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The common wisdom is that Python is slow. And yet people run high performance software on it. It's hard to make Python fast, and yet there are incredibly high performance Python VMs. This talk breaks down the facts and the myths of Python performance.
You may have encountered the pickle or cPickle libraries, and used them to persist some state about your program. But how do they work? This talk explores how the pickle protocol works, what its advantages are, and its disadvantages
Open source software powers the world. But it defies a lot of conventional expectations about how people organize and innovate. This talk will explore the psychology, sociology, and economics of open source, and how we come together to effectively build things.
Classifying what type of job programmers do can be a challenge. Are we engineers? Are we scientists? Craftspeople? Something else entirely? Are software engineers, software developers, software architects, and programmers all really the same thing? This talk explores the nature of our work, and its relationship to the scientific method, including a dive into epistemology.
You're a programmer, you use interpreter and compilers every day (and twice on Sundays!). But how do these things work? Could you build one yourself? What would it take? Where would you start? This talk takes you through the process, from lexing to interpreting, and leaves you ready to start on your own language!
Django has always had a strong commitment to backwards compatibility, and is used by thousands of developers every day. This means that it's very difficult to make large sweeping changes to Django. This talk is a look at how I'd redesign different components of Django, if I got to do it all over again.
One of the goals of PyPy is to make existing Python code faster, however an even broader goal was to make it possible to write things in Python that previous would needed to be written in C or other low-level language. This talk will show examples of this, and describe how they represent the tremendous progress PyPy has made, and what it means for people looking to use PyPy.
For many applications PyPy can provide performance benefits right out of the box. However, little details can push your application to perform much better. In this tutorial we'll give you insights on how to push pypy to it's limites. We'll focus on understanding the performance characteristics of PyPy, and learning the analysis tools in order to maximize your applications performance.
Python has a reputation for being a bit slow, but it doesn't have to be that way. This talk will cover why Python is slow, and what two of the most exciting virtual machines are doing about it.