Use production App Engine datastore on development machine? - python

Is it possible to setup the App Engine SDK on my local machine to use the live datastore while developing? Sometimes it's just easier for my workflow to work live.
If not, is there an easy way to download or sync the live data to development machine?
Thanks!

TL;DR: We do not support having the dev_appserver use the real app-engine datastore. Even with the suggested use of "remote_api", AFAIK, the dev_appserver does not know how to use it.
If you really want to make this work, you could write your own low-level API and have your own datastore abstraction that uses your API instead of the actual datastore, however this is a non trivial amount of work.
Another option is to have a servlet that can pre-populate your dev datastore with the data you need from checked in files. The checked in raw data could be non-real data or obfuscated real data. At dev_appserver startup, you hit this URL and your database becomes pre-populated with data. If you take this route, you get the bonus of not operating on your live data with dev code.
HTH!

Instead of "touching" live data from the development server I'd recommend downloading a copy of all your production data locally with appcfg.py download_data/upload_data if you wish to move changes from development to production you can explicitly use the same commands to override existing entities.

Related

How to deploy Django app not using Localhost

We have created an app for a production facility that is very simple using django and python. But throughout prototyping we used Runserver command and localhost. The problem is this: We want to deploy the app without using localhost and the command line every time. The people using it wont be able to do this. It will be on implemented on one computer so it shouldnt be that challenging. The app pulls data from one database and stores data in another. It would be nice to have our own URL. Do we need to do it through wsgi? Apache? I know the problem is simple but there seem to be so many ways to deploy and many of them are overcomplicated for our needs.
Follow up question: I read that it just using Localhost isnt the best for this type of thing. Is this true?
Any help would be great
It sounds like you want to deploy the app live. So, I'd recommend using a dynamic hosting service like AWS/Azure/Firebase etc. If you want your own URL, purchase a domain, and in the configuration for the domain set up a CNAME file as well so you can redirect your domain to the live instance on the cloud.
Local host is better used for testing, and making changes without affecting the client and then you deploy/push to the cloud instance for production.

Django cache vs App Engine cache - which one should I use?

I'm running Django (1.5) on App Engine and I need to use some kind of key-value cache. I know App Engine's memcache API and also the Django's cache framework. I wonder which one should I use.
On one hand I would like my code to be as portable as possible for migrating it to another cloud platform. But on the other hand I would like to fully utilize the services offered by App Engine.
Is writing a custom cache backend for Django that will use the App Engine memcache is the best solution?
Tzach, I think you're already answering your question.
Putting your app in GAE and not using the services provided by Google it doesn't look to me as a wise decision, even more, when those features are key for performance at the same time free or very cheap.
On the other hand, the embedded default cache in Python is not guaranteed to give its best results under GAE, as GAE instances are not a normal server where you'd run your django instance, e.g. instances can be shutdown at any time.
These special characteristics found in Django are tuned in the django for GAE versions.
For that reason, and taking into account that using the GAE memcache is also straightforward, I'd recommend you using the easiest ones to add to your application.
And, if in the future, you move to another platform, there will be more things to change than the key-value cache.
My two cents on that is to focus firstly in getting the job done and secondly in optimizing the performance on GAE and only afterwards to start thinking on things to improve.

Google-App-Engine-Like Datastore for Python

Is there any software library that provides an interface for storing and querying data like the Google App Engine Datastore, but uses a local file or service instead of running on App Engine?
The specific features I am looking for are:
Stores data as Entities with Named Properties
Query support
Atomic transactions
Python language bindings
Runs on my local machine
either stores to a single file
or connects to a local database
service
Free and open source
Thanks
You can also check MongoDB. It is an open source document-oriented database system.
You may also want to check out Appscale (http://www.appscale.com). It lets you run your App Engine apps without modification outside of Google (on your laptop, on your local cluster / behind your firewall, or in Amazon EC2). AppScale is and does each of the requirements you list here. It automatically installs/configures/manages the datastore service (and all other APIs/services) for your apps to use, so you don't have to.
Have a look at ZODB - not exactly alike but similiar http://www.zodb.org/
from the docs
Some of the features that ZODB brings to you:
Transparent persistence for Python objects
Full ACID-compatible
transaction support (including savepoints) History/undo ability
Efficient support for binary large objects (BLOBs)
Pluggable storages
Scalable architecture

Migrating Django Application to Google App Engine?

I'm developing a web application and considering Django, Google App Engine, and several other options. I wondered what kind of "penalty" I will incur if I develop a complete Django application assuming it runs on a dedicated server, and then later want to migrate it to Google App Engine.
I have a basic understanding of Google's data store, so please assume I will choose a column based database for my "stand-alone" Django application rather than a relational database, so that the schema could remain mostly the same and will not be a major factor.
Also, please assume my application does not maintain a huge amount of data, so that migration of tens of gigabytes is not required. I'm mainly interested in the effects on the code and software architecture.
Thanks
Most (all?) of Django is available in GAE, so your main task is to avoid basing your designs around a reliance on anything from Django or the Python standard libraries which is not available on GAE.
You've identified the glaring difference, which is the database, so I'll assume you're on top of that. Another difference is the tie-in to Google Accounts and hence that if you want, you can do a fair amount of access control through the app.yaml file rather than in code. You don't have to use any of that, though, so if you don't envisage switching to Google Accounts when you switch to GAE, no problem.
I think the differences in the standard libraries can mostly be deduced from the fact that GAE has no I/O and no C-accelerated libraries unless explicitly stated, and my experience so far is that things I've expected to be there, have been there. I don't know Django and haven't used it on GAE (apart from templates), so I can't comment on that.
Personally I probably wouldn't target LAMP (where P = Django) with the intention of migrating to GAE later. I'd develop for both together, and try to ensure if possible that the differences are kept to the very top (configuration) and the very bottom (data model). The GAE version doesn't necessarily have to be perfect, as long as you know how to make it perfect should you need it.
It's not guaranteed that this is faster than writing and then porting, but my guess is it normally will be. The easiest way to spot any differences is to run the code, rather than relying on not missing anything in the GAE docs, so you'll likely save some mistakes that need to be unpicked. The Python SDK is a fairly good approximation to the real App Engine, so all or most of your tests can be run locally most of the time.
Of course if you eventually decide not to port then you've done unnecessary work, so you have to think about the probability of that happening, and whether you'd consider the GAE development to be a waste of your time if it's not needed.
Basically, you will change the data model base class and some APIs if you use them (PIL, urllib2, etc).
If your goal is app-engine, I would use the app engine helper http://code.google.com/appengine/articles/appengine_helper_for_django.html. It can run it on your server with a file based DB and then push it to app-engine with no changes.
It sounds like you have awareness of the major limitation in building/migrating your app -- that AppEngine doesn't support Django's ORM.
Keep in mind that this doesn't just affect the code you write yourself -- it also limits your ability to use a lot of existing Django code. That includes other applications (such as the built-in admin and auth apps) and ORM-based features such as generic views.
There are a few things that you can't do on the App Engine that you can do on your own server like uploading of files. On the App Engine you kinda have to upload it and store the datastore which can cause a few problems.
Other than that it should be fine from the Presentation part. There are a number of other little things that are better on your own dedicated server but I think eventually a lot of those things will be in the App Engine

Is Google App Engine right for me?

I am thinking about using Google App Engine.It is going to be a huge website. In that case, what is your piece of advice using Google App Engine. I heard GAE has restrictions like we cannot store images or files more than 1MB limit(they are going to change this from what I read in the GAE roadmap),query is limited to 1000 results, and I am also going to se web2py with GAE. So I would like to know your comments.
Thanks
Having developed a smallish site with GAE, I have some thoughts
If you mean "huge" like "the next YouTube", then GAE might be a great fit, because of the previously mentioned scaling.
If you mean "huge" like "massively complex, with a whole slew of screens, models, and features", then GAE might not be a good fit. Things like unit testing are hard on GAE, and there's not a built-in structure for your app that you'd get with something like (famously) (Ruby on) Rails, or (Python powered) Turbogears.
ie: there is no staging environment: just your development copy of the system and production. This may or may not be a bad thing, depending on your situation.
Additionally, it depends on the other Python modules you intend to pull in: some Python modules just don't run on GAE (because you can't talk to hardware, or because there are just too many files in the package).
Hope this helps
using web2py on Google App Engine is a great strategy. It lets you get up and running fast, and if you do outgrow the restrictions of GAE then you can move your web2py application elsewhere.
However, keeping this portability means you should stay away from the advanced parts of GAE (Task Queues, Transactions, ListProperty, etc).
The AppEngine uses BigTable as it's datastore backend. Don't try to write a traditional relational-database driven application. BigTable is much more well suited for use as a highly-scalable key-value store. Avoid joins if at all possible.
I wouldn't worry about any of this. After having played with Google App Engine for a while now, I've found that it scales quite well for large data sets. If your data elements are large (i.e. photos), then you'll need to integrate with another service to handle them, but that's probably going to be true no matter what with data of that size. Also, I've found BigTable relatively easy to work with having come from a background entirely in relational databases. Finally, Django is a somewhat hidden, but awesome, "feature" of Google App Engine. If you've never used it, it's a really nice, elegant web framework that makes a lot of common tasks trivial (forms come to mind here).
Google has just released version 1.3.0 of the SDK with support with a new Blobstore API for storage of files up to 50MB. See the post "App Engine SDK 1.3.0 Released Including Support for Larger User Uploads".
What about Google Wave? It's being built on appengine, and once live, real-time translatable chat reaches the corporate sector... I could see it hitting top 1000th... But then again, that's an internal project that gets to do special stuff other appengine apps can't.... Like hanging threads; I think... And whatever else Wave has under the hood...
If you are planning on a 'huge' website, then don't use App Engine. Simple as that. The App Engine is not built to deliver the next top 1000th website.
Allow me to also ask what do you mean by 'huge', how many simultaneous users? Queries per second? DB load?

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