Specifically when working with numbers (something scientists do), i feel it is more important to know the numbers and have an intuition of what is important to get right and what is less important. Rather than spreading unit tests and the following abstractions all over the place.
But scientists can create a hot mess too. This is when they don't care about the code enough to minify it. I.e. reducing the code to what is necessary.
Number of lines of code matter.
So the perfect blend here is not necessarily the person that follows all engineering practices. But the person has the domain knowledge but that knows enough about software practices to be able to write concise code.
If you are either missing out on the domain knowledge - or the ability to reduce the code - then it will derail.
Shipping the notebook to engineering department will not be the solution. They will break the code into pieces, follow best practices but miss out on the important.
And another aspect of this practice is that if someone finds a problem, the scientist will not be able to modify or re-run the engineered version of the notebook.
Specifically when working with numbers (something scientists do), i feel it is more important to know the numbers and have an intuition of what is important to get right and what is less important. Rather than spreading unit tests and the following abstractions all over the place.
But scientists can create a hot mess too. This is when they don't care about the code enough to minify it. I.e. reducing the code to what is necessary.
Number of lines of code matter.
So the perfect blend here is not necessarily the person that follows all engineering practices. But the person has the domain knowledge but that knows enough about software practices to be able to write concise code.
If you are either missing out on the domain knowledge - or the ability to reduce the code - then it will derail.
Shipping the notebook to engineering department will not be the solution. They will break the code into pieces, follow best practices but miss out on the important.
And another aspect of this practice is that if someone finds a problem, the scientist will not be able to modify or re-run the engineered version of the notebook.