Compare Manhattan distance calculations implemented in python

twitter.sh

# https://twitter.com/IsntTrivial/status/1344185584013742086
echo "sum(map(abs, map(operator.sub, p, q)))"
python -m timeit \
    -s "import operator;p=q=range(-10_000, 10_000, 1);" \
    -s "def manhattan_distance(p, q): return sum(map(abs, map(operator.sub, p, q)))" \
    "manhattan_distance(p, q)"
echo ""

echo "sum(abs(x - y) for x, y in zip(p, q))"
python -m timeit \
    -s "p=q=range(-10_000, 10_000, 1);" \
    -s "def manhattan_distance(p, q): return sum(abs(x - y) for x, y in zip(p, q))" \
    "manhattan_distance(p, q)"
echo ""

echo "sum([abs(x - y) for x, y in zip(p, q)])"
python -m timeit \
    -s "p=q=range(-10_000, 10_000, 1);" \
    -s "def manhattan_distance(p, q): return sum([abs(x - y) for x, y in zip(p, q)])" \
    "manhattan_distance(p, q)"

sum(map(abs, map(operator.sub, p, q)))
200 loops, best of 5: 1.68 msec per loop

sum(abs(x - y) for x, y in zip(p, q))
100 loops, best of 5: 2.5 msec per loop

sum([abs(x - y) for x, y in zip(p, q)])
100 loops, best of 5: 2.24 msec per loop