Some weekend miscellanies on my Airbook.
A coupe of weeks ago, I installed the binary distribution (1.8.2) of Pandoc. The binaries are installed in
/usr/bin, while the older ones were in
~/.cabal/bin/. To test my installation, I used a fairly basic document with some $\LaTeX$ expressions, references, and code chunk with or without syntax highlighting (because the latest version of Pandoc added support for the R programming language). Here is the test document.
For unknown reason, the citation mechanism via
citeproc-hs (0.3.3) was broken because of an hard-coded path, as described in this issue. So, I decided to reinstall Pandoc with
cabal as I did before. (This time I had no problem with
cabal, though.) So basically,
$ cabal update $ cabal install cabal-install $ cabal install highlighting-kate --disable-library-for-ghci $ cabal install citeproc-hs $ cabal install pandoc -fhighlighting
And voilà! I should note that a lot of warnings were issued when building the packages, like
ld: warning: text reloc in
This has been referenced on Ticket #5128, and it led me to suspect that I rather need to update my entire Haskell system. Well, that was quick and easy with the Frameworkized version available on http://hackage.haskell.org/platform//mac.html.
Next to that, even if I didn’t get any problem compiling a sample demo program, it throws out some warnings (see partial output below):
$ echo "main = return ()" > Main.hs $ ghc --make Main [1 of 1] Compiling Main ( Main.hs, Main.o ) Linking Main ... ld: warning: could not create compact unwind for _ffi_call_unix64
Here is a preview of the HTML version of the test document, with working references, syntax highlight and $\LaTeX$ support. (The commands I used were:
pandoc pandoc_text.md -s -m --bibliography="ml_dysp.bib" -o 1.html.)
Ah, remember to never install so-called “superpack”, you know the
pkg that is supposed to do everything for you (like the scipy-superpack) . Note that I don’t want to denigrate all the efforts made by the maintainers (and for what is worth, maintaining working package on a Mac is a challenging task!), but the problem I have with that approach is that you never know what is installed or whether it will break what you already installed by hand. In my case, I decided to give a try to SimpleCV. I dont’t know why but instead of a simple
easy_install simplecv, I choose the packaged binary. As can be seen, a lot of stuff is installed directly in /usr/local`.
There were so many problems with that install (notwithstanding the fact that it targeted Python 2.6, while Python 2.7 is now the default under OS X Lion) that I decided to reinstall everything, that means:
cudasupport (I had problems when compiling and wanted to get it the easiest way, i.e. not reintalling too much things).
At present, most of the demos scripts are working, including face tracking with Airbook built-in camera. I will probably have to tweak the install a little bit in the future. But that’s another story…