Show HN: Pyexperiment

Re:Show HN: Pyexperiment by jackmaney on Sunday August 09, 2015 @04:29AM (#10029859)

I...I really don't understand what the primary use-cases are for this library. By "experiment", do you mean some kind of scientific experiment? A double-blind study on file input? That...doesn't make a whole lot of sense, but that's the closest thing that I can glean from a skim of the first documentation page that makes any sense at all...

    Motivating Example
    Let’s assume we need to write a quick and clean script that
    reads a couple of files with time series data and computes
    the average value. We also want to generate a plot of the
    data.

That...provides no motivation whatsoever. If I want to do that, I'll use Pandas and matplotlib. This example sheds absolutely no light on what pyexperiment does or why I would want to use it.

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Re:Show HN: Pyexperiment by duerrp on Sunday August 09, 2015 @04:36AM (#10029872)

Pandas and matplotlib are great, I use them all the time. Yet whenever I write a python script for such experiments, beyond some point, I find myself writing code that parses command line arguments, handles simple configuration options, saves the results of my computation in a shareable way, etc.

Pyexperiment collects these bits and pieces into a library where I can just write the relevant stuff - it's mainly solving my own pain-point and I thought I could share it.

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Re:Show HN: Pyexperiment by jackmaney on Sunday August 09, 2015 @04:40AM (#10029877)

So...it's for configuration management? What do "experiments" have to do with this?

What does this package do that isn't done by click, docopt, or argparse?

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Re:Show HN: Pyexperiment by duerrp on Sunday August 09, 2015 @04:47AM (#10029888)

>> So...it's for configuration management? What do >> "experiments" have to do with this?

Yes and no, pyexperiment handles configuration management for you (by using argparse and configobj etc.), but it's main point is that it saves you from having to set up these components. My main goal was to reduce the overhead of writing the same "framework" code every time, so pyexperiment sets you up with simple one-command solutions for many common tasks.

>> What does this package do that isn't done by click, >> docopt, or argparse?

It will set you up with a framework where e.g., you don't have to write the same boilerplate code to get a multiprocessing cabable logger that logs to a file. You just call log.debug("bla") and that's it.

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Re:Show HN: Pyexperiment by duerrp on Sunday August 09, 2015 @08:18AM (#10030130)

Thanks for the comments, I just added another motivating example right at the top of the README. Is it clearer now?

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Re:Show HN: Pyexperiment by jackmaney on Sunday August 09, 2015 @02:29PM (#10030980)

Not in the slightest. I still have no idea what this has to do with experiments.

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Re:Show HN: Pyexperiment by duerrp on Thursday August 13, 2015 @10:39PM (#10058349)

Ok, I gave the motivating example another shot... not sure if it helps, but please let me know if you have any suggestions.

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Re:Show HN: Pyexperiment by duerrp on Monday August 10, 2015 @11:24PM (#10038936)

Thanks for the feedback. I will try to improve the example and make it more "experimental".

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Re:Show HN: Pyexperiment by zenojevski on Sunday August 09, 2015 @04:42AM (#10029881)

I think most people would refer to this as a "boilerplate" or "project template", even if it is not exactly so. You may have more luck explaining it to people using these terms.

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Re:Show HN: Pyexperiment by duerrp on Sunday August 09, 2015 @07:41AM (#10030079)

Thanks, I'll try to rephrase the readme...

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