Basically how many elements are there in x.
So those many times so Lebovitz for every element in range.
I just want that for every index I would want said to contain X of my class Y of-I.
Right.
I just want to add each element of X and Y and I put them in a new list that is set right.
So that's the in.
So now I can just calculate the time after getting the point in motion either.
Right.
So I can see all CIOs set is equal to x.
So now I can just calculate the time once again and say time that time.
And that was written to me what it returns to me I'm going to store that in T-2 or that's going to be
that's going to be T-2 out here.
So can you tell me what would be the time taken.
Do you know of you're creating a list in Python you're creating another list and you're creating a third
list which is which is an additional tool.
So you're doing a lot of manipulation on the list and you're calculating the time taken at the start
and at the end of doing this entire manipulation.
So all this function is going to the tonus all this function is going to return is T-2 minus T-1 that
it's going to return the time taken for you know basically how much time you took to finish you know
at the end time minus the time taken at the start.
So now I'm going to get the weapon which is the calquing time.
That's number one in number.
How do I create.
You can of course create within that.
As I told you.
But a better way to create it without using less front now is you know again I'm going to time that
time first before starting up with a number sorry and then we're here I'm going to say x is equal to
instead of using the range function I'm going to use another function and Bedacht that is an idle function.
There's another method in the library and that mattered or that function is called as you can have a
look alien.
It's called as an image.
And then of course range also requires a particular you know you can given you can given certain values
out there you can you can just say what is the size of the vector that you require.
Now as we toss it again you create that y is equal to that range constant.
And let me say T-2 is equal to.
OK sorry I need to say is dead is equal to.
I can directly do X plus light.
That's the beauty of not by without going into a 4.
Right.
So T-2 will be equal to time that time once again after I give the entire thing done.
So now all I have to do is turn t2 minus minus 1.
And with this done what I can do is I can call these functions anytime I want.
Right.
So I can call them any time.
So how do we call them.
I'm going to say import time.
And let me say I'm going to call all these functions I'm going to call these methods and I'm going to
call them.
So when I call them let's say the Kal time Pie-Wagon and I'm going to call the Kal time.
Right.
So both of them are going to return to me some values which I'm going to printed up right.
So that's the time which will return for both of them.
I trained them both up.
OK let me run it.
Oh it saves you a Boyne's you.
Why.
Because the time taken is very very rarely very less.
And that's that's quite that's sartain to show out here because it shows it more accurately just a second.
So what we can have is let me just do something.
What are we going to do was just sprint
let's print both of them together first and
I'm going to say come on and you called them once again.
OK.
So Peyton will still take some time as you can see but NUMP is too fast.
If you keep running it again and again you will get different time.
So what I can do is I can just put them in a for loop and just check it up for I in range 10.
OK.
I want to print whatever you do.
Numbers are so fast that it's always going to be weeks.
It's like as though there's hardly any time numpad is that you can have a look the number one whereas
the other one still takes a few seconds to do or a few milliseconds to get things done.
So this is about this is about number three so you can have a look how time efficient a number that
is.
So why are are time efficient and that's the beauty of.
That's the beauty of an umpire.
So numb players as we saw a number of areas are time efficient.
That's number one.
And they consume much less space.
So these are the two main differences between now play areas and analyst because of which non-pay is
here to stay.
Right.
Think.