Reputation: 6450
In Python, how do I check if an object is a generator object?
Trying
>>> type(myobject, generator)
gives the error
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'generator' is not defined
(I know I can check if the object has a __next__
method for it to be a generator, but I want some way using which I can determine the type of any object, not just generators.)
Upvotes: 224
Views: 83158
Reputation: 2407
There is no need to import a module, you can declare an object for comparison at the beginning of the program:
gentyp = type(1 for i in "")
# ...
type(myobject) == gentyp
Upvotes: 7
Reputation: 1124
The inspect.isgenerator
function is fine if you want to check for pure generators (i.e. objects of class "generator"). However it will return False
if you check, for example, a zip
iterable. An alternative way for checking for a generalised generator is to use this function:
def isgenerator(iterable):
return hasattr(iterable, '__iter__') and not hasattr(iterable, '__len__')
Upvotes: 18
Reputation: 27216
You can use GeneratorType
from types
:
>>> import types
>>> types.GeneratorType
<class 'generator'>
>>> gen = (i for i in range(10))
>>> isinstance(gen, types.GeneratorType)
True
Upvotes: 313
Reputation: 784
It's a little old question, however I was looking for similar solution for myself, but for async generator class, so you may find this helpful.
Based on utdemir reply:
import types
isinstance(async_generator(), types.AsyncGeneratorType)
Upvotes: 0
Reputation: 2636
You could use the Iterator or more specifically, the Generator from the typing module.
from typing import Generator, Iterator
g = (i for i in range(1_000_000))
print(type(g))
print(isinstance(g, Generator))
print(isinstance(g, Iterator))
<class 'generator'>
True
True
Upvotes: 9
Reputation: 177
If you are using tornado webserver or similar you might have found that server methods are actually generators and not methods. This makes it difficult to call other methods because yield is not working inside the method and therefore you need to start managing pools of chained generator objects. A simple method to manage pools of chained generators is to create a help function such as
def chainPool(*arg):
for f in arg:
if(hasattr(f,"__iter__")):
for e in f:
yield e
else:
yield f
Now writing chained generators such as
[x for x in chainPool(chainPool(1,2),3,4,chainPool(5,chainPool(6)))]
Produces output
[1, 2, 3, 4, 5, 6]
Which is probably what you want if your looking to use generators as a thread alternative or similar.
Upvotes: 2
Reputation: 16361
I think it is important to make distinction between generator functions and generators (generator function's result):
>>> def generator_function():
... yield 1
... yield 2
...
>>> import inspect
>>> inspect.isgeneratorfunction(generator_function)
True
calling generator_function won't yield normal result, it even won't execute any code in the function itself, the result will be special object called generator:
>>> generator = generator_function()
>>> generator
<generator object generator_function at 0x10b3f2b90>
so it is not generator function, but generator:
>>> inspect.isgeneratorfunction(generator)
False
>>> import types
>>> isinstance(generator, types.GeneratorType)
True
and generator function is not generator:
>>> isinstance(generator_function, types.GeneratorType)
False
just for a reference, actual call of function body will happen by consuming generator, e.g.:
>>> list(generator)
[1, 2]
See also In python is there a way to check if a function is a "generator function" before calling it?
Upvotes: 45
Reputation: 391854
I know I can check if the object has a next method for it to be a generator, but I want some way using which I can determine the type of any object, not just generators.
Don't do this. It's simply a very, very bad idea.
Instead, do this:
try:
# Attempt to see if you have an iterable object.
for i in some_thing_which_may_be_a_generator:
# The real work on `i`
except TypeError:
# some_thing_which_may_be_a_generator isn't actually a generator
# do something else
In the unlikely event that the body of the for loop also has TypeError
s, there are several choices: (1) define a function to limit the scope of the errors, or (2) use a nested try block.
Or (3) something like this to distinguish all of these TypeError
s which are floating around.
try:
# Attempt to see if you have an iterable object.
# In the case of a generator or iterator iter simply
# returns the value it was passed.
iterator = iter(some_thing_which_may_be_a_generator)
except TypeError:
# some_thing_which_may_be_a_generator isn't actually a generator
# do something else
else:
for i in iterator:
# the real work on `i`
Or (4) fix the other parts of your application to provide generators appropriately. That's often simpler than all of this.
Upvotes: 1
Reputation: 60604
>>> import inspect
>>>
>>> def foo():
... yield 'foo'
...
>>> print inspect.isgeneratorfunction(foo)
True
Upvotes: 4
Reputation: 70031
You mean generator functions ? use inspect.isgeneratorfunction
.
EDIT :
if you want a generator object you can use inspect.isgenerator as pointed out by JAB in his comment.
Upvotes: 52