Python Identity and Membership Operators

Python identity and membership operators answer two everyday questions. "Are these the exact same thing?" is answered by is. "Is this inside that?" is answered by in. In this lesson, you'll learn how is, is not, in and not in work, why you should write x is None, and why is is the wrong tool for comparing numbers and text.

What are identity operators in Python?

Every value in Python lives in memory as an object. A variable is a name that points to an object, as you saw in Python variables. Identity operators check whether two names point to the same object, not just to equal values.

What is the difference between is and == in Python?

== compares values. is compares identity. Here are two shopping lists with the same items. (Lists hold several values in square brackets; you'll learn them in Python lists.)

my_list = ["eggs", "milk"]
your_list = ["eggs", "milk"]
same_list = my_list

print(my_list == your_list)   # same items?
print(my_list is your_list)   # same object?
print(my_list is same_list)

True
False
True

my_list and your_list are two separate lists that happen to contain the same items. same_list = my_list doesn't copy anything; it just puts a second name on the same list. You can see an object's identity number with the built-in id() function: two names are the same object exactly when their id() values match.

Why should you write x is None?

None is Python's special value for "nothing" or "no value yet". There is only one None object in the whole program, so checking identity is exact and fast. The official Python style guide (PEP 8) says to always compare with None using is or is not:

delivery_date = None   # not scheduled yet

print(delivery_date is None)
print(delivery_date is not None)

delivery_date = "Friday"
print(delivery_date is not None)

True
False
True

Why shouldn't you use is to compare numbers or strings?

Because two equal numbers or strings are not guaranteed to be the same object. Sometimes Python reuses objects to save memory (it keeps one copy of small integers from -5 to 256, for example), and sometimes it doesn't. That makes is give results that seem random:

order_id = 1000
typed_id = int("1000")   # same value, built at run time

print(order_id == typed_id)
print(order_id is typed_id)

True
False

The values are equal, but they are two different objects. If your code used is here, a correct order number would be rejected. Python even warns you when you write is with a literal number or string:

x = 5
print(x is 5)   # SyntaxWarning: "is" with 'int' literal. Did you mean "=="?

What are membership operators in Python?

Membership operators check whether a value is inside a collection, such as a string, a list or a dictionary. They return True or False.

How do you check if text is in a string?

With strings, in looks for a substring: a piece of text that appears anywhere inside, in the exact same order and case.

email = "maya.lopez@example.com"

print("@" in email)
print("example" in email)
print("Maya" in email)          # case matters
print(" " not in email)         # no spaces allowed

True
True
False
True

How do you check if an item is in a list?

With a list, in checks whether any item is equal to the value (it uses ==, not is). Unlike strings, it matches whole items only:

playlist = ["Yellow", "Dreams", "Africa"]

print("Africa" in playlist)
print("Afr" in playlist)        # not a whole item
print("Hello" not in playlist)

True
False
True

How does in work with a dictionary?

A dictionary stores pairs of keys and values, like a menu of items and prices. You'll learn dictionaries in Python dictionaries. For now, the important part: in checks the keys, not the values.

menu = {"espresso": 2.5, "latte": 3.8, "mocha": 4.2}

print("latte" in menu)
print("tea" in menu)
print(3.8 in menu)              # 3.8 is a value, not a key

True
False
False

Real-world example: checking a sign-up form

username = "skater_jo"
email = "jo@example.com"
promo_code = None
taken_names = ["admin", "skater_jo", "guest"]

print("Name available:", username not in taken_names)
print("Email looks valid:", "@" in email and "." in email)
print("Promo entered:", promo_code is not None)

Name available: False
Email looks valid: True
Promo entered: False

Common mistakes with identity and membership operators

1. Using is to compare values

As shown above, order_id is typed_id can be False even when the numbers are equal. Use ==.

2. Checking a number inside a string

pin = "4821"
print(4 in pin)

TypeError: 'in <string>' requires string as left operand, not int

To search a string, the left side must be text too: "4" in pin.

3. Expecting in to search dictionary values

3.8 in menu is False because in only looks at keys. You'll see how to search values in dictionary methods.

4. Forgetting that in is case-sensitive

"Paris" in "I love paris" is False. Make both sides lowercase first if case shouldn't matter.

Practice exercise

seat = None
meal_options = ["veggie", "chicken", "fish"]
request = "vegan"
booking_code = "BA2490"

print("Seat chosen:", seat is not None)
print("Meal available:", request in meal_options)
print("British Airways flight:", "BA" in booking_code)

Seat chosen: False
Meal available: False
British Airways flight: True

What's next?

You've now met every kind of Python operator. But what happens when you mix several in one line, like 2 + 3 * 4 ** 2? Find out which runs first in Python operator precedence.