By Yuki Katoh
Sublime Text is a powerful text editor. Here I introduce how to add custom REPL config for remote/local R, Python, Scala, Spark, Hive, you name it (this is only tested for OS X).
The example below interprets local Python (top), R (middle) and Hive (bottom) code on remote.
Good IDEs are everywhere. RStudio for R, Pycharm for Python, IntelliJ for Scala. But these are specialized in one language and what I wanted to have is a tool for broad and multi-language data science tasks with autocompletion, FTP, highlighter, formatter, split editing, local/remote evaluation and REPL. I especially wanted REPL functionality that takes single inputs, evaluates them, and returns the result for quick prototyping. Sublime Text is a popular text editor with massive amount of plugins that provides quite a lot of what you need. By adding custom REPL, Sublime Text becomes an all-in-one tool for every data science task from hadoop ETL, Spark machine learning, HTML/CSS editing to markdown reporting.
The above gif setup is heavily based on the following two packages
When you have them installed, the only thing you need to do is to add a new SublimeREPL config.
First thing you need to do is to find out SublimeREPL config file location. Most probably you can find it by Sublime Text tab, Preferences, Brouse Packages, SublimeREPL, then config (I use OS X 10.10.5).
As an example, we are going to add remote_R sublime interepreter config. This should be useful when you have local R script and like to evaluate it remotelly.
cd YOURSUBLIMEREPLCONFIGFOLDER #Move to YOURSUBLIMEREPLCONFIGFOLDER
cp -r R remote_R #This will create remote_R folder
cd remote_R #Go to remote_R
open . #Open the folderYou’ll find two files in the folder.
Now we are going to give SublimeREPL access to your remote R (I assume you can SSH to your …read more
Source:: r-bloggers.com