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?
>> 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.
Thanks for the comments, I just added another motivating example right at the top of the README. Is it clearer now?
Not in the slightest. I still have no idea what this has to do with experiments.
Ok, I gave the motivating example another shot... not sure if it helps, but please let me know if you have any suggestions.
Thanks for the feedback. I will try to improve the example and make it more "experimental".
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.
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.