Object is enumerable but not indexable?

Question

Problem summary and question

I'm trying to look at some of the data inside an object that can be enumerated over but not indexed. I'm still newish to python, but I don't understand how this is possible.

If you can enumerate it, why can't you access the index through the same way enumerate does? And if not, is there a way to access the items individually?

The actual example

import tensorflow_datasets as tfds

train_validation_split = tfds.Split.TRAIN.subsplit([6, 4])

(train_data, validation_data), test_data = tfds.load(
    name="imdb_reviews", 
    split=(train_validation_split, tfds.Split.TEST),
    as_supervised=True)

Take a select subset of the dataset

foo = train_data.take(5)

I can iterate over foo with enumerate:

[In] for i, x in enumerate(foo):
    print(i)

which generates the expected output:

0
1
2
3
4

But then, when I try to index into it foo[0] I get this error:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-44-2acbea6d9862> in <module>
----> 1 foo[0]

TypeError: 'TakeDataset' object does not support indexing

Answer 1

This is a result of foo being iterable, but not having a __getitem__ function. You can use itertools.isslice to get the nth element of an iterable like so

import itertools

def nth(iterable, n, default=None):
    "Returns the nth item or a default value"
    return next(itertools.islice(iterable, n, None), default)

Answer 2

Python only allows these things if the class has methods for them:

• __getitem__ is required for the [] syntax.
• __iter__ and __next__¹ are required to iterate.

Any class can define one without defining the other. __getattr__ is usually not defined if it would be inefficient.

---

¹__next__ is required on the class returned by __iter__.