dog[::,::,::] in Python And How This Is Possible

The closest thing you might have seen to this might be in pandas

# df is some pandas DataFrame

df.iloc[:, :3]

^ selecting some rows and some columns using pandas

Default dog[::,::,::] behaviour

class Dog:
  pass

dog = Dog()
print(dog[::,::,::])    # ERROR

^ by default, we get an error

Defining __getitem__

class Dog:
  def __getitem__(self, key):
    return key

dog = Dog()

print(dog[1])        # 1
print(dog[2])        # 2
print(dog['apple'])  # apple

when we define the __getitem__ magic method, we are actually defining our Dog object’s behaviour if we try to dog[key]

Here, we define __getitem__ to return key itself. Which means that if we do dog[1] we will simply get 1, and if we do dog['apple'] we will simply get 'apple'

dog[::]

class Dog:
  def __getitem__(self, key):
    return key

dog = Dog()

print(dog[1])        # 1
print(dog[2])        # 2
print(dog[::])       # slice(None, None, None)

^ without changing any code in the Dog class, notice what happens when we try dog[::] — we get slice(None, None, None)

When we slice anything eg. list, string etc using lis[2:0:5], we are actually passing in a slice object ie. lis[slice(2,0,5)]. So when we do dog[::], we are actualy doing dog[slice(None,None,None)]

__getitem__ with multiple arguments

class Dog:
    def __getitem__(self, key):
        return key

dog = Dog()

print(dog[1])          # (1,)
print(dog[1,2])        # (1, 2)
print(dog[1,2,3,4,5])  # (1, 2,3 , 4, 5)

By default, if we do dog[1, 2, 3], the tuple (1, 2, 3) is passed to the __getitem__ magic method.

dog[::, ::, ::]

dog[::, ::, ::]

is the same as:

dog[slice(None, None, None), slice(None, None, None), slice(None, None, None)]

And so

class Dog:
    def __getitem__(self, key):
        return key

dog = Dog()

print(dog[::,::,::])

# (slice(None, None, None), slice(None, None, None), slice(None, None, None))

Conclusion

Ignoring this dumb dog example, you can now customize your classes and objects to take in more complex slices

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