Walrus operator in Python 3.8: a primer

The all-new assignment expressions (:=) or the 'walrus operator' explained with examples. Know how it saves lines and helps make the author's intent clearer.Assignment expressions (:=), or the “walrus” operator, have been the most talked about feature to be introduced in the latest version of Python. The new addition to the language was proposed in PEP 572. In this post, we look at the rationale behind assignment expressions, and understand how to use it with various examples.

Assignment expressions (:=), or the “walrus” operator, have been the most talked about feature to be introduced in the latest version of Python. The new addition to the language was proposed in PEP 572. In this post, we look at the rationale behind assignment expressions, and understand how to use it with various examples.

Background

The primary rationale behind introducing assignment expressions, as stated in the PEP, is the observation that programmers want to save lines of code, and would even repeat a subexpression (and thereby slow down the program) in order to do so.

So instead of writing:

match = re.match(data)
group = match.group(1) if match else None

they write:

group = re.match(data).group(1) if re.match(data) else None

Assignment in expressions make it easier to write code constructs where a value calculated is re-used as part of some condition later, and help make the intent of the code’s author clearer. Languages like C and Go, among others, already support a functionality like this.

Where to use the Walrus operator

Let’s have a look at few examples on how to use walrus operator in Python:

Example 1: When a calculated value is used as part of a condition later

match = pattern.search(data)
if match is not None:
    do_something(match)

python python

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