Skip to main content

Google App Engine at the Utah Open Source Conference

App Engine is probably the biggest thing to happen to Python this year, so of course I volunteered to give a presentation on it at at the Utah Open Source Conference. (I'm scheduled for Friday, Aug 29, at 10:00 AM.) Last year's conference was a big success, so I'm looking forward to an even better experience this year.

Here's the abstract I submitted, before they blew away my paragraph breaks:

Google launched the App Engine service earlier this year to immense interest from the web development community. App Engine allows running applications on Google infrastructure, including BigTable, Google's non-relational, massively scalable database.

App Engine is appealing both at the low end, where small shops don't want to have to deal with hardware procurement and systems administration, and at the high end, where the kind of "instant scaling" App Engine promises to deal with bursty traffic is the holy grail of infrastructure planning. This tutorial will cover the basics of App Engine development, including development and deployment of a simple application.

Please sign up for an App Engine account and download the SDK ahead of time so we can jump right in to the code. Basic Python knowledge will be assumed.

After I submitted the proposal, I found out that all presentations are going to be 60 minutes long. That is not much time if we're going to do hands-on work, but you retain so much more by doing than you do merely from watching that I don't consider it optional. So seriously, come with the SDK installed. Those who do not, can look over the shoulders of those who do.

If you don't know Python and you're a last minute kind of person, you might want to attend Matt Harrison's talk the day before, 90% of the Python you need to know. Matt has presented several times at the Utah Python User Group as well as PyCon.

Bonus tip: if you can't make it to the UTOSC, the two best talks on App Engine are Rapid Development with Python, Django, and Google App Engine and Building Scalable Web Applications with Google App Engine. My presentation will cover similar material to the first of these.

Comments

Popular posts from this blog

The Missing Piece in AI Coding: Automated Context Discovery

I recently switched tasks from writing the ColBERT Live! library and related benchmarking tools to authoring BM25 search for Cassandra . I was able to implement the former almost entirely with "coding in English" via Aider . That is: I gave the LLM tasks, in English, and it generated diffs for me that Aider applied to my source files. This made me easily 5x more productive vs writing code by hand, even with AI autocomplete like Copilot. It felt amazing! (Take a minute to check out this short thread on a real-life session with Aider , if you've never tried it.) Coming back to Cassandra, by contrast, felt like swimming through molasses. Doing everything by hand is tedious when you know that an LLM could do it faster if you could just structure the problem correctly for it. It felt like writing assembly without a compiler -- a useful skill in narrow situations, but mostly not a good use of human intelligence today. The key difference in these two sce...

Why PHP sucks

(July 8 2005) Apparently I got linked by some PHP sites, and while there were a few well-reasoned comments here I mostly just got people who only knew PHP reacting like I told them their firstborn was ugly. These people tended to give variants on one or more themes: All environments have warts, so PHP is no worse than anything else in this respect I can work around PHP's problems, ergo they are not really problems You aren't experienced enough in PHP to judge it yet As to the first, it is true that PHP is not alone in having warts. However, the lack of qualitative difference does not mean that the quantitative difference is insignificant. Similarly, problems can be worked around, but languages/environments designed by people with more foresight and, to put it bluntly, clue, simply don't make the kind of really boneheaded architecture mistakes that you can't help but run into on a daily baisis in PHP. Finally, as I noted in my original introduction, with PHP, ...

A week of Windows Subsystem for Linux

I first experimented with WSL2 as a daily development environment two years ago. Things were still pretty rough around the edges, especially with JetBrains' IDEs, and I ended up buying a dedicated Linux workstation so I wouldn't have to deal with the pain.  Unfortunately, the Linux box developed a heat management problem, and simultaneously I found myself needing a beefier GPU than it had for working on multi-vector encoding , so I decided to give WSL2 another try. Here's some of the highlights and lowlights. TLDR, it's working well enough that I'm probably going to continue using it as my primary development machine going forward. The Good NVIDIA CUDA drivers just work. I was blown away that I ran conda install cuda -c nvidia and it worked the first try. No farting around with Linux kernel header versions or arcane errors from nvidia-smi. It just worked, including with PyTorch. JetBrains products work a lot better now in remote development mod...