Stefan Karpinski - Julia + Python = ♥

PyData NYC 2014
Julia is a new language for scientific computing, which combines the high-level abstractions and dynamic interactivity of languages like Python with the performance of low-level languages like C. It has been gaining traction as a faster alternative to NumPy, Matlab or R, and as a more productive alternative to C or C++. Julia is particularly relevant when both expressiveness and performance are paramount – in areas like machine learning, “big statistics”, data mining and linear algebra. But a major challenge for any young programming language is the lack of a large ecosystem of mature libraries and tools. To overcome this difficulty, Julia is “bootstrapping” off of the Python ecosystem, both by making it easy to call Python code and also by exploiting infrastructure such as IPython/Jupyter. Since it would be rude to take and give nothing back, we've also made it possible to call Julia libraries from Python, allowing Julia to be (yet) another alternative when CPython isn't quite fast enough. This talk will be full of live coding, with all the fun and tantalizing possibility of disaster that entails. 00:00 Welcome!
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