“Project A: Resilient and Rapid Raspberries” is Group Design Practical set by the Department of Computer Science at the University of Oxford in the academic year 2012/2013. OxBerryPis is an implementation of the practical maintained by 4 university students (Group 8).
In today’s world of high frequency trading, understanding the rapidly changing quotes from a myriad of trading algorithms is a colossal data processing problem. With tens of thousands of updated per second in a single market, and limited space and power constraints, it is important to be able to maximise throughput and resiliency with the hardware available. Given a day of actual stock exchange data, your challenge is to create a cluster to process and aggregate the data. Doing this with real hardware is more fun - we can’t give you our data centre, but we can suppy you with a Raspberry Pi cluster.
The idea of the project is that, given a day of stock exchange data, we must parse it to retrieve the useful information, consisting of buying, selling, and various trade orders. This will then be sent to the cluster of Raspberry Pis that we have, which will maintain a data structure called the Order Book, which will keep track of the various offers to buy and sell for different prices, how many of each stock are being sold, and allowing the trades to occur according to the data given, maintaining the order book and keeping it up to date. From this, certain data will be sent back to the computer, which will then implement some visualisation so as to show various things about each product, such as last trade price, various medians, and so on. An optional suggestion from GResearch was to implement high availability in the cluster, so as to allow the pis to redistribute the work if one or more were to fail, without data loss.
Firstly, install the package with all the dependencies in the development mode:
python setup.py develop
You may want to use virtualenv if you don’t want to pollute your operationg system’s Python distrubution.
Then introduce your changes and run all the tests:
python setup.py nosetests
Please follow the guidelines from PEP8 (4 spaces for indentation!). If still in doubt, apply the coding style from the master branch. Remember to include appropriate tests for new modules.