I couldn't agree more. This is related to another recent HN posting (<a href="http://news.ycombinator.com/item?id=3104598" rel="nofollow">http://news.ycombinator.com/item?id=3104598</a>) and discussions at PyCodeConf in Miami. There's a general feeling (which I've experienced in many of my interactions with non-scientific Python programmers) that the folks working on pure Python don't really "get" the scientific Python community. We would all understand each other better if the PyPy folks or the Python core developers spent a year, say, working at Enthought on scientific Python consulting projects or working on a core project that uses NumPy/SciPy like scikit-learn, matplotlib, statsmodels, theano, pandas, or many, many others. A small annoyance but having a matrix multiplication infix operator would actually be a huge help but the idea has met a great deal of resistance from core Python as being "too domain specific". It strikes me as very short-sighted as I think Python is well-poised to make waves in the data analysis, statistics, and high performance computing ecosystem. Having used Python to build large systems for financial applications, I am acutely aware of how Python is being used in that industry and some of the ways that it needs to adapt to be more relevant. So bravo, Travis, for speaking up!<p>Also, his point that Cython (<a href="http://cython.org" rel="nofollow">http://cython.org</a>) tends to be ignored in the broader discussion about performance computing in Python is especially flagrant when you consider how it's revolutionized the way that scipythonistas (myself included) speed up their code over the last 2-3 years.
> There were a lot of young people there who understood a lot more about making web-pages and working at cool web start-ups than solving partial differential equations with arrays.<p>I can especially relate to this, even though I'm 26. Admittedly, I work in a microcosm though, where I'm the youngest, least educated and least experienced in my group, despite having a BS in Physics and 4 years research in particle astrophysics.<p>Luckily we do a little less with matrix operations, but I agree that Python, specifically PyPy, has so much potential to be the scientific computing standard and that the python community should really push for it. In a world with less python, there's so much pain involved on a regular basis setting up software like ROOT, switching between libraries of FFTs or plot libraries, installing Octave or Matlab to work nice with some bash script and dealing with OS discrepancies in getting someone else's code to run. It sucks.<p>If PyPy can displace that with near-C performance, the world would be a much better place.
I love it when someone writes an articulate, non-inflamatory blog post with reasonable suggestions on how to improve things. It's sad how rare this is around here these days.
I just don't see adding a special matrix infix operator to Python happening. It is too specialized, and yet matrix is not special enough that it must have its own operator. Isn't this what operator overloading is for?<p>I suspect the real problem is NumPy's type system implementation, since data-types are not visible as different Python types.
If numpy-c were to be called over ctypes, it'd be slow.The reason PyPy's numpy reimplementation is so insanely fast is the integration with the JIT.<p>A more plausible scenario would be both CPython and PyPy using numpy-py to call into numpy-c and numpy-pypy respectively.
Off-topic but anyone else seeing every instance of "fi" in the text replaced with a slightly overlapping AV? (I tried to cut and paste it but it pasted as just "fi").<p>I'm on Ubuntu Ocelot & Firefox 7.<p>nevermind: I'm seeing it on various websites that use ligatures. Possibly because I'm half-way through an Ubuntu upgrade.
I was going to do a Cython lightning talk, but the organizers indicated that we ran out of time slots, so I could only give one talk. Half of the audience at PyCodeConf indicated they were aware of the Cython project, although perhaps it would have been useful regardless...