R

Using renv is an excellent choice for maintaining a clean and reproducible R environment on macOS. Here, I will share my experiences and provide a guide on setting up R on macOS. The post is divided into the following sections: Installing system dependencies required for R libraries using Homebrew. Installing R libraries using renv. Saving and restoring R environments using renv. Installing R libraries hosted on private repositories. Building R libraries from source using Makevars....

When developing in Python, it is generally a good practice not to rely on the Python version that ships with the operating system (OS). This is to ensure that the system version of Python remains relatively ‘clean’ for the OS processes. In addition, by installing a custom version(s) of Python, we open many possibilities. For one, it gives us control over which specific version(s) to use in our projects, and two, by using a virtual environment manager, we ensure that each project has access to its own tailored list of packages....

If you are facing difficulties with large data sets in R, using data.table could provide a performance boost. However, when loading data.table, especially on macOS, you might encounter a warning indicating the absence of OpenMP support, causing data.table to operate in a single-threaded mode. This limitation prevents you from fully utilizing the potential benefits of using data.table and taking advantage of the underlying hardware. 1library(data.table) 2data.table 1.14.0 using 1 threads (see ?...