Skip to main content

The best PyCon talk you didn't see

There were a lot of good talks at PyCon but I humbly submit that the best one you haven't seen yet is Robert Brewer's talk on DejaVu. Robert describes how his Geniusql layer disassembles and parses python bytecode to let his ORM turn python lambdas into SQL. Microsoft got a lot of press for doing something similar for .NET with LINQ, but Bob was there first.
  box = store.new_sandbox()
print [c.Title for c in box.recall(
  Comic, lambda c: 'Hob' in c.Title or c.Views > 0)]
This is cool as hell. The Geniusql part start about 15 minutes in.

Comments

Unknown said…
Erlang has had this for a very long time too, at least for Mnesia databases, e.g. Mnemosyne and later QLC. Cool stuff :)
Jason Baker said…
Hah! I proved you wrong. I did see that talk. Shows you.

Seriously though, I've been meaning to try dejavu out for a while and this gives me new impetus to give it a shot.
Rob De Almeida said…
I did something similar: a DB API wrapper that parses the source code to build the SQL:

http://pypi.python.org/pypi/simpleQL

The only problem is that it doesn't work on an interactive session, since it needs to read the source code.
Unknown said…
I liked it a lot, too. I haven't yet had time to figure out if I want to use DejaVu in general, but the principle is a great one: why make people learn a new syntax for something (like filtering rows) when they already know a perfectly good syntax for it?

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...