ten-simple-rules-dockerfiles
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Ten Simple Rules for Writing Dockerfiles for Reproducible Data Science
comments about rule 10 "Regularly use and rebuild containers" For me this clearly seems to be a damage-limiting measure, acknowledging that the other 9 rules don’t ensure anything. This rule...
comments about rule 7: "Mount dataset at run time" To be reproducible, there is nothing that can be different at different runtime, all must be the same. Thus it does...
I would like to add the “Rule 0” for Writing Dockerfiles for Reproducible Artifacts" and it is: “Do not use docker”. Docker makes it hard to be reproducible, the eco...
comments about rule 3: "Format for clarity" I think this is a rule for maintenance, not for reproducibility. It could even be good in certain cases if the files (Dockerfile)...
comments about rule 8: "Make the image one-click runnable" To be reproducible, the exact data needs to be part of. So it could just be processed during the build, that...
comments about rule 5: "Specify software versions" 1. A version number is not reliable, usually it cannot be formally guaranteed that an artifact identified by name and version is unique....
comment about rule 6: "Use version control" Surely there are many reasons forcing any reasonable process to use version control, but reproducibility IMHO is not. Burning everything (all archives, the...
comment about rule 4: "Document within the dockerfile" Whether to documentation is inside the `Dockerfile`, a `README.txt` or a formal document going through processes and ending up as signed PDF...
comments about rule 2: "Build upon existing images" From my point of view this is a clear no-go. Normally we cannot know the state of an existing image – there...
comments about rule 1: Use available tools 1. All tools need to be available locally. It breaks things if people simply install something and use it, because it could be...