Friday, April 18, 2014

Django debug server Windows service

I hijacked tracservice.py from Trac-Hacks to do the same for Django. It's long and rambling but gets the job done.
It's in this Gist: It was working on my Windows-7 machine, but I changed trac --> django everywhere in the source, so I might have broken something, so please let me know if you find any problems.

Thursday, April 17, 2014

Fix vcvarsall.bat to install Python-2.7 x64 extensions with v90 instead of sdk7

[UPDATE 2014-11-13] Free x86 and AMD64 (x86-64) VC90 c-compilers for Python-2.7 are now available from Microsoft. The free VC90 compilers can be used to install package source that contains c-extensions using either pip, setuptools or distutils. For example, pip install dulwich will build and install the Python Git implementation which contains several speedups as c-extensions.

Previously in order to install Python-2.7 packages with extensions on my 64-bit Windows-7 machine, I have been using the Windows SDK-7 shell and setting the target and some environmental variables manually. What a drag! Then a few days ago, I discovered that the reason vcvarsall.bat has been complaining that it can't find my x64 compilers, even tho they are right there in my Visual Studio 2008 VC folder is because the path the the batch file that sets up the environmental variables for the x64 compiler was wrong. In fact all of the paths were wrong except for vcvars32.bat.

I posted a patch in this Gist:

Now to install packages that include extensions, EG: Dulwich, I just use pip install -U dulwich and easy peasy!

Thursday, April 3, 2014

My fears about MATLAB

Someone just sent me a funny email about funny MATLAB bugs. When I say "funny" I mean in the geeky-(in fact I didn't even get why they were so funny)-way. I probably was targeted for this funny email thread because I have suggested switching from MATLAB to Python, but I think my reasons for suggesting this switch have been misunderstood. It doesn't have anything to do with bugs or the quality of MATLAB software - IMHO MATLAB is outstanding. My complaint is more practical. I am afraid of the consequences of the facts that MATLAB is closed-source and TMW is privately held. I hope that this perspective is useful, however what I express below is my opinion and based on my experiences not necessarily on facts, so please forgive me if there are some inaccuracies.

Here are my fears about MATLAB enumerated, and why I suggest switching to Python:

  1. If MATLAB goes out of business, your code is useless, and they could decide to close shop any day, because they’re not publicly traded.
  2. You can’t use it without a license! In my case I have to VPN to work to use it, this makes me not want to work from home because using vpn is just a smidge slower and another hurdle to getting started and of course forget working on airplanes or anywhere where there’s no internet.
  3. The $$$ for the toolboxes is obscene! Especially considering they are repackaging what is already free in the public domain in C/C++, FORTRAN and Python. It’s a racket. Ostensibly you could argue that the money is for support, but there are similar paid support options for Python (Anaconda, Enthought, ActiveState, etc.) that are substantially cheaper, and rival MATLAB support options to varying degrees of success.
  4. MATLAB is not portable, unless of course you use the MATLAB compiler toolbox and one of its toolbox add-ons like MATLAB builder-NE, builder-JA or builder-XL. That right there floors me as a scam, you can’t port it to someone unless you buy not one but 2 extra $$$$$ toolboxes and they are by far the most expensive toolboxes! And that’s the way it is with everything they sell. EG parallel toolbox is useless without the extra distributed computing toolbox, both of which are $$$$$! And you pay per number of machines in the computing cluster. Back to portability. If you want to share your MATLAB code with someone they will have to purchase MATLAB to use it.
  5. There is not enough consideration for backwards compatibility. I believe that TMW tries to minimize backwards incompatibility, but they still do it anyway, and in their business model, where they only make money if you maintain your license, they have a strong incentive to introduce backwards incompatibility. Other languages have the opposite incentive, in order to maintain the code-base of external packages, libraries and toolboxes that would fail if backwards incompatibilities were introduced. IE you will never find backwards incompatibilities between any version of Python-2.7.x (or in between versions of Python-3.x.x, although Python-3 is not strictly backwards compatible with Python-2).
  6. It is very powerful, but it is not the most powerful coding platform out there. FORTRAN as ancient as it is, still exceeds MATLAB and the newer Julia is faster than them all! See the comparison chart where is says “High-Performance JIT Compiler”.

Other than these few issues, I revere MATLAB and have used it extensively for decades. I rarely have issues with it and it is clearly one of the best analysis tools for science and engineering, but it isn’t the only one and it’s debatable if it’s the best.

I adhere to the philosophy of "use the right tool for the right job" and that nothing is binary, even quanta come in different flavors.
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