, the matplotlib.animation package is not useful.
  • The matplotlib.cbook.report_memory function and matplotlib.cbook.MemoryMonitor class are not supported.
• The matplotlib.test function has been disabled.

Note: The pylab and matplotlib.pyplot modules are stateful and not thread-safe. If you use them on App Engine, you must set threadsafe: false in app.yaml , and be aware that the plotter state will be preserved between requests on the same instance. For example, you will need to call pyplot.clf() at the beginning of each request to ensure that previous plots are not visible. It is recommended that you use the thread-safe object-oriented API instead of the stateful pyplot API.

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