[Hackaton 2024][Coach Team][Python] Copying a list using `list.append(x)` within a loop is not energy efficient. (Rule example for Hackaton spotter - measure justification)

[jhertout]

Rule title

Using list.append(x) within a loop is not energy efficient.

Language and platform

Python.

Rule description

Using list.append(x) within a loop to copy a list is not energy efficient. Prefer the usage of native methods which are more energy friendly.

Noncompliant Code Example

    list = [1, 2, 3, 4, 5]
    new_list = []
    for item in list:
        new_list.append(item)

Compliant Solution

    list = [1, 2, 3, 4, 5]
    new_list = []
    new_list = list.copy()

Rule short description

Using list.append(x) within a loop is not energy efficient.

Rule justification

Here are some measures performed using RAPL on a computer with a CPU Intel(R) Xeon(R) CPU E3-1245 v5 @ 3.50GHz. This computer was running only the tests but to limit the impact of perturbation on the results, the tests were performed several time.

Tested code (non compliant)

list = ['1', '2']
for i in range(5000000):
   new_list = []
   for item in list:
       new_list.append(item)

Tested code (compliant)

list = ['1', '2']
for i in range(5000000):
    list.copy()

We perform the copy of a list using two different methods (append or list.copy) and we perform the copy 5000000 time. The test was done 5 time for each function and there is the result:

append in loop

Number of iteration	Consumption (Joules)
1	1723.98
2	1813.46
3	1885.35
4	1800.87
5	1744.04

list.copy

Number of iteration	Consumption (Joules)
1	626.35
2	616.29
3	620.61
4	621.93
5	615.08

Conclusion: as we can see using list.copy() is more energy efficient in this simple case. More tests should be done using a bigger list or other type of list but we clearly have the tendency for the rule definition.

Severity / Remediation Cost

Estimate the severity and remediation cost of your issue.

• Severity: Minor - the impact of the bad practice is not so important unless the call to the impacted function is called a lot of time (million of time, but that may happen).
• Remediation cost: Easy - alternative energy efficient functions exists in Python. The code requires a little refactor but not very complicated.

Implementation principle

• Search for a "for" loop
• Search for calls of append() function
• If the caller of the function is a list, report the line

[dedece35]

my first review ok