What is the difference between “is None” and “== None”

I recently came across this syntax, I am unaware of the difference.

I would appreciate it if someone could tell me the difference.

Answers:

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Method 1

The answer is explained here.

To quote:

A class is free to implement
comparison any way it chooses, and it
can choose to make comparison against
None mean something (which actually
makes sense; if someone told you to
implement the None object from
scratch, how else would you get it to
compare True against itself?).

Practically-speaking, there is not much difference since custom comparison operators are rare. But you should use is None as a general rule.

Method 2

class Foo:
    def __eq__(self,other):
        return True
foo=Foo()

print(foo==None)
# True

print(foo is None)
# False

Method 3

In this case, they are the same. None is a singleton object (there only ever exists one None).

is checks to see if the object is the same object, while == just checks if they are equivalent.

For example:

p = [1]
q = [1]
p is q # False because they are not the same actual object
p == q # True because they are equivalent

But since there is only one None, they will always be the same, and is will return True.

p = None
q = None
p is q # True because they are both pointing to the same "None"

Method 4

It depends on what you are comparing to None. Some classes have custom comparison methods that treat == None differently from is None.

In particular the output of a == None does not even have to be boolean !! – a frequent cause of bugs.

For a specific example take a numpy array where the == comparison is implemented elementwise:

import numpy as np
a = np.zeros(3) # now a is array([0., 0., 0.])
a == None #compares elementwise, outputs array([False, False, False]), i.e. not boolean!!!
a is None #compares object to object, outputs False

Method 5

If you use numpy,

if np.zeros(3)==None: pass

will give you error when numpy does elementwise comparison

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