String comparison in Python: is vs. ==

When to use is or ==

Dealing with None

When testing if a variable has a value of None, it's preferred to use is because None is a singleton object in Python (meaning there’s only one None sailing the Pythonic seas).

val = do_something_mysterious()
if val is None:  # It's None for sure, no imposters allowed!
    handle_mysterious_case()
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Boolean checks

For boolean values, clear syntax is king. Use if x: rather than if x == True:.

if sea_is_calm:
    hoist_sail()  # Sail on, me hearties!
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Small numbers and is

Python performs optimizations for immutable types like integers, causing some "inflated truths".

a = 256
b = 256
print(a is b)  # True, but only by the grace of Python's optimization quirks
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NaN: Not an ordinary member

When dealing with NaN (Not a Number), equality checks through == are effectively irrelevant.

import math
nan = math.nan
print(nan == nan)  # False, isNaN joined the Doubt Club: NaN doubts its own identity.
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Wise precautions

Immutable vs. mutable battles

In a Pythonic war of immutable vs mutable, choose your weapon of comparison wisely: for immutable objects (str, int, tuple), 'arm' yourself with ==. If dealing with mutable structures (list, dict), remember, appearances can be deceptive; two objects may look alike, but can be distinct entities.

Dodging logical entanglements

Beware of the booby traps of logical errors! Ensure to use is None rather than == None to avoid falling off the Pythonic cliffs.

Infinity War

In the realm of loops or conditions, is not instead of != might open a portal to the Infinite Loop Universe™. Be as fierce as Thanos, and crush infinite loops with !=.

while cash is not infinite:  # This can sadly loop forever...
    keep_working()
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The Quirks of Python Interning

Python's string interning can result in misleading outcomes in some cases. Using is for comparison between strings can sometimes return True, but it's nothing more than a trick played by Python's optimization.