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When working in python for research I often end up with some problem where I want to compare a result over a different number of parameters.

params1 = [0.1, 0.2, 0.3]
params2 = [5, 10, 50]
parmas3 = range(8)

for (p1, p2, p3) in itertools.product(params1, params2, params3):
    result = evaluate(p1, p2, p3)

Is there some module or framework to manage a setup like this for many parameters, where I have a good way to

  • save the results
  • plot and analyse them conveniently
  • probably running multiple experiments in parallel
  • maybe even some caching and saving of intermediate results (e.g. if you want to continue the run later

I was thinking that this must be a pretty common pattern, but I was not able to find something that even slightly goes into this direction.

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  • I think this is off topic for this particular site as it is a question about programming and not of finding an existing piece of software. You might consider Stack Overflow. – Eric S Jan 21 at 16:59
  • Did you read the question? – Christian Jan 21 at 17:08
  • Yes and the answer is that you are going to have to write a Python program to execute those tasks. This particular site is not about how to write Python programs. Just so you know, I am not the downvoter, but I'm guessing they think its off topic too. – Eric S Jan 21 at 17:10
  • Sorry, my last comment was slightly passive-aggressive. I edited my question and tried to make it more clear that I am in fact looking for a python module, which would be a piece of software. I pretty clearly know how I would do something like this myself, this is not what I am asking. But I was hoping to save some work, because I think it is a common problem and there must be some piece of software that does this already. So I came here. – Christian Jan 21 at 17:11
  • Could you please remove your downvote, because it does not help to find an answer? – Christian Jan 21 at 17:14
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I'm not aware of a library that does everything you want (which doesn't mean it doesn't exist), and I suspect you will need to write code. That said, I do recommend you learn about the Pandas library. Pandas provides DataFrames which is a great way to organize such calculations. Once you have a DataFrames, things like data manipulation, IO and plotting are greatly eased. Pandas is very popular with data scientists.

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