In Python, how do I determine if an object is iter

Question

Is there a method like isiterable? The only solution I have found so far is to call

hasattr(myObj, '__iter__')

But I am not sure how fool-proof this is.

Answer 1

Duck typing

try:
    iterator = iter(theElement)
except TypeError:
    # not iterable
else:
    # iterable

# for obj in iterator:
#     pass

Type checking

Use the Abstract Base Classes. They need at least Python 2.6 and work only for new-style classes.

from collections.abc import Iterable   # import directly from collections for Python < 3.3

if isinstance(theElement, Iterable):
    # iterable
else:
    # not iterable

However, iter() is a bit more reliable as described by the documentation:

Checking isinstance(obj, Iterable) detects classes that are registered as Iterable or that have an __iter__() method, but it does not detect classes that iterate with the __getitem__() method. The only reliable way to determine whether an object is iterable is to call iter(obj).

Answer 2

This isn't sufficient: the object returned by __iter__ must implement the iteration protocol (i.e. next method). See the relevant section in the documentation.

In Python, a good practice is to "try and see" instead of "checking".

Answer 3

In Python <= 2.5, you can't and shouldn't - iterable was an "informal" interface.

But since Python 2.6 and 3.0 you can leverage the new ABC (abstract base class) infrastructure along with some builtin ABCs which are available in the collections module:

from collections import Iterable

class MyObject(object):
    pass

mo = MyObject()
print isinstance(mo, Iterable)
Iterable.register(MyObject)
print isinstance(mo, Iterable)

print isinstance("abc", Iterable)

Now, whether this is desirable or actually works, is just a matter of conventions. As you can see, you can register a non-iterable object as Iterable - and it will raise an exception at runtime. Hence, isinstance acquires a "new" meaning - it just checks for "declared" type compatibility, which is a good way to go in Python.

On the other hand, if your object does not satisfy the interface you need, what are you going to do? Take the following example:

from collections import Iterable
from traceback import print_exc

def check_and_raise(x):
    if not isinstance(x, Iterable):
        raise TypeError, "%s is not iterable" % x
    else:
        for i in x:
            print i

def just_iter(x):
    for i in x:
        print i


class NotIterable(object):
    pass

if __name__ == "__main__":
    try:
        check_and_raise(5)
    except:
        print_exc()
        print

    try:
        just_iter(5)
    except:
        print_exc()
        print

    try:
        Iterable.register(NotIterable)
        ni = NotIterable()
        check_and_raise(ni)
    except:
        print_exc()
        print

If the object doesn't satisfy what you expect, you just throw a TypeError, but if the proper ABC has been registered, your check is unuseful. On the contrary, if the __iter__ method is available Python will automatically recognize object of that class as being Iterable.

So, if you just expect an iterable, iterate over it and forget it. On the other hand, if you need to do different things depending on input type, you might find the ABC infrastructure pretty useful.

Answer 4

The easiest way, respecting the Python's duck typing, is to catch the error (Python knows perfectly what does it expect from an object to become an iterator):

class A(object):
    def __getitem__(self, item):
        return something

class B(object):
    def __iter__(self):
        # Return a compliant iterator. Just an example
        return iter([])

class C(object):
    def __iter__(self):
        # Return crap
        return 1

class D(object): pass

def iterable(obj):
    try:
        iter(obj)
        return True
    except:
        return False

assert iterable(A())
assert iterable(B())
assert iterable(C())
assert not iterable(D())

Notes:

1. It is irrelevant the distinction whether the object is not iterable, or a buggy __iter__ has been implemented, if the exception type is the same: anyway you will not be able to iterate the object.

2. I think I understand your concern: How does callable exists as a check if I could also rely on duck typing to raise an AttributeError if __call__ is not defined for my object, but that's not the case for iterable checking?

   I don't know the answer, but you can either implement the function I (and other users) gave, or just catch the exception in your code (your implementation in that part will be like the function I wrote - just ensure you isolate the iterator creation from the rest of the code so you can capture the exception and distinguish it from another TypeError.

Answer 5

I often find convenient, inside my scripts, to define an iterable function. (Now incorporates Alfe's suggested simplification):

import collections

def iterable(obj):
    return isinstance(obj, collections.Iterable):

so you can test if any object is iterable in the very readable form

if iterable(obj):
    # act on iterable
else:
    # not iterable

as you would do with thecallable function

EDIT: if you have numpy installed, you can simply do: from numpy import iterable, which is simply something like

def iterable(obj):
    try: iter(obj)
    except: return False
    return True

If you do not have numpy, you can simply implement this code, or the one above.

Answer 6

The best solution I've found so far:

hasattr(obj, '__contains__')

which basically checks if the object implements the in operator.

Advantages (none of the other solutions has all three):

• it is an expression (works as a lambda, as opposed to the try...except variant)
• it is (should be) implemented by all iterables, including strings (as opposed to __iter__)
• works on any Python >= 2.5

Notes:

• the Python philosophy of "ask for forgiveness, not permission" doesn't work well when e.g. in a list you have both iterables and non-iterables and you need to treat each element differently according to it's type (treating iterables on try and non-iterables on except would work, but it would look butt-ugly and misleading)
• solutions to this problem which attempt to actually iterate over the object (e.g. [x for x in obj]) to check if it's iterable may induce significant performance penalties for large iterables (especially if you just need the first few elements of the iterable, for example) and should be avoided