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git clone https://dagshub.com/mrd/DIB_COVID19_paper.git
This will copy the git repository to your computer. After that, move into the directory by typing:
cd DIB_COVID19_paper
If you're on GNU/Linux, you can install DVC with pip:
pip install dvc
More install options here.
If you move into data/preprocessed/ you will see that the folder is empty. Yes, it is, dataset files should not be there, afterall they are not tracked by git. The same thing applied to data/raw. It is not recommended to track big files and objects with git. The documentation folder folder will not be there either (though you can see the documentation.dvc file there, which means DVC tracks it ).
dvc pull
It's the same reasoning as if you wanted to get the latest tracked code by git (git pull). Now you will find the files in the data/raw and data/preprocessed files, and also the documentation files in the documentation folder.
Let's say you have an updated version of one or more of the raw files, on the same format (column names did not change, for example), and you want to reproduce the pipeline (generate an updated version of the preprocessed file). From the root directory of the repository, run:
dvc repro preprocess.dvc
DVC will automatically notice that one of the raw files changed and therefore it will reproduce the pipeline and generate a new output file in the data/preprocessed folder. If nothing changed, dvc will realize there is no reason to reproduce the pipeline and you will see the following message:
Data and pipelines are up to date.
Well, maybe you want to force a reproduction fo the pipeline because... well, you want to see how it would be like. For this, you should run:
dvc repro -f preprocess.dvc
This final dataset can also be downloaded from Mendeley Data by clicking here.
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Are you sure you want to delete this access key?