Linux users who want to run Windows applications without switching operating systems have been able to do so for years with Wine, software that lets apps designed for Windows run on Unix-like systems.

There has been no robust equivalent allowing Mac applications to run on Linux, perhaps no surprise given that Windows is far and away the world's most widely used desktop operating system. A developer from Prague named Luboš Doležel is trying to change that with 'Darling,' an emulation layer for OS X.

I have the urge to commit my 24' Core 2 Duo iMac to a single Linux operating system, thus giving up the goodness of my beloved Mac OS X. I am not a stranger to Linux, but I am a stranger to running Mac apps on Linux. On my PowerPC I can use SheepShaver to run Classic apps. The Mac-on-Linux project c. Installing Mac OS X features on Ubuntu 14.04 Linux commands / May 18, 2014 In this tutorial, we will explain how to converse from Ubuntu 14.04 look to Mac format by installing MacBuntu, note that this explanation applies only to Ubuntu 14.04, and for the other versions search the web. Run a macOS Virtual Machine (All Apps) The most reliable way to run Mac apps on Linux is through a virtual machine. With a free, open-source hypervisor application like VirtualBox, you can run macOS on a virtual device on your Linux machine. A properly-installed virtualized macOS environment will run all macOS apps without issue.

'The aim is to achieve binary compatible support for Darwin/OS X applications on Linux, plus provide useful tools that will aid especially in application installation,' Doležel's project page states. Darwin is Apple's open source operating system, which provides some of the backend technology in OS X and iOS. The name 'Darling' combines Darwin and Linux. Darling works by 'pars[ing] executable files for the Darwin kernel.. load[ing] them into the memory.. and execut[ing] them.'

But there is a ways to go. 'Darling needs to provide an ABI-compatible [application binary interface] set of libraries and frameworks as available on OS X.. by either directly mapping functions to those available on Linux, wrapping native functions to bridge the ABI incompatibility, or providing a re-implementation on top of other native APIs,' the project page notes.

Doležel, who started Darling a year ago, described the project and its progress in an e-mail interview with Ars. Darling is in the early stages, able to run numerous console applications but not much else. Cache clearing app mac. 'These are indeed the easiest ones to get working, albeit 'easy' is not the right word to describe the amount of work required to achieve that,' Doležel said. 'Such applications include: Midnight Commander, Bash, VIM, or Apple's GCC [GNU Compiler Collection]. I know it doesn't sound all that great, but it proves that Darling provides a solid base for further work.'

Users must compile Darling from the source code and then 'use the 'dyld' command to run an OS X executable,' Doležel said. One roadblock is actually getting Mac .dmg and .pkg application files working on a Linux system. Because doing so isn't that straightforward, Doležel said, 'I've written a FUSE module that enables users to mount .dmg files under Linux directly and without root privileges. An installer for .pkg files is underway.'

Unix/Linux synergy

The fact that OS X is a Unix operating system provides advantages in the development process. 'This saved me a lot of work,' Doležel explained. 'Instead of implementing all the 'system' APIs, it was sufficient to create simple wrappers around the ones available on Linux. I had to check every function for ABI compatibility and then test whether my wrapper works, so it wasn't as easy as it may sound.'

Another lucky break not available to Wine developers is that Apple releases some of the low-level components of OS X as open source code, 'which helped a lot with the dynamic loader and Objective-C runtime support code,' Doležel noted.

But of course, the project is an extremely difficult one. Doležel isn't the first to try it, as Darling was initially based on a separate project called 'maloader.' Doležel said he heard from another group of people 'who started a similar project before but abandoned the idea due to lack of time.'

Doležel was actually a novice to OS X development when he started Darling, being more familiar with OS X from a user's perspective than a developer's perspective. 'I have personally looked for something like Darling before, before I realized I would have to start working on it myself,' he said.

Darling relies heavily on GNUstep, an open source implementation of Apple's Cocoa API. GNUstep provides several core frameworks to Darling, and 'the answer to 'can it run this GUI app?' heavily depends on GNUstep,' Doležel said. Doležel is the only developer of Darling, using up all his spare time on the project.

No reverse-engineering

Doležel isn't reverse-engineering Apple code, noting that it could be problematic in terms of licensing and also that 'disassembling Apple's frameworks wouldn't be helpful at all because Darling and the environment it's running in is layered differently than OS X.'

The development process is a painstaking one, done one application at a time. Doležel explains:

To improve Darling, I first take or write an application I'd like to have running. If it is someone else's application, I first examine it with one of the tools that come with Darling to see what frameworks and APIs it requires. I look up the APIs that are missing in Apple's documentation; then I create stub functions for them and possibly for the rest of the framework, too. (Stub functions only print a warning when they are called but don't do any real work.)

The next step is to implement all the APIs according to the documentation and then see how the application reacts. I also add trace statements into important functions to have an insight into what's happening. I believe this is very much like what Wine developers do.

When things go wrong, I have to use GDB [GNU Debugger] to debug the original application.

It is rather unfortunate that Apple's documentation is often so poorly written; sometimes I have to experiment to figure out what the function really does. Many OS X applications seem to contain complete pieces of example code from Apple's documentation, presumably because one would have to spend a lot of time getting to understand how the APIs interact. This is why I appreciate open source so much—when the documentation is sketchy, you can always look into the code.

Years of development are needed. Similar to Wine, 'Having a list of applications known to be working is probably the best way to go,' Doležel said.

Darling should work on all Linux distributions, he said, with the catch that 'many apps for OS X are 32-bit only, and installing 32-bit packages on a 64-bit Linux system could be tricky depending on your distribution. I personally use Gentoo Linux, so I'm gradually creating a Portage overlay that would compile Darling and all dependencies for both 32-bit and 64-bit applications.'

Doležel would like to bring Angry Birds, other games, and multimedia applications to Linux. Darling could potentially 'be used to run applications compiled for iOS,' he writes on the project site. This will also be a challenge. 'The intention is to support the ARM platform on the lowest levels (the dynamic loader and the Objective-C runtime),' he writes. 'Rewriting the frameworks used on iOS is a whole different story, though.'

R is one of the main languages used for data science today. As such, it is natural that any beginner may want to know how to get started with this powerful language regardless of the operating system running on a computer. Thus, this tutorial will address this by covering the installation process of R on Windows 10, Mac OSX, and Ubuntu Linux.

Furthermore, it will also go over the installation of RStudio, which is an IDE (Integrated Development Environment) that makes R easier to use as well as how to install R packages such as dplyr or ggplot2.

Installing R on Windows 10

Installing R on Windows 10 is very straightforward. The easiest way is to install it through CRAN, which stands for The Comprehensive R Archive Network. Just visit the CRAN downloads page and follow the links as shown in the video below:

Once the download is finished, you will obtain a file named 'R-3.6.3-win.exe' or similar depending on the version of R that you download. The links shown in the video above will take you to the most recent version. To finish installing R on your computer, all that is left to do is to run the .exe file. Most of the time, you will likely want to go with the defaults, so click the button 'Next' until the process is complete, as shown in the video below. Note that, even though I do not do so, you can add desktop or quick start shortcuts during the process.

Installing RStudio

Once R is installed, you can proceed to install the RStudio IDE to have a much-improved environment to work in your R scripts. It includes a console that supports direct code execution and tools for plotting and keeping track of your variables in the workspace, among other features. The installation process is very straightforward, as well. Simply go to the RStudio downloads page and follow the video below:

Once the download is complete, you will get a file named 'RStudio-1.2.5033.exe' or similar. Again this will be dependent on the version. To complete the installation, it is as easy as before. Just run the previously mentioned .exe file with the default settings by clicking 'Next', and wait until the installation finishes. Bear in mind that RStudio requires that R is installed beforehand.

Installing Packages in R

Now you have base R installed on your system and a nice IDE to begin your R programming journey. However, base R is rather limited in the things that it can do, which is why we have R packages such as dplyr for enhanced,'ggplot2'))

The second is shown in the video below. It is an easy-to-use graphical interface built into RStudio from which you can search and download any R package available on CRAN.

Installing R on Mac OSX

Installing R on Mac OS is similar to Windows. Once again, The easiest way is to install it through CRAN by going to the CRAN downloads page and following the links as shown in the video below:

The next step is to click on the 'R-3.6.2.pkg' (or newer version) file to begin the installation. You can leave the default options as is just like for Windows.

Installing RStudio and R packages

This process is essentially the same as in Windows. To download RStudio, go to the RStudio downloads page and get the .dmg for Mac OS, as shown in the image below. Remember to keep default installation options.

Once you open RStudio, installing packages is the same as with Windows. You can use either install.packages(c('dplyr','ggplot2')) in the console or go ahead and use the graphical interface shown in the video under the installing packages in R subsection of this tutorial.

Installing R on Ubuntu 19.04/18.04/16.04

Installing R on Ubuntu maybe a little bit more tricky for those unused to working in the command line. However, it is perhaps just as easy as with Windows or Mac OS. Before you start, make sure to have root access in order to use sudo.

As it is common, prior to installing R, let us update the system package index and upgrade all our installed packages using the following two commands:

sudo apt update

sudo apt -y upgrade

After that, all that you have to do is run the following in the command line to install base R.

sudo apt -y install r-base

Installing RStudio and R Packages

Once base R is installed, you can go ahead and install RStudio. For that we are going to head over again to the RStudio downloads page and download the .deb file for our Ubuntu version as shown in the image below:

Once you have the .deb file, all that is left is to navigate to your downloads folder using cd Downloads in the command line and then run the following command to begin the installation process:

Mac Os X Leopard Install

sudo dpkg -i rstudio-1.2.5033-amd64.deb

You may encounter some dependency problems that may cause your first try to install RStudio to fail, but this has an easy fix. Just run the following command and try again:

Download For Mac Os X

sudo apt -f install

When the process finishes, you will have an RStudio shortcut in your Ubuntu app list, but you will also be able to start RStudio by typing rstudio in the command line.

Once you open RStudio, installing packages can be done in the exact same manner as with Windows or Mac OS. Either by typing install.packages(c('dplyr','ggplot2')) in the console or using the graphical interface shown in the video under the installing packages in R subsection of this tutorial

Conclusion

I hope that this tutorial will help those of you eager to dive into the world of R programming regardless of your operating system choice. If you are looking to start learning R as such after installing it, please refer to the Introduction to R course, which will guide you through the basics of R programming. Keep learning; the sky is the limit.