PyConUY 2013 contest
We use Python in a large portion of our projets and we wanted the PyConUY attendees to know about it.
The objective is simple, create a Python library to ease the usage of our REST-ish speaker voice recognition API documented in docs/api.rst. There is also a live demo using this very same API accesible by telephone at +598 27123142 (instructions are in Spanish).
The version of this public webservice only supports male/female gender recognition, so the coding task should not be too hard nor long. To get you started, you can check out the very basic client example at example/gender.py.
The rules are simple, you spend a bit of time coding, we got to choose the one we like the most. Only open licensed software is allowed to be used and you can team up with as many developers as you like.
We watch out for, but not limited to:
- Automated tests.
- How functionally complete the library is.
- The right degree of abstraction.
- Documentation, usage of a framework for this end is a plus.
- PEP8 complaint code.
- Few dependencies.
- Reported API bugs thru this repository Issue system. This includes documentation errors.
How to participate
Fork this repo and issue a "pull request" before November 10th. Keep an eye for updates to this README and API documentation.
The prize -besides the glory- is a Lenovo IdeaTab A2107 tablet.
We'll make a decision on November 18th and announce the happy winner right here in this file.
Just git pull the results.
There were two PRs.
marcelor reported several issues, and the library was documented using Sphinx, which we love. The code was functional and quite easy to follow, yet it introduced some concepts as endpoints which weren't that much natural for us. Also, no audio file handling was included, which we would like to be included as this is a big part of the API usage.
Let's talk about tooxie's work now. We loved the level of abstraction of his library, it was well balanced, and included test suites. The code was extremely well documented, but lacked auto-generated documentation, that we would have appreciated. However, good documentation and usage examples where supplied, so it was easy to follow the code and understand how the library worked.
No submission was 100% PEP8 compliant but tooxie's was by far the most rigorous in that matter. This submission also had automatic audio file handling, including automatic conversion, which is fantastic feature to have. tooxie also reported a couple of issues via github.
We found tooxie's version the most pythonic and functionally complete, and that's why we choose it as the winner.
Congratulations to both and thank you very much for your submissions.