Imaginary Journey

Walrus operator, or assignment expression, was introduced into Python at version 3.8. This saves some additional line of assignment in storing-and-checking scenario following evaluations.

However, it also brings the containers data types, such as a list, a step closer to the Turing completeness. Following is a piece of real code:

[d:=get_scans(fn),b:=d[0],c:=d[1],c[np.isin(b,bs)][np.argsort(b)]][-1]

Or, in a more structured format:

[
    d:=get_scans(fn),
    b:=d[0],
    c:=d[1],
    c[np.isin(b,bs)][np.argsort(b)]
][-1]

This performs some additional processing from the result returned by get_scans(fn) and turn the whole thing into a value by extracting the last element of the list. One application of this kind of composite expressions is the possibility of replacing traditional loops with list comprehension. For example, without assignment expressions, we need a loop to collect the data:

r = []
for fn in fns:
    [b,c] = get_scans(fn)[:2]
    r.append(c[np.isin(b,bs)][np.argsort(b)])
r = np.array(r)

Using the walrus operator, we can do it in “one-line” (which is broken down to several lines for clarity):

r = np.array([[
    d:=get_scans(fn),b:=d[0],c:=d[1],
    c[np.isin(b,bs)][np.argsort(b)]
][-1] for fn in fns])

Some may consider this is an abuse of the container types of Python. But, as long as it is used with care, it can help to make elegant code without hindering readability.