Doing IT the App Engine Way
For this article, I'm using Fedora 12. I used to eat, sleep and breathe Red Hat Linux (then Fedora), but like a lot of other Linux users, I was tempted away by the promise and then delivery of a friendlier desktop experience with Ubuntu. As luck would have it, I recently received the latest edition of Mark G. Sobell's book (see Resources), which includes Fedora 12 on DVD. Installation, as expected, was straightforward. However, Fedora 12 comes with Python 2.6 pre-installed, and I needed the 2.5 release.
A feature of Python that I love is that multiple versions of the interpreter can happily co-exist on your system. On my systems (desktops and laptops), I have releases 2.5, 2.6 and 3.1 installed. Only one of these releases is symbolically linked to the /usr/bin/python (usually the 2.6 release), but I can invoke the other releases using one of these command lines:
Deploying release 2.5 of Python on Fedora wasn't an issue. It's the usual tar -zxvf, configure, make and make-install four-step. As expected, the Fedora DVD pre-installed all the development tools required to let me build Python 2.5 from source without any issues.
Unlike technologies, such as Ruby on Rails or Django, which provide a collection of helper scripts to get you up and running quickly, App Engine forces you to do all the work yourself. Thankfully, this is not a huge effort. To demonstrate, let's create a new project with the rather imaginative name, myapp. Create the initial directories and files required in your HOME directory with these commands:
mkdir myapp && cd myapp mkdir templates && touch app.yaml
The above commands create some required directories (more on these later) as well as the main App Engine configuration file: app.yaml. You edit this file to tell App Engine all about your webapp. Add the following configuration directives to your YAML file:
application: myapp version: 1 runtime: python api-version: 1 handlers: - url: /.* script: myapp.py
The application line identifies your webapp, and the value needs to match the name of the directory you just created to house your project. Use the version value to indicate the release of your webapp to which this YAML file refers (this value also is used by Google's cloud to refer to different versions of your webapp, should they exist). The runtime line tells the App Engine for which platform you are coding, and the api-version value indicates what version of the API you are using.
The remaining three lines tell App Engine what to do with any Web requests destined for your webapp. It is useful to think of these handlers in the YAML file as high-level, application “routing directives”. The bit after url is a regular expression that (as all regex gurus will tell you) matches anything that starts with a /, followed by any string (or nothing at all). What's happening here is that any URL received by App Engine on behalf of your webapp is going to be redirected to the script identified on the script> line, which in this case is called myapp.py. At the moment, no such script exists, so let's fix that.
To demonstrate how an App Engine webapp is put together, let's build a simple Web page that lets users submit their e-mail addresses with a message. These two pieces of data are stored in the Google cloud. A second page displays the e-mail addresses and messages on-demand. Granted, this isn't a hugely exciting webapp, but it's enough to demonstrate the basics of the technology and for you to get started with something “real”. Of course, it is possible to build this using App Engine's CGI mechanism (which works exactly as you would expect), but as this application is destined for greatness, let's code to Python's WSGI standard instead. Let's also build the webapp to conform to the MVC pattern.
As you plan to store some data in this webapp, you need somewhere to put it, which means you need a model. App Engine provides an API to Google's “cloud” datastore. All you need to do is define a Python class that inherits from db.Model, then create the required data fields. For the webapp, you need a field for the e-mail address and the associated message. To keep things manageable, let's put your model code in its own file, called myappDB.py:
from google.appengine.ext import db class UserComment(db.Model): cust_email = db.StringProperty() cust_message = db.TextProperty()
There's not much to this model code. It simply imports the db module from App Engine, creates a new class called UserComment and creates class instance variables for each data field. As App Engine's StringProperty type is limited to 500 bytes, you need to specify TextProperty for the user message, just in case someone has a lot to say.
With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide
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- Updates from LinuxCon and ContainerCon, Toronto, August 2016
- New Version of GParted
- What I Wish I’d Known When I Was an Embedded Linux Newbie
- NVMe over Fabrics Support Coming to the Linux 4.8 Kernel
- Tor 0.2.8.6 Is Released
- All about printf
- Downloading an Entire Web Site with wget
- Blender for Visual Effects