For example, PostgreSQL supports Python out of the box as a lang for writing sprocs and functions. However, the big issue that Ruby faces is that Python is default supported out of the box, and as such gains more traction in a cyclicle way. Doing things to collections of data is just straight up pleasant in Ruby, and data science is all about doing things to collections. Sequel (Ruby's premier DB abstraction) is quite a bit more sensible (to me) than SQL Alchemy (Python's premier DB abstraction). I think there are some parts of it that Ruby totally slays at: particularly data creation and fixing. I use them regularly to organize, normalize, and deliver ~8 million price facts each week, from ~40,000 unique products from ~150 different sources. These three tools are my bread and butter. The CSV and JSON libraries are robust as well. With Ruby, it's baked into the basic building blocks (String, Hash, Array - they are all super smart). With Python, you have to go a bit out of your way to get powerful functionality through modules that aren't included by default. This is something I find to be a notable difference between Ruby and Python. Most everything else I lean on heavily is baked into the standard library. It also makes it much easier to learn Ruby, by showing you what moves an object knows, docs, and source code. It's the thing that I think is most valuable when working with data, as it makes it incredibly easy to explore and test your theories. It's very simple to use, extremely powerful, and more performant than ActiveRecord (the other default db toolkit). You can use it to organize complex data processing pipelines, and easily re-use logic from your domain. Some of the above problems might just be my own lacking experience with Ruby, but installations of gem should just work seamlessly and not be a cause of headaches. I have all the respect in the world for the people who dedicate their time to develop open source software and provide gems/libraries like these.
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