Mark Pollack discusses Spring XD and its integration driven by the Big Data ecosystem at large such as Kafka, Spark, functional programming, integration with Python, and designer/monitoring UIs.
The authors demonstrate the design and use of an environment for quantitative researchers building a market risk simulation first as a basic system and then adding a hypothetical systemic shock.
Uri Laserson reviews the different available Python frameworks for Hadoop, including a comparison of performance, ease of use/installation, differences in implementation, and other features.
Jessica McKellar introduces Twisted, a Python event-driven networking engine, and explaining several design concepts used: deferred API, transport/protocol separation, and plug-in infrastructure.
Mike Solomon shares some of the experiences and lessons learned scaling YouTube over the years.
Dustin Getz shows writing monads code explaining how they work and why they are useful.
Mark Rendle introduces the basic services offered by Windows Azure along with examples of various platform choices that can be used: RavenDB, ASP.NET MVC, Node.js + Express, MongoDB, Sinatra, etc.
Mike Pirnat presents some tips and tricks, standard libraries and third party packages that make programming in Python a richer experience.
Jeff Lindsay discusses creating distributed and concurrent systems using ZeroMQ – a lightweight message queue-, and gevent – a coroutine-based networking library.
Bruce Eckel emphasizes using different languages within a project, each one for the task it is better fitted for, and giving several such examples: Python+Scala, Go+Python, Python+CoffeeScript.
Graham Tackley discusses how The Guardian switched all new development from Java to Scala, why they did that, what were the benefits and the problems, and why they did not choose Python+Django.
Michael Foord discusses IronPython, the DLR, static vs. dynamic typing, VS.net integration, Resolver One, embedding IronPython, error handling, dynamic operations, and functions as delegates.