5.2. Assignment Expression

5.2.1. Recap

result = [x for x in range(0,10)]
result = [x for x in range(0,10) if x%2 == 0]

5.2.2. Rationale

  • Since Python 3.8: PEP 572 -- Assignment Expressions

  • A.K.A. "the walrus operator"

  • A.K.A. "Named Expressions"

During discussion of this PEP, the operator became informally known as "the walrus operator". The construct's formal name is "Assignment Expressions" (as per the PEP title), but they may also be referred to as "Named Expressions" (e.g. the CPython reference implementation uses that name internally). [pep572]

DATA = ['Jan Twardowski',
        'Melissa Lewis',
        'Mark Watney']


result = [(name.split()[0], name.split()[1])
          for name in DATA]
# [('Jan', 'Twardowski'),
#  ('Melissa', 'Lewis'),
#  ('Mark', 'Watney')]

result = [{'firstname': name.split()[0],
           'lastname': name.split()[1]}
          for name in DATA]
# [{'firstname': 'Jan', 'lastname': 'Twardowski'},
#  {'firstname': 'Melissa', 'lastname': 'Lewis'},
#  {'firstname': 'Mark', 'lastname': 'Watney'}]

result = [{'firstname': astro[0],
           'lastname': astro[1]}
          for name in DATA
          if (astro := name.split())]
# [{'firstname': 'Jan', 'lastname': 'Twardowski'},
#  {'firstname': 'Melissa', 'lastname': 'Lewis'},
#  {'firstname': 'Mark', 'lastname': 'Watney'}]

5.2.3. Syntax

result = [<RETURN>
          for <VARIABLE1> in <ITERABLE>
          if (<VARIABLE2> := <EXPR>)]

result = [<RETURN>
          for <VARIABLE1> in <ITERABLE>
          if (<VARIABLE2> := <EXPR>)
          and (<VARIABLE3> := <EXPR>)]

result = [<RETURN>
          for <VARIABLE1> in <ITERABLE>
          if (<VARIABLE2> := <EXPR>)
          and (<VARIABLE3> := <EXPR>)
          or (<VARIABLE4> := <EXPR>)]

It's not substitution for equals:

a = 1

a := 1
# Traceback (most recent call last):
# SyntaxError: invalid syntax

result = {}
result['commander'] = 'Mark Watney'

result = {}
result['commander'] := 'Mark Watney'
# Traceback (most recent call last):
# SyntaxError: cannot use assignment expressions with subscript

x = 1, 2
print(x)
# (1, 2)

(x := 1, 2)
print(x)
# 1

result = (x := 1, 2)
print(result)
# (1, 2)

x = 0
x += 1

x = 0
x +:= 1
# Traceback (most recent call last):
# SyntaxError: invalid syntax
../../_images/unpacking-assignmentexpr-bdfl1.png

Figure 5.14. Guido van Rossum stepped down after accepting PEP 572 -- Assignment Expressions

5.2.4. Example

5.2.4.1. Reusing Results

result = [f(x), f(x)+1, f(x)+2]

result = [res := f(x), res+1, res+2]

5.2.4.2. Processing Steams in Chunks

file = open('_temporary.txt')
chunk = file.read(8192)

while chunk:
    print(chunk)
    chunk = file.read(8192)

file = open('_temporary.txt')

while chunk := file.read(8192):
    print(chunk)

5.2.4.3. Checking Match

import re

pattern = r'\w+naut$'
data = 'Astronaut'

result = re.search(pattern, data)

if result:
    print(result.group())

import re

pattern = r'\w+naut$'
data = 'Astronaut'

if (result := re.search(pattern, data)):
    print(result)

5.2.4.4. Patterns

import re

pattern = r'\w+naut$'
data = 'Astronaut'

match = re.match(pattern, data)
result = match.group() if match else None

import re

pattern = r'\w+naut$'
data = 'Astronaut'

result = re.match(pattern, data).group() if re.match(pattern, data) else None

import re

pattern = r'\w+naut$'
data = 'Astronaut'

result = res.group() if (res := re.match(pattern, data)) else None

5.2.4.5. Comprehensions

DATA = ['5.8,2.7,5.1,1.9,virginica',
        '5.1,3.5,1.4,0.2,setosa',
        '5.7,2.8,4.1,1.3,versicolor']

result = []

for line in DATA:
    X = [float(x) for x in line.split(',')[0:4]]
    result.append(X)

print(result)
# [[5.8, 2.7, 5.1, 1.9],
#  [5.1, 3.5, 1.4, 0.2],
#  [5.7, 2.8, 4.1, 1.3]]

DATA = ['5.8,2.7,5.1,1.9,virginica',
        '5.1,3.5,1.4,0.2,setosa',
        '5.7,2.8,4.1,1.3,versicolor']

result = [[float(x) for x in X]
          for line in DATA
          if (X := line.split(',')[0:4])]

print(result)
# [[5.8, 2.7, 5.1, 1.9],
#  [5.1, 3.5, 1.4, 0.2],
#  [5.7, 2.8, 4.1, 1.3]]

5.2.5. Use Case

DATA = ['5.8,2.7,5.1,1.9,virginica',
        '5.1,3.5,1.4,0.2,setosa',
        '5.7,2.8,4.1,1.3,versicolor']

result = [[float(x) for x in X] + [y]
          for line in DATA
          if (row := line.split(','))
          and (X := row[0:4])
          and (y := row[4])]

print(result)
# [[5.8, 2.7, 5.1, 1.9, 'virginica'],
#  [5.1, 3.5, 1.4, 0.2, 'setosa'],
#  [5.7, 2.8, 4.1, 1.3, 'versicolor']]

DATA = [{'is_astronaut': True,  'name': 'JaN TwarDOwski'},
        {'is_astronaut': True,  'name': 'Mark Jim WaTNey'},
        {'is_astronaut': False, 'name': 'José Maria Jiménez'},
        {'is_astronaut': True,  'name': 'Melissa Lewis'},
        {'is_astronaut': False, 'name': 'Alex Vogel'}]

result = [{'firstname': person['name'].title().split()[0],
           'lastname': person['name'].title().split()[-1]}
          for person in DATA
          if person['is_astronaut']]

result = [{'firstname': name[0],
           'lastname': name[-1]}
          for person in DATA
          if person['is_astronaut']
          and (name := person['name'].title().split())]

result = [{'firstname': fname,
           'lastname': lname}
          for person in DATA
          if person['is_astronaut']
          and (name := person['name'].title().split())
          and (fname := name[0])
          and (lname := name[-1])]

print(result)
# [{'firstname': 'Jan', 'lastname': 'Twardowski'},
#  {'firstname': 'Mark', 'lastname': 'Watney'},
#  {'firstname': 'Melissa', 'lastname': 'Lewis'}]

from dataclasses import dataclass
from pprint import pprint


@dataclass
class Iris:
    sepal_length: float
    sepal_width: float
    petal_length: float
    petal_width: float


class Versicolor(Iris):
    pass

class Virginica(Iris):
    pass

class Setosa(Iris):
    pass


DATA = [('Sepal length', 'Sepal width', 'Petal length', 'Petal width', 'Species'),
        (5.8, 2.7, 5.1, 1.9, 'virginica'),
        (5.1, 3.5, 1.4, 0.2, 'setosa'),
        (5.7, 2.8, 4.1, 1.3, 'versicolor'),
        (6.3, 2.9, 5.6, 1.8, 'virginica'),
        (6.4, 3.2, 4.5, 1.5, 'versicolor'),
        (4.7, 3.2, 1.3, 0.2, 'setosa'),
        (7.0, 3.2, 4.7, 1.4, 'versicolor')]

result = [cls(*features)
          for *features, species in DATA[1:]
          if (clsname := species.capitalize())
          and (cls := globals()[clsname])]


pprint(result)
# [Virginica(sepal_length=5.8, sepal_width=2.7, petal_length=5.1, petal_width=1.9),
#  Setosa(sepal_length=5.1, sepal_width=3.5, petal_length=1.4, petal_width=0.2),
#  Versicolor(sepal_length=5.7, sepal_width=2.8, petal_length=4.1, petal_width=1.3),
#  Virginica(sepal_length=6.3, sepal_width=2.9, petal_length=5.6, petal_width=1.8),
#  Versicolor(sepal_length=6.4, sepal_width=3.2, petal_length=4.5, petal_width=1.5),
#  Setosa(sepal_length=4.7, sepal_width=3.2, petal_length=1.3, petal_width=0.2),
#  Versicolor(sepal_length=7.0, sepal_width=3.2, petal_length=4.7, petal_width=1.4)]

5.2.6. References

pep572

Angelico, C. and Peters T. and van Rossum, G. PEP 572 -- Assignment Expressions. Python Software Foundation. 2018. Url: https://www.python.org/dev/peps/pep-0572/#abstract Accessed: 2020-12-04.

5.2.7. Assignments