Determine the type of an object?

There are two built-in functions that help you identify the type of an object. You can use type() if you need the exact type of an object, and isinstance() to check an object’s type against something. Usually, you want to use isinstance() most of the times since it is very robust and also supports type inheritance.

To get the actual type of an object, you use the built-in type() function. Passing an object as the only parameter will return the type object of that object:

>>> type([]) is list
True
>>> type({}) is dict
True
>>> type('') is str
True
>>> type(0) is int
True

This of course also works for custom types:

>>> class Test1 (object):
        pass
>>> class Test2 (Test1):
        pass
>>> a = Test1()
>>> b = Test2()
>>> type(a) is Test1
True
>>> type(b) is Test2
True

Note that type() will only return the immediate type of the object, but won’t be able to tell you about type inheritance.

>>> type(b) is Test1
False

To cover that, you should use the isinstance function. This of course also works for built-in types:

>>> isinstance(b, Test1)
True
>>> isinstance(b, Test2)
True
>>> isinstance(a, Test1)
True
>>> isinstance(a, Test2)
False
>>> isinstance([], list)
True
>>> isinstance({}, dict)
True

isinstance() is usually the preferred way to ensure the type of an object because it will also accept derived types. So unless you actually need the type object (for whatever reason), using isinstance() is preferred over type().

The second parameter of isinstance() also accepts a tuple of types, so it’s possible to check for multiple types at once. isinstance will then return true, if the object is of any of those types:

>>> isinstance([], (tuple, list, set))
True

Use type():

>>> a = []
>>> type(a)
<type 'list'>
>>> f = ()
>>> type(f)
<type 'tuple'>

It might be more Pythonic to use a try...except block. That way, if you have a class which quacks like a list, or quacks like a dict, it will behave properly regardless of what its type really is.

To clarify, the preferred method of "telling the difference" between variable types is with something called duck typing: as long as the methods (and return types) that a variable responds to are what your subroutine expects, treat it like what you expect it to be. For example, if you have a class that overloads the bracket operators with getattr and setattr, but uses some funny internal scheme, it would be appropriate for it to behave as a dictionary if that's what it's trying to emulate.

The other problem with the type(A) is type(B) checking is that if A is a subclass of B, it evaluates to false when, programmatically, you would hope it would be true. If an object is a subclass of a list, it should work like a list: checking the type as presented in the other answer will prevent this. (isinstance will work, however).

be careful using isinstance

isinstance(True, bool)
True
>>> isinstance(True, int)
True

but type

type(True) == bool
True
>>> type(True) == int
False

In many practical cases instead of using type or isinstance you can also use @functools.singledispatch, which is used to define generic functions (function composed of multiple functions implementing the same operation for different types).

In other words, you would want to use it when you have a code like the following:

def do_something(arg):
    if isinstance(arg, int):
        ... # some code specific to processing integers
    if isinstance(arg, str):
        ... # some code specific to processing strings
    if isinstance(arg, list):
        ... # some code specific to processing lists
    ...  # etc

Here is a small example of how it works:

from functools import singledispatch


@singledispatch
def say_type(arg):
    raise NotImplementedError(f"I don't work with {type(arg)}")


@say_type.register
def _(arg: int):
    print(f"{arg} is an integer")


@say_type.register
def _(arg: bool):
    print(f"{arg} is a boolean")

>>> say_type(0)
0 is an integer
>>> say_type(False)
False is a boolean
>>> say_type(dict())
# long error traceback ending with:
NotImplementedError: I don't work with <class 'dict'>

Additionaly we can use abstract classes to cover several types at once:

from collections.abc import Sequence


@say_type.register
def _(arg: Sequence):
    print(f"{arg} is a sequence!")

>>> say_type([0, 1, 2])
[0, 1, 2] is a sequence!
>>> say_type((1, 2, 3))
(1, 2, 3) is a sequence!

value = 12
print(type(value)) # will return <class 'int'> (means integer)

or you can do something like this

value = 12
print(type(value) == int) # will return true

using type()

x='hello this is a string'
print(type(x))

output

<class 'str'>

to extract only the str use this

x='this is a string'
print(type(x).__name__)#you can use__name__to find class

output

str

if you use type(variable).__name__ it can be read by us

type() is a better solution than isinstance(), particularly for booleans:

True and False are just keywords that mean 1 and 0 in python. Thus,

isinstance(True, int)

and

isinstance(False, int)

both return True. Both booleans are an instance of an integer. type(), however, is more clever:

type(True) == int

returns False.

In general you can extract a string from object with the class name,

str_class = object.__class__.__name__

and using it for comparison,

if str_class == 'dict':
    # blablabla..
elif str_class == 'customclass':
    # blebleble..

For the sake of completeness, isinstance will not work for type checking of a subtype that is not an instance. While that makes perfect sense, none of the answers (including the accepted one) covers it. Use issubclass for that.

>>> class a(list):
...   pass
... 
>>> isinstance(a, list)
False
>>> issubclass(a, list)
True