Lists, dictionaries and tuples are known generically as data structures; in this chapter we are starting to see compound data structures, like lists of tuples, and dictionaries that contain tuples as keys and lists as values. Compound data structures are useful, but they are prone to what I call shape errors; that is, errors caused when a data structure has the wrong type, size or composition. For example, if you are expecting a list with one integer and I give you a plain old integer (not in a list), it won’t work.
To help debug these kinds of errors, I have written a module called structshape that provides a function, also called structshape, that takes any kind of data structure as an argument and returns a string that summarizes its shape. You can download it from http://thinkpython.com/code/structshape.py
Here’s the result for a simple list:
>>> from structshape import structshape>>> t = [1,2,3]>>> print structshape(t)list of 3 int
A fancier program might write “list of 3 ints,” but it was easier not to deal with plurals. Here’s a list of lists:
>>> t2 = [[1,2], [3,4], [5,6]]>>> print structshape(t2)list of 3 list of 2 int
If the elements of the list are not the same type, structshape groups them, in order, by type:
>>> t3 = [1, 2, 3, 4.0, '5', '6', , , 9]>>> print structshape(t3)list of (3 int, float, 2 str, 2 list of int, int)
Here’s a list of tuples:
>>> s = 'abc'>>> lt = zip(t, s)>>> print structshape(lt)list of 3 tuple of (int, str)
And here’s a dictionary with 3 items that map integers to strings.
>>> d = dict(lt)>>> print structshape(d)dict of 3 int->str
If you are having trouble keeping track of your data structures, structshape can help.