Loop through functions in a class

Question

I have several functions inside a class that I applied augmentation to a numpy image array. I would like to know how to loop through all of them and apply those. For example:

Class Augmentation():
    def rotation(data):
      return rotated_image
    def shear(data):
      return sheared_image
    def elasticity(data):
      return enlarged_image
A=Augmentation()

My end result should be stacking all my functions. So for example: my data is (64,64) in shape. So after all my augmentations I should have a final numpy of (12,64,64). I currently tried creating different functions and then used

stack_of_images = np.stack(f1,f2,f3,....,f12)
stack_of_images.shape = (12,64,64)

I am using 12 different functions to augmentate numpy image arrays. I insert 1 image (64,64) and I get 12 images stacked (12,64,64).

Answer 1

You can do this by accessing the attribute dictionary of the type. You can either get it with vars(Augmentation) or Augmentation.__dict__. Then, just iterate through the dict, and check for functions with callable.

NOTE: querying vars(A) or A.__dict__ (note it's the instance, not the class), will NOT include anything defined in the class, and in this case would be just {}. You don't even have to create an instance in the first place.

NOTE2: It seems like you should tag all methods with the decorator @staticmethod instead. Otherwise calling any method on an instance, like A.shear(), would pass A as data instead, which is most likely not desired.

class foo:
    @staticmethod
    def bar(data):
        ...

Example:

methods = []
for attrname,attrvalue in vars(Augmentation).items():
    if callable(attrvalue):
        methods.append(attrvalue)
print([i.__name__ for i in methods])