circuitpython/tests/internal_bench/arrayop-1-list_inplace.py

# Array operation
# Type: list, inplace operation using for. What's good about this
# method is that it doesn't require any extra memory allocation.
import bench


def test(num):
    for i in iter(range(num // 10000)):
        arr = [0] * 1000
        for i in range(len(arr)):
            arr[i] += 1


bench.run(test)
bench: Add test for map() vs inplace operations in array-likes. map() is 5 times slower. That's mostly because of inefficiency of creating containers from iterables of unknown length (like map()). 2014-06-19 21:54:51 +03:00			`# Array operation`
			`# Type: list, inplace operation using for. What's good about this`
			`# method is that it doesn't require any extra memory allocation.`
			`import bench`

run code formatting script 2021-03-15 19:27:36 +05:30
bench: Add test for map() vs inplace operations in array-likes. map() is 5 times slower. That's mostly because of inefficiency of creating containers from iterables of unknown length (like map()). 2014-06-19 21:54:51 +03:00			`def test(num):`
run code formatting script 2021-03-15 19:27:36 +05:30			`for i in iter(range(num // 10000)):`
bench: Add test for map() vs inplace operations in array-likes. map() is 5 times slower. That's mostly because of inefficiency of creating containers from iterables of unknown length (like map()). 2014-06-19 21:54:51 +03:00			`arr = [0] * 1000`
			`for i in range(len(arr)):`
			`arr[i] += 1`

run code formatting script 2021-03-15 19:27:36 +05:30
bench: Add test for map() vs inplace operations in array-likes. map() is 5 times slower. That's mostly because of inefficiency of creating containers from iterables of unknown length (like map()). 2014-06-19 21:54:51 +03:00			`bench.run(test)`