Skip to main content

ipython notebook

I'm, of course, a Python groupie. Many of you perhaps use Matlab or Mathematica as an interactive environment to explore math (or algebra). Python has had the regular python shell and then Ipython, which allows such easy interactive exploration.

However, when using the python shell, I always feel the need to open up a separate editor and write scripts when the concepts get a little complicated, and this takes away a little of the interactiveness.

Ipython notebook changes all that. You should really try it out. The Ipython notebook uses your browser as a GUI (something I heartily support). It breaks everything up into 'cells'. Some cells can be text and some can be code. Each code cell can be executed on its own but as part of a common workspace.

This is ideal for me as I write this blog: I type in some code and execute it to see results (including graphs). Then I type up some text explaining the what I just did. I then move on to another cell for the next part. I can go back to an earlier cell and change code and then rerun everything, or just a part of it. It's like one giant interactive script. I love it.

There still is not a polished way to convert the notebook to say a wordpress post (though there is a pipeline for blogger). This script works for me to convert the figures into .png format. I simply copy and paste by code and text into this blog from the notebook and then attach the figure .png files. Janky and increases the time spent, but whatever.

Comments

Popular posts from this blog

A note on Python's __exit__() and errors

Python's context managers are a very neat way of handling code that needs a teardown once you are done. Python objects have do have a destructor method ( __del__ ) called right before the last instance of the object is about to be destroyed. You can do a teardown there. However there is a lot of fine print to the __del__ method. A cleaner way of doing tear-downs is through Python's context manager , manifested as the with keyword. class CrushMe: def __init__(self): self.f = open('test.txt', 'w') def foo(self, a, b): self.f.write(str(a - b)) def __enter__(self): return self def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() return True with CrushMe() as c: c.foo(2, 3) One thing that is important, and that got me just now, is error handling. I made the mistake of ignoring all those 'junk' arguments ( exc_type, exc_val, exc_tb ). I just skimmed the docs and what popped out is that you need to return True or...

Remove field code from Word document

e.g. before submitting a MS, or hand manipulating some formatting because Word does things (like cross-references) so half-assed [from here ] Select all the text (CTRL-A) Press Ctrl+Shift+F9 Editing to remove anonymous comments that only contain thanks. I really appreciate the thanks, but it makes it harder to find comments that carry pertinent information. I'm also going to try and paste informative comments in the body of the post to make them easier to find.

h5py and multiprocessing

The HDF5 format has been working awesome for me, but I ran into danger when I started to mix it with multiprocessing. It was the worst kind of danger: the intermittent error. Here are the dangers/issues in order of escalation (TL;DR is use a generator to feed data from your file into the child processes as they spawn. It's the easiest way. Read on for harder ways.) An h5py file handle can't be pickled and therefore can't be passed as an argument using pool.map() If you set the handle as a global and access it from the child processes you run the risk of racing which leads to corrupted reads. My personal runin was that my code sometimes ran fine but sometimes would complain that there are NaNs or Infinity in the data. This wasted some time tracking down. Other people have had this kind of problem [ 1 ]. Same problem if you pass the filename and have the different processes open individual instances of the file separately. The hard way to solve this problem is to sw...