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def ftrain(l):
    '''Convert an iterable to a nested list based on ordered comparison'''
    i = iter(l)
    tree, seen = ftrain_helper(i, i.next())
    # This might not be the desired behavior, but it's not terrible
    # You could also emit a warning or an exception here
    while(not seen is None):
        rest_tree, seen = ftrain_helper(i, seen)
        tree = [tree] + rest_tree
    return tree

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{
  "axes": [],
  "data": [
    {
      "format": {
        "feature": "world-countries",
        "type": "topojson"
      },
      "name": "countries",
      "transform": [

davclark

How to:

 1. Writing good questions
 
 2. Code
 
 3. I added this

 4. I also
    a. added this

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davclark

#!/usr/bin/env python3

'''ungraded.py - extract answers to ungraded problems 

Data is obtained from the `course_structure` and `courseware_studentmodule`
data, which are currently specified at the top of the file.

This was developed in response to a request from an instructor to obtain
individual student responses to ungraded questions *with 0 weight*. However,
upon inspection, I noted that all items had either 0 weight, or had weight

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davclark

#!/usr/bin/bash

# XXX The below was made before the jupyter switch and would be nice to
# update! For now, you can run this *before* ever running the jupyter notebook,
# OR you can `rm ~/.jupyter/migrated` and move any existing `jupyter_notebook_config.py` 
# after you run this script and it should re-import. -DJC

# Make it easy to set up password / encryption for IPython notebook

echo "

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