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Behind the Scenes of the Wave API Python Client Library

When I heard that Australia was going to have its very own PyCon, I knew I wanted to give a talk. While working on the with the Wave APIs over the last year, I've gotten to the point where I'm using the Python client library on a daily basis, and I've learnt a lot about Python from our library. I wanted to give a talk that would be interesting both to Wave API developers and to Python developers and would force me to dig deeper into the depths of our client library.

So, I presented a talk called "Wave Robots API: Behind the Scenes", with the goal of showing how we used Python to abstract on top of our HTTP API. I started with an overview of Google Wave and a quick look at Wave's core technology — the conversation model and operational transformation algorithm — so that everyone in the room would be comfortable with me talking about blips, wavelets, operations, and the like. Then I went deep into the robots API, explaining the JSON-RPC protocol between the Wave server and robots, and showing how the Python client library serializes the JSON into Python objects, how it lets developers register for events, and how it signs outgoing requests using OAuth. I then explained how we designed the client library to be hosting-provider-agnostic, and live demoed a robot that I created using the Django framework on a slicehost node. I finished with a summary of the most important features of the client library — versioning, automation, authentication, flexibility, and being Pythonic.

But, hey, if all that sounds interesting to you, you don't have to read about it -- you can watch it! Check out the video here, and the slides here. If you have any questions after watching, just head over to our Google Wave API forum.

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