Comments (4)
Hm, I'm a bit confused by this, also from the manual, which seems to suggest you cannot combine the above two functions into one function:
Targets with the "file" format are called dynamic files, and these targets are unusual because their return values do not get saved in the _targets/objects/ folder. Rather, they expect you to return a character vector files and directories, which gets stored in the _targets/meta spreadsheet, and then targets watches the data at those paths for changes.
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But does section 4.3 of the manual suggest that we could create an imported function that both loads (or saves) the file, but still returns a file path.
from comparing-sentiment.
Good point! You can save targets objects as external files and return their path, but then you need to re-read in that path in order to reference these objects inside the pipeline at later target steps. In short: If you want to keep referencing data frames without an additional read-in step, you need to make these two steps. At some points it makes sense to save targets objects externally but I think its not the best idea to do it at all steps. Lastly, I think that tar_target(ss_scale_file, read.table(here("data-sentiment", "sentistrength_scale.txt"), sep="\t", header = T, quote=""), format="file"),
would not work since a data object would be returned by the type expects a path/string. Will touch on that in the meeting later today!
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Related Issues (11)
- Line in the plan about exploring different subsets of the data HOT 2
- where are raw data files saved? HOT 3
- status_id variable is behaving correctly? HOT 9
- make create_raw_data faster? HOT 3
- Error when accessing dictionaries HOT 2
- successfully ran the entire list of targets! HOT 1
- recursively adding replies HOT 5
- identifying common threads
- code to access consensus code is up! HOT 19
- master branch after merge HOT 4
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