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There are definitely uses cases for Ruby without Rails. It's a great command-line scripting language, for example, filling the slot of an evolved Perl. There ar

There are definitely uses cases for Ruby without Rails. It's a great command-line scripting language, for example, filling the slot of an evolved Perl. There are also lighter-weight approaches to web scripting, such as Sinatra and bare Rack HTTP servers. I have no idea how prevalent that is. I did it for several small but well used apps. Ruby and Python share a lot of commonalities as languages. But their constituencies vary substantially, and that matters. Academic, probably Python. Working "interactive" agency, probably Ruby. Process automation, probably Ruby again. Author's implementation of new algo paper, probably Python. I wouldn't think either-or. If it's worth familiarizing with one, it's probably one more weekend to be walk-on-ready for both.

berkes 5y ago
As a Ruby developer, I really fail to see any benefit or Ruby over Python (or even Node) for commandline scripting. Other than "I already know Ruby". In fact, I'll often go for the -for me- more unfamiliar Python for such tools. Knowing it will cost me more effort, but also knowing that the libraries, documentation, education and off-the-shelve solutions are far, far better and move available.
- heartbreak 5y ago
  If nothing else, Python’s miserable package management ecosystem makes me reach for Ruby instead. I’ll take Bundler over requirements.txt, pipenv, poetry, etc. any day.
- montblanc 5y ago
  What have you built lately in Python/Node that "the libraries, documentation, education and off-the-shelve solutions are far, far better and move available." ? I'm not saying those use cases don't exist at all, but I don't think it's as common as you're making it up to be. As a Ruby dev the last 8 years I didn't have many times when some key functionality was only available in Python/Node. I can see it happening in web crawling or data science but those aren't common to every day web development.
  - berkes 5y ago
    Panda's et all do investigate Data. There are tools in Ruby for Datascience but the resources are thin or completely lacking. A scraper using Scrapy. Had a tool in Ruby with Hydra (multitreaded) and message cueus and whatnot to speed it up. Spidy is just faster. Not because of the language, but because the tooling is much further along and has far more effort poored into. Server/infra management: ported from chef to ansible. Not for speed, but because stability and availability (of a.o. resources). Unexpected side-effect was that ansible was actually faster and used far less resources on the servers (chef-deamon was notoriously bad). Not sure why, but I don't think its the language design. FluentD, moved to flowgger and plain-old-syslog. FluentD is an awesome piece of software, but it was hogging our (micro)servers enough to be noticable, measurable and show up in the billing (as higher CPU/memory vpses).

berkes 5y ago

As a Ruby developer, I really fail to see any benefit or Ruby over Python (or even Node) for commandline scripting. Other than "I already know Ruby". In fact, I'll often go for the -for me- more unfamiliar Python for such tools. Knowing it will cost me more effort, but also knowing that the libraries, documentation, education and off-the-shelve solutions are far, far better and move available.

heartbreak 5y ago
If nothing else, Python’s miserable package management ecosystem makes me reach for Ruby instead. I’ll take Bundler over requirements.txt, pipenv, poetry, etc. any day.
montblanc 5y ago
What have you built lately in Python/Node that "the libraries, documentation, education and off-the-shelve solutions are far, far better and move available." ? I'm not saying those use cases don't exist at all, but I don't think it's as common as you're making it up to be. As a Ruby dev the last 8 years I didn't have many times when some key functionality was only available in Python/Node. I can see it happening in web crawling or data science but those aren't common to every day web development.
- berkes 5y ago
  Panda's et all do investigate Data. There are tools in Ruby for Datascience but the resources are thin or completely lacking. A scraper using Scrapy. Had a tool in Ruby with Hydra (multitreaded) and message cueus and whatnot to speed it up. Spidy is just faster. Not because of the language, but because the tooling is much further along and has far more effort poored into. Server/infra management: ported from chef to ansible. Not for speed, but because stability and availability (of a.o. resources). Unexpected side-effect was that ansible was actually faster and used far less resources on the servers (chef-deamon was notoriously bad). Not sure why, but I don't think its the language design. FluentD, moved to flowgger and plain-old-syslog. FluentD is an awesome piece of software, but it was hogging our (micro)servers enough to be noticable, measurable and show up in the billing (as higher CPU/memory vpses).