There's An OPTIMIZED Way To Do THIS In Python (ft. enumerate)

Here's a quick optimization that you can perform in Python with enumerate().

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00:00 Intro
00:10 enumerate()
01:38 The tests
03:53 A good optimisation?
04:14 That’s it

[cerealport]

For the occasions where "start" with enumerate has been really useful for me, I define the start as a variable because it depends on some other conditions. Then I refer to that variable via "start=". I think having the start value somewhere other than with "start=" is less readable, but each to their own, I guess.

[xelxen]

Loved the video! Which IDE is that tho?

[HerculeanYT]

Correct me if I am incorrect, could you not have just done the following for the enumerate function?:
temp_list = list(enumerate(values, start=1))

[kamurashev]

Is it the same if you first time normal and then the “start=1” solution?
It’s not very accurate to benchmark like this.
First timed would be in worst condition, starting with the system that is not yet heated up.
Ideally this should be 2 separate programs and you should start it separate with a propped benchmarking tool that performs several heat up runs and then several measurement runs and calculate the average.

[kite]

look at this code below
for key, group by groupby(enumerate(numbers, start=1), lambda x: x[1] - x[0])
i can't set i + 1) use start instead, it more readable

[HoSza]

Writing start= is especially better if you use the value more than once.

[the_huge_knight]

Why I need to use that "enumerate" function instead of "for _ in sth" with definition of list_index = 0 and in the cycle I can just increment that index. Indexes often are not required in iterations.

[InterpretingYou]

Python 11 shaving off time, by making both implementations slower 🙃 @ 3:41