I just found out that Python 2.5 or newer allows relative imports, something I had been writing custom code to work around. Python documentation gives examples in 3 forms:
from . import echo
from .. import formats
from ..filters import equalizer
pip is an alternative to easy_install where you can install and upgrade python packages easily with commands like:
pip install -U ipython
Fabric facilitates deploying code to a remote location.
virtualenv lets you setup and manage working environments that aren’t littered with everything you ever installed into your global site-packages directory.
I also recommend virtualenvwrapper, which puts a nice interface on top of virtualenv.
After visiting the Ophthalmologist yesterday, I received a prescription
for corrective lenses with some crazy numbers on it. It looked something
like this:
It turns out that this is a precription for distance vision only (near
vision corrections are usually not necessary for a 25-year-old).
What are the abbreviations?
O.D. abbreviates oculus dexter, Latin for “right eye”
O.S. abbreviates oculus sinister, Latin for “left eye”
SPH stands for spherical diopter units
CYL stands for cylindrical diopter units
AXIS defines the angle of the CYL correction in degrees
The spherical component is the main correction as it acts equally to
correct blur in all directions. The cylindrical component corrects blur
in only one direction — therefore it is useful in correcting
astigmatism. The axis angle defines the direction of the necessary
cylindrical correction.
I implemented numpyIO.py because I often use scipy.io.numpyio.fread() and scipy.io.numpyio.fwrite(), but I don’t want to depend on scipy. It uses numpy’s tofile/fromfile functions instead.
Why might you want this instead of SciPy’s numpyio? Well, I can think of a few reasons:
it imports faster because it only depends on numpy, not scipy
easier to package with py2exe or py2app
it is slightly faster
it lets you avoid rewriting legacy code that makes extensive use of scipy’s deprecated fread/fwrite
cd ~/tmp
wget http://www.python.org/ftp/python/2.6.1/Python-2.6.1.tgz
untar Python-2.6.1.tgz
cd Python-2.6.1
mate Mac/README
./configure --enable-framework
make
make install
cd ..
Update setuptools so that easy_install works.
wget http://pypi.python.org/packages/2.6/s/setuptools/setuptools-0.6c9-py2.6.egg
sh setuptools-0.6c9-py2.6.egg
Add the following to my .profile so that the binaries installed by easy_install take precedence over my old Python 2.5 stuff.
Do the slightly tougher installs: NumPy (svn rev 6271), SciPy (svn rev 5300), matplotlib, and euclid. See http://www.scipy.org/Installing_SciPy/Mac_OS_X for details. Before starting, I also updated to the latest apple developer tools, although this isn’t strictly necessary.
wget http://r.research.att.com/gfortran-4.2.3.dmg
open gfortran-4.2.3.dmg # install using GUI
wget http://www.fftw.org/fftw-3.2.tar.gz
untar fftw-3.2.tar.gz
cd fftw-3.2
./configure
make
sudo make install
cd ..
svn co http://svn.scipy.org/svn/numpy/trunk numpy
cd numpy
python setup.py build
python setup.py install
cd ..
svn co http://svn.scipy.org/svn/scipy/trunk scipy
cd scipy
python setup.py build
python setup.py install
cd ..
python
>>> import numpy
>>> numpy.test('1','10') # 6 problems in 1897 tests, but usable
>>> import scipy
>>> scipy.test('1','10') # 168 errors of 3990 tests, but usable
sudo port install libpng
sudo port install freetype
easy_install matplotlib
ipython -pylab
>>> plot([1,2,3])
svn checkout http://pyeuclid.googlecode.com/svn/trunk/ pyeuclid
cd pyeuclid
python setup.py install
cd ..
Install wxPython and PythonCard for GUI development.
wget http://downloads.sourceforge.net/wxpython/wxPython2.8-osx-unicode-2.8.9.1-universal-py2.6.dmg
wget http://downloads.sourceforge.net/wxpython/wxPython2.8-osx-docs-demos-2.8.9.1-universal-py2.6.dmg
open wxPython2.8-osx-unicode-2.8.9.1-universal-py2.6.dmg
open wxPython2.8-osx-docs-demos-2.8.9.1-universal-py2.6.dmg
wget http://prdownloads.sourceforge.net/pythoncard/PythonCard-0.8.2.tar.gz
untar PythonCard-0.8.2.tar.gz
cd PythonCard-0.8.2
python setup.py install
open /Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/PythonCard/samples/minimal/
Then, Ctrl-click and open minimal.py with Python Launcher to test.
Set good “don’t mess with my line endings” option before first checkout:
git config --global core.autocrlf false
Do this one time to suck in the repo w/history from SVN:
git svn clone svn://myrepo.com/project/
Do this loop over and over until your code ready to push back to SVN. The cool thing about this is that the adds and commits can be done off the network! Don’t forget to merge and re-test your changes after the rebase:
git add .
git commit -m "Added some awesome stuff"
git svn rebase
Push all local changes back to the SVN repo, which will now have all the local commits you did when you were on the airplane:
git svn dcommit
One other key tip is what when you want to decommit or rebase but you are in the middle of some changes, don’t worry. git-stash to the rescue:
git stash
git svn rebase
git stash apply
Also, here are a few links that inspired this post:
I’ve been working more with git lately and have found a few more interesting sites I’d like to share.
The Git Community Book is a great quick reference for finding out how to use a command if you can’t recall from the man page.
If you want to really understand the gory details of branching and merging with git (and I do highly recommend understanding them … easy branching is the best part of git coming from a svn background), then read this long article on LWN.net.
Also, R. Tyler Ballance has a series of blog entries on moving his team from subversion to git. I especially liked Team Development with Git which details the bad habits of developers that are just becoming familiar with distributed source control.
The Battery Powered blog tells us how to deploy a Git Repository Server in Ubuntu, which may prove useful soon. Currently, I’m just using Git for my local work and then pushing to a SVN repo, but I’d like to move others to Git soon.
Amanda and I are running the Chicago Marathon this year. We’re hoping our friends will want to come watch us run on Sunday, October 12!
We are running as part of a fundraising group that supports the Chicago Children’s Memorial Hospital. So, Amanda made a fun video showing her unique Rocky Balboa training methods.
Anyway, hope you enjoy the video. If you like it and want to sponsor us, head to Amanda’s donation site and make a pledge to support her. Or, you can pledge to support me here.
I helped put together a simple website and RSS feed of Haiku published by Bronze Man Books. Read the announcement or check out today’s haiku of the day!
Check out GPULib from Tech-X Corp. It gives you the ability to run mathematical functions on your GPU card (certain NVIDIA models only, as the moment). Includes a blog and bindings for Python (pystream) and MATLAB.
Today is becoming python link day, so here are a few more:
Idiomatic Python has some great tips on how to use python as it was intended.
The Python Package Index is a good place to look for code someone has already written that might solve the problem you’re thinking about, and probably in a much cleaner way than you were thinking. This used to be known as the Cheese Shop.
pyeuclid is a nice 2D/3D vector, matrix, and quaternion math library (that needs better docstrings and a ray-sphereoid intersection).
Straight-forward Python reference the explains the standard library rather completely and cleanly just by showing a simple example for each module and function. Very nice for a quick lookup of something you don’t quite remember.
Because it obscures the nice Leopard python that includes Numpy and Dtrace, remove your old Python completely.
sudo rm -rf /Library/Frameworks/Python.framework/
Check that NumPy is already installed and working.
python
import numpy
numpy.test(1,10)
Install latest IPython, version 0.8.2. Note that I always alais untar='tar xvzf' in my bash setup.
wget http://ipython.scipy.org/dist/ipython-0.8.2.tar.gz
untar ipython-0.8.2.tar.gz
cd ipython-0.8.2
sudo python setup.py install
Install a fortran compiler binary because it is needed to compile/install Scipy. I get the PPC version of gfortran. You can also find the Intel version at HPC Mac OS X.
wget http://internap.dl.sourceforge.net/sourceforge/hpc/\
gfortran-ppc-leopard-bin.tar.gz
sudo tar -xvf gfortran-ppc-leopard-bin.tar.gz -C /
Edit a disttools file in Apple’s NumPy distribution so it is more lenient in allowing the use of the above gfortran compiler when building SciPy. Inspired by this note.
cd /System/Library/Frameworks/Python.framework/Versions/2.5/\
Extras/lib/python/numpy/distutils/fcompiler
sudo cp -p gnu.py gnu.py.bak
And edit the following lines as follows (I use mate gnu.py to edit in TextMate).
