Python None comparison: should I use "is" or ==?

My editor warns me when I compare my_var == None, but no warning when I use my_var is None.

I did a test in the Python shell and determined both are valid syntax, but my editor seems to be saying that my_var is None is preferred.

Is this the case, and if so, why?

Summary:

Use is when you want to check against an object's identity (e.g. checking to see if var is None). Use == when you want to check equality (e.g. Is var equal to 3?).

Explanation:

You can have custom classes where my_var == None will return True

e.g:

class Negator(object):
    def __eq__(self,other):
        return not other

thing = Negator()
print thing == None    #True
print thing is None    #False

is checks for object identity. There is only 1 object None, so when you do my_var is None, you're checking whether they actually are the same object (not just equivalent objects)

In other words, == is a check for equivalence (which is defined from object to object) whereas is checks for object identity:

lst = [1,2,3]
lst == lst[:]  # This is True since the lists are "equivalent"
lst is lst[:]  # This is False since they're actually different objects

is is generally preferred when comparing arbitrary objects to singletons like None because it is faster and more predictable. is always compares by object identity, whereas what == will do depends on the exact type of the operands and even on their ordering.

This recommendation is supported by PEP 8, which explicitly states that "comparisons to singletons like None should always be done with is or is not, never the equality operators."

PEP 8 defines that it is better to use the is operator when comparing singletons.

I recently encountered where this can go wrong.

import numpy as np
nparray = np.arange(4)

# Works
def foo_is(x=None):
    if x is not None:
        print(x[1])

foo_is()
foo_is(nparray)

# Code below raises 
# ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
def foo_eq(x=None):
    if x != None:
        print(x[1])

foo_eq()
foo_eq(nparray)

I created a function that optionally takes a numpy array as argument and changes if it is included. If I test for its inclusion using inequality operators !=, this raises a ValueError (see code above). If I use is not none, the code works correctly.