ralf | combine Amazon S3 log files and merge and convert to Apache | AWS library

The %d convention is simply a C printout format and as mentioned in KenS comment cannot be "offset"

see https://www.ghostscript.com/doc/current/Use.htm#One_page_per_file

but there are workarounds mentioned in How to set printf %d offset for Ghostscript?

However they are perhaps not the most efficient, but may help in some cases, just beware the comments below them.

The simplest way I will alter the range is to apply a preset such as

1%d to produce 10 11 12..., or

2%02d = 201 202 ...

Again you are limited to the first page will always be ###1 and if you need it to start at ###5 then you need to rename all files post production. That can often be easily scripted depending how well you prepare the desired names.

The below example should get you going for now!

You define an array of objects by simply putting [] after the type, so Volume[]

At the bottom of the snippet are 2 examples that show how to access the volumes data too.

Would this be what you are after?

I think this solves your problem:

Just to expand on Steve's comment.

Example or dbFiddle

You want to convert an array of Rate (ie [Rate]) into an Array of Double (ie Double), where it will be filled with the value of each Rate.

That's a job for map()! It does exactly that: iterate over the initial array, for each element (here a Rate element) return what you want to extract from it (here just its property value).

Quick answer and "Swifty" one:

You are getting the TypeError because your Result is a list of dictionaries.
Make sure to iterate through Result and process each dictionary separately.
Your Result object is like this [{}, {}, {} ...]

Also you shouldn't capitalize the first letter of your variable. You should name it results, because it may contain more than 1 result.

I'm not going into detail of your code, but instead lets have a look at the problem and the knapsack-like solution.

Basically, the relevant properties of your solution are value and weight, where weight is constrained and a solution A is better than solution B, if A.value > B.value or if A.value = B.value AND A.weight < B.weight as long as A and B satisfy the constraint.

So, given a list of potential items [item1, [others...]], where a solution including items1 is possible, you need to find the better solution