Posts Tagged → booleano

Koren’s SVD++ Python Implementation

I recently had to implement a recommender system for the Netflix Prize. Out of the best known models, I chose Yehuda Koren’s SVD++ model as published on the paper entitled “Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model” (the version that doesn’t take into account temporal effects; I’d have implemented the complete model, but couldn’t due to time constraints).

I named this Python-based project “wooflix” and you can download it from code.gustavonarea.net. It ships with a command-line interface and basic documentation, including the design document.

It’s the first project, as far as I know, that uses Booleano. With it, you can get random movie recommendations and filter them, like this:

# Get 5 movie recommendations for user #7, at least those published after 2001
wooflix recommendations 7 --max="5" --filter="movie:year > 2001"

Keep in mind that I won’t offer support for it; I’m publishing because I thought it might be useful for some people, but I have no intentions to work on it in the future.

Announcing Booleano

I am proud to announce the first alpha release of Booleano, a Python-based interpreter of boolean expressions:

Booleano is an interpreter of boolean expressions, a library to define and run filters available as text (e.g., in a natural language) or in Python code.

In order to handle text-based filters, Booleano ships with a fully-featured parser whose grammar is adaptive: Its properties can be overridden using simple configuration directives.

On the other hand, the library exposes a pythonic API for filters written in pure Python. These filters are particularly useful to build reusable conditions from objects provided by a third party library.

It’s been designed to address the following use cases:

  1. Convert text-based conditions: When you need to turn a condition available as plain text into something else (i.e., another filter).
  2. Evaluate text-based conditions: When you have a condition available as plain text and need to iterate over items in order to filter out those for which the evaluation of the condition is not successful.
  3. Evaluate Python-based conditions: When you have a condition represented by a Python object (nothing to be parsed) and need to iterate over items in order to filter out those for which the evaluation of the condition is not successful.

It is a project I found necessary while working on repoze.what 2, which I’ve been developing for the last few months in my spare time. This release is absolutely usable, but lacks documentation because I needed this release out for a (small) project I need to work on ASAP (it will depend on Booleano). The next release will ship with a nice documentation, I promise.