2019-09-05 –, Track 2 (Baroja)
PyPy, the fast and compliant alternative implementation of Python, is now compatible with the SciPy ecosystem. We'll explore how scientific programmers can use it.
PyPy is a fast and compliant implementation of Python. In other words, it's an interpreter for the Python language that can act as a full replacement for the reference interpreter, CPython. It's optimised to enable efficient just-in-time compilation of Python code to machine code, and has releases matching versions 2.7, and 3.6. It now also supports the main pillars of the scientific ecosystem (numpy, Cython, scipy, pandas, ...) thanks to its emulation layer for the C API of CPython.
Performance is a major concern for Python programmers. When using CPython, this leads to splitting out the performance-sensitive parts of the computation and rewriting them in a faster, but less convenient, language such as C or Cython. With PyPy, there is no need to choose between clear, Pythonic code and good performance. This talk aims to convince the audience that PyPy should be part of every scientific programmer's toolbox.
Why PyPy should be part of every scientific programmer's toolbox
Python Skill Level –professional
Domain Expertise –some
Domains –General-purpose Python
I'm an open-source developer and consultant. I've been working on PyPy since 2012, with particular focus on the RPython annotator, Python 3 features, and cpyext.