gnu-parallel VS Python Fire

You can use GNU Parallel (https://www.gnu.org/software/parallel/) to run command-line clients with all of those queries. You can set up the upper limit of simultaneous clients run, and this will automatically handle all possible parallelism.

Some other multi machine options that have worked well for me, well beyond just compilation of C/C++ on multiple machines with multiple cores.

1) set up passwordless, ssh.

and

2) use the gnu parallel. https://www.gnu.org/software/parallel/

gnu parallel is super flexible, very useful.

How does this stack up againg GNU parallel? If you just wanna parallelize CLI work-loads (like nmap), parallel should be easier, I guess.

It requires jq for JSON processing and GNU parallel for concurrent searches in the notebooks.

Since you've got lots of images, you could use GNU Parallel to spread the job across multiple CPUs.

Gnu parallel

You could easily use something like GNU Parallel:

https://www.gnu.org/software/parallel/

The cli tool [fire](https://github.com/google/python-fire/blob/master/docs/guide...) has a nifty feature where it can generate a cli for any file for you.

So random and math are somewhat usable that way

    $ python -m fire random uniform 0 1

With python-fire you can use either function or class to create your subcommands. But I find working with classes more intuitive and manageable. Our first command is going to be a sub-command that shows us the UTC time.

Have you checked out fire? Personally, I think it's a really elegant solution to turning a callable object into command line. Plus, the chaining function calls feature lets you build some pretty complex command line patterns likes you never seen with other frameworks. Definitely worth giving it a try!

I started with click but found python fire to be so much easier to use.

I highly recommend checking out fire for adding a CLI quickly to little utility scripts that aren't going to be published to the world but just for you.

python fire autogenerates CLI wrappers for python modules, which really synergizes with method-chaining APIs like pandas.

Fire can basically do the first step (object -> CLI):

https://github.com/google/python-fire

Gooey can do (CLI -> GUI):

https://github.com/chriskiehl/Gooey

also, while we're on the subject, fire may not be the same kind of workhorse as argparse or click, but for really simple stuff it's pretty awesome

I'm relatively new to Go (coming from Python) so I haven't been using Cobra (or Go, for that matter) for long but it's clearly very polished -- only friction I was experiencing with it is there's a lot of boilerplate to creating commands and subcommands, that IMO (idea as proven by python-fire) can be naturally (better) expressed as types / fields / methods that are already built into the language.