Hello R family,
Please, I am making a passionate plea for your help with regard to mastering docker for data science. I need to put my code into production and make my research reproducible.
I have tried and failed many times with docker and it is really frustrating. All the videos and web articles I have looked at have not done much to help. None of such videos or articles are explicit enough to help you really grasp what is going on. They all tend to just gloss over many things.
I use a Windows10 machine, I have docker desktop installed, I have successfully pulled and run the rocker R image from the hub, but I am simply unable to build an image from scratch with Dockerfile, let alone push it to an image registry. Every time I have tried, I have failed.
I understand the principles of images and containers, which make it possible for other users who do not have your software to still run your analysis on their machines. . . I get that part well. But, I am simply unable to get docker to work for me, and I need to use it in my workflow. The process looks simple enough, but I am just not able to use it.
I would like a situation where regardless of whether I am coding in R, or python, or javascript, I will be able to easily build and deploy an image of my analysis.
Therefore, I am humbly appealing to this community for any advice they may have with regard to starting off with docker on Windows, any tips and helpful resources they may have that will make it easy to quickly get started with docker and building images. I have some projects where I will need to use docker for containerization, and so I am quite desperate right now.
Please, as always, I appreciate your help. I need to put this docker hurdle behind me once and for all, and fast too. Thanks!