GAE multi-module, multi-language application on localhost
You might be able to do something similar by using "appscale" (an open source project that could be able to help you, if you setup Virtual Box and load the image on it). Look at community.appscale.com
Another way (mind you, this is tricky) would be to :
1- deploy your python as a standalone project on localhost:9000
2- deploy your java as a standalone project on localhost:8000
3- Change your python and java code so that when they are in Dev, they hit the right localhost (java 
hits localhost:9000 and python hits localhost:8000)
4- Try, like @tx802 suggested, to specify a path to local_db.
I am not sure either method works, but I figure they are both worth trying at the very least.
I have a multi-module GAE Application that is structured like this:

a Python27 module, that is a regular web application. This Python app uses the Datastore API. Regular, boring web app.
a Java module (another web application) that hooks on the Datastore calls (calls made by the Python web app), and displays aggregated data about the recorded Datastore calls.

I have been able to deploy this application on the GAE cloud, and everything works fine.
However, problems arise when I want to run my application on localhost.
The Python module must be started using the Python SDK. The Java module must be started using the Java SDK.
However, the 2 SDK's do not seem to share the same datastore (I believe the 2 SDKs write/read to separate files on disk). 
It seems to me that the 2 SDK's also differ in the advancement of the Development Console implementation. 
The Python SDK sports a cleaner, more "recent-looking" Development Console (akin to the new console.developers.google.com console) than the Java SDK, which has the old-looking version of the Development Console (akin to the old appspot.com console)
So my question is, is there a way to boot 2+ modules (in different languages: Python, Java) that share the same Datastore files? That'd be nice, since it would allow the Java module to hook on the Python Datastore calls, which does not seem to be possible at the moment.