Just two days ago working in Rstudio, thought my script ran fine, but actually the data loading part failed but Rstudio charges on despite errors and runs the r

Just two days ago working in Rstudio, thought my script ran fine, but actually the data loading part failed but Rstudio charges on despite errors and runs the rest of the script on the data that was still in memory from another script I had run the day before! But I don't have a satisfactory solution to handle the problem where Step A takes a few minutes or longer to complete and so I don't want to keep re-running it while coding Step B. I resort to copy-and-pasting Part B into ipython which amounts to being a poor-man's notebook. Obviously the "correct" answer is to write out the results of A to disk but this is can be a lot of a pain while you're developing! (Eg: loading an excel sheet in pandas is slow, while the equivalent tab-separated sheet is very fast, but I don't really want to have a separate step pre-processing all excel sheets into tsv files.) Also, pandas to_csv/read_csv functions aren't even inverses of each other (they lose the index) so writing to desk requires extra steps. (And from_csv is deprecated.) What I'd rather have is "half" a notebook where I can checkpoint a computation part way through and restart from there. But only ever proceed linearly through the code to avoid notebook out-of-order confusion.