Check if all elements of a list are of the same type

Using any(), no need to traverse whole list. Just break as soon as object which is not int or long is found:

>>> not any(not isinstance(y,(int,long)) for y in [1,2,3])
True
>>> not any(not isinstance(y,(int,long)) for y in [1,'a',2,3])
False

>>> def checkInt(l):
    return all(isinstance(i, (int, long)) for i in l)

>>> checkInt([1,2,3])
True
>>> checkInt(['a',1,2,3])
False
>>> checkInt([1,2,3,238762384762364892364])
True

The simplest way to check if a list is composed of omogeneous elements can be with the groupby function of the itertools module:

from itertools import groupby
len(list(groupby(yourlist,lambda i:type(i)))) == 1

If th len is different from one it means that it found different kind of types in the list.
This has the problem of running trough the entire sequence.
If you want a lazy version you can write a function for that:

def same(iterable):
    iterable = iter(iterable)
    try:
        first = type(next(iterable))
        return all(isinstance(i,first) for i in iterable)
    except StopIteration:
        return True

This function store the type of the first element and stop as soon as it find a different type in one of the elements in the list.

Both of this methods are strongly sensitive to the type, so it will see as different int and float, but this should be as close as you can get to your request

EDIT:

replaced the for cycle with a call to all as suggested by mgilson

in case of void iterator it returns True to be consistent with the behavior of the bulitin all function

    def c(x):
         for i in x:
             if isinstance(i,str):
                   return False
             if isinstance(i,float):
                   return False

          return True

You can also use type() if you want to exclude subclasses. See the difference between isinstance() and type():

>>> not any(not type(y) is int for y in [1, 2, 3])
True
>>> not any(not type(y) == int for y in [1, 'a', 2.3])
False

Although you may not want to, because this will be more fragile. If y changes its type to a subclass of int, this code will break, whereas isinstance() will still work.

It’s OK to use is because there is only one <type 'int'> in memory, so they should return the same identity if they are the same type.

I prefer to use map for a case like this:

from types import IntType
In [21]: map((lambda x: isinstance(x, IntType)), x)
   Out[21]: [True, False, False]

Combining some of the answers already given, using a combination of map(), type() and set() provides a imho rather readable answer. Assuming the limitation of not checking for type polymorphisms is ok. Also not the most computationally efficient answer, but it allows to easily check whether all elements are of the same type.

# To check whether all elements in a list are integers
set(map(type, [1,2,3])) == {int}
# To check whether all elements are of the same type
len(set(map(type, [1,2,3]))) == 1

I like the function by EnricoGiampieri (above) but there is a simpler version using all_equal from the "Itertools recipes" section of the itertools docs:

from itertools import groupby

def all_equal(iterable):
    "Returns True if all the elements are equal to each other"
    g = groupby(iterable)
    return next(g, True) and not next(g, False)

All of these recipes are packaged in more_itertools:

Substantially all of these recipes and many, many others can be installed from the more-itertools project found on the Python Package Index:

pip install more-itertools

The extended tools offer the same high performance as the underlying toolset. The superior memory performance is kept by processing elements one at a time rather than bringing the whole iterable into memory all at once. Code volume is kept small by linking the tools together in a functional style which helps eliminate temporary variables. High speed is retained by preferring “vectorized” building blocks over the use of for-loops and generators which incur interpreter overhead.

from more_itertools import all_equal

all_equal(map(type, iterable))

or with isinstance and a known type int (as per the original question)

all_equal(map(lambda x: isinstance(x, int), iterable))

These two ways are more concise than Enrico’s suggestion and handle ‘void iterators’ (e.g. range(0)) just as Enrico’s function does.

all_equal(map(type, range(0))) # True
all_equal(map(type, range(1))) # True
all_equal(map(type, range(2))) # True

all_equal(map(lambda x: isinstance(x, int), range(0))) # True
all_equal(map(lambda x: isinstance(x, int), range(1))) # True
all_equal(map(lambda x: isinstance(x, int), range(2))) # True

I would prefer you use this method, where you iterate through each item in the list and check if they are all same data type, if Yes, returns True else, False.

def checkIntegers(x):
    # return True if all elements are integers, False otherwise
    return all(isinstance(i, type(x[0])) for i in x[1:])

x = [1, 2.5, 'a']
checkIntegers(x)

False

Here is a concise function regarding this, currently it checks (in a list) if all items are integer or if all items are string, or if mixed data type.

def check_item_dtype_in_list(item_range):
    if all(map(lambda x: str(x).isdigit(), item_range)):
        item_range = list(map(int, item_range))
        print('all are integer')
        print(item_range)
        return 
    elif all(isinstance(item, str) for item in item_range):
        print('all are string')
        print(item_range)
        return 
    elif any(map(lambda x: str(x), item_range)):
        print('mixed dtype')
        print(item_range)
        return 

check_item_dtype_in_list(['2', 2, 3])
check_item_dtype_in_list(["2", 2, 'Two'])
check_item_dtype_in_list(['Two', 'Two', 'Two'])
check_item_dtype_in_list([2, 2., 'Two'])

all are integer
[2, 2, 3]
mixed dtype
['2', 2, 'Two']
all are string
['Two', 'Two', 'Two']
mixed dtype
[2, 2.0, 'Two']