Some random notes on my recent ‘pythonic peregrinations’ on my Airbook.
Python packages management is really painful. My
/Library/Python/2.7/site-packages is just a mess. This is probably due in part to the fact that I switched from
pip two years ago, but anyway there's a lot of useless stuff in there.
I heard about Bokeh, a new plotting library for Python. Basically, it ought to embed Wilkinson's Grammar of Graphics into the d3js framework. It is maintained by the same guys from Continuum Analytics who develop Blaze and Anaconda. In contrast to Enthought EPD,1 it is
completely free enterprise-ready Python distribution for large-scale data processing, predictive analytics, and scientific computing.
I followed the instructions to install Anaconda, and it is quite simple actually: You just have to
sh Anaconda-*.sh and you should end up with something like:
installing: anaconda-1.4.0-np17py27_0 ... Python 2.7.3 :: Continuum Analytics, Inc. creating default environment... installation finished. You may wish to edit your .bashrc or prepend the Anaconda install location: % export PATH=/Users/chl/anaconda/bin:$PATH Thank you for installing Anaconda! WARNING: You current have a PYTHONPATH environment variable set. This may cause unexpected behavior when running the Python interpreter in Anaconda. For best results, please verify that your PYTHONPATH only points to directories of packages that are compatible with the Python interpreter in Anaconda: /Users/chl/anaconda
Anaconda supports multiple versions of Python to live on your system, and it provides a virtual environment that allow to switch to different version of the same package without much difficulty. Package management is done via
conda, a command-line utility that is used to fetch one or more specific versions of a package, display information on the system or environment locations, etc.
% conda search --all numpy 12 matches found: Packages with available versions and build strings: numpy 1.5.1 py26_0 1.5.1 py27_0 1.6.2 py26_0 1.6.2 py27_0 1.7.0b2 py26_0 1.7.0b2 py27_0 1.7.0rc1 py27_0 1.7.0rc1 py33_0 1.7.0rc1 py26_0 1.7.0 py26_0 1.7.0 py33_0 1.7.0 py27_0
As can be seen, there is a version of
numpy 2.7 for Python 3. I haven't explore the full capabilities of this distribution, but at first sight it sounds more interesting than EPD. The default Python is 2.7.3, with numpy 1.5.1 (!) and scipy 0.11.0.
I tried to compile Chaco last year; I don't remember if it was from a manual install or through
pip, but it failed. Today it just works (such packages usually go to my system-wide library,
% sudo pip install Chaco
I should note that several packages were installed or updated at the same time, including
Exemples from the Quickstart guide seem to run smoothly. I had to replace
traitsui, and of course remove every mention of
Bokeh, I just followed the instructions on GitHub.
% git clone git://github.com/ContinuumIO/Bokeh.git % cd Bokeh % sudo python setup.py install
That worked just fine to generate static html on my disk (
local_example.py). As I wanted to use the websockets backend, there're a couple of additional steps I had to follow. I already have redis installed on my Mac.
% python startlocal.py Traceback (most recent call last): File "startlocal.py", line 1, in <module> from bokeh.server import start File "/Users/chl/gitroot/Bokeh/bokeh/server/start.py", line 1, in <module> from geventwebsocket.handler import WebSocketHandler ImportError: No module named geventwebsocket.handler
So, I had to install
gevent-websocket, and then
flask. Finally, following the instructions on GitHub, this is just a matter of starting the redis server, launch
python startlocal.py in Bokeh main directory, and run
python pandas_example.py in another terminal to get the following plot, live in my browser (
Quite impressive so far!
I should note that Enthought just released Canopy (or see Introducing Enthought Canopy), but this is probably another story, and I tend to keep away from multiple install of Python. I had some issues with EPD and IPython last year so I decided to only use the Python version that ships with my Mac. I know some folks recommend using an official Python package, but I never have had any problem with Apple Python. ↩︎