What's the canonical way to check for type in Python?
What is the best way to check whether a given object is of a given type? How about checking whether the object inherits from a given type?
Let's say I have an object o
. How do I check whether it's a str
?
To check if o
is an instance of str
or any subclass of str
, use isinstance (this would be the "canonical" way):
if isinstance(o, str):
To check if the type of o
is exactly str
(exclude subclasses):
if type(o) is str:
The following also works, and can be useful in some cases:
if issubclass(type(o), str):
See Built-in Functions in the Python Library Reference for relevant information.
One more note: in this case, if you're using Python 2, you may actually want to use:
if isinstance(o, basestring):
because this will also catch Unicode strings (unicode
is not a subclass of str
; both str
and unicode
are subclasses of basestring
). Note that basestring
no longer exists in Python 3, where there's a strict separation of strings (str
) and binary data (bytes
).
Alternatively, isinstance
accepts a tuple of classes. This will return True
if o
is an instance of any subclass of any of (str, unicode)
:
if isinstance(o, (str, unicode)):
The most Pythonic way to check the type of an object is... not to check it.
Since Python encourages Duck Typing, you should just try...except
to use the object's methods the way you want to use them. So if your function is looking for a writable file object, don't check that it's a subclass of file
, just try to use its .write()
method!
Of course, sometimes these nice abstractions break down and isinstance(obj, cls)
is what you need. But use sparingly.
isinstance(o, str)
will return True
if o
is an str
or is of a type that inherits from str
.
type(o) is str
will return True
if and only if o
is a str. It will return False
if o
is of a type that inherits from str
.
After the question was asked and answered, type hints were added to Python. Type hints in Python allow types to be checked but in a very different way from statically typed languages. Type hints in Python associate the expected types of arguments with functions as runtime accessible data associated with functions and this allows for types to be checked. Example of type hint syntax:
def foo(i: int):
return i
foo(5)
foo('oops')
In this case we want an error to be triggered for foo('oops')
since the annotated type of the argument is int
. The added type hint does not cause an error to occur when the script is run normally. However, it adds attributes to the function describing the expected types that other programs can query and use to check for type errors.
One of these other programs that can be used to find the type error is mypy
:
mypy script.py
script.py:12: error: Argument 1 to "foo" has incompatible type "str"; expected "int"
(You might need to install mypy
from your package manager. I don't think it comes with CPython but seems to have some level of "officialness".)
Type checking this way is different from type checking in statically typed compiled languages. Because types are dynamic in Python, type checking must be done at runtime, which imposes a cost -- even on correct programs -- if we insist that it happen at every chance. Explicit type checks may also be more restrictive than needed and cause unnecessary errors (e.g. does the argument really need to be of exactly list
type or is anything iterable sufficient?).
The upside of explicit type checking is that it can catch errors earlier and give clearer error messages than duck typing. The exact requirements of a duck type can only be expressed with external documentation (hopefully it's thorough and accurate) and errors from incompatible types can occur far from where they originate.
Python's type hints are meant to offer a compromise where types can be specified and checked but there is no additional cost during usual code execution.
The typing
package offers type variables that can be used in type hints to express needed behaviors without requiring particular types. For example, it includes variables such as Iterable
and Callable
for hints to specify the need for any type with those behaviors.
While type hints are the most Pythonic way to check types, it's often even more Pythonic to not check types at all and rely on duck typing. Type hints are relatively new and the jury is still out on when they're the most Pythonic solution. A relatively uncontroversial but very general comparison: Type hints provide a form of documentation that can be enforced, allow code to generate earlier and easier to understand errors, can catch errors that duck typing can't, and can be checked statically (in an unusual sense but it's still outside of runtime). On the other hand, duck typing has been the Pythonic way for a long time, doesn't impose the cognitive overhead of static typing, is less verbose, and will accept all viable types and then some.
Here is an example why duck typing is evil without knowing when it is dangerous.
For instance: Here is the Python code (possibly omitting proper indenting), note that this situation is avoidable by taking care of isinstance and issubclassof functions to make sure that when you really need a duck, you don't get a bomb.
class Bomb:
def talk(self):
self.explode()
def explode(self):
print("BOOM!, The bomb explodes.")
class Duck:
def talk(self):
print("I am a duck, I will not blow up if you ask me to talk.")
class Kid:
kids_duck = None
def __init__(self):
print("Kid comes around a corner and asks you for money so he could buy a duck.")
def take_duck(self, duck):
self.kids_duck = duck
print("The kid accepts the duck, and happily skips along.")
def do_your_thing(self):
print("The kid tries to get the duck to talk.")
self.kids_duck.talk()
my_kid = Kid()
my_kid.take_duck(Bomb())
my_kid.do_your_thing()
NOTE: the example is old, naive, and the danger is greatly exaggerated. It is left as a proof of concept without major edits other than update to Python 3. I do not remember what compelled me to write this originally.