Use stricter check to bypass validation of x[]

[Bisaloo]

This ensures that object manipulated by [ via dplyr function are still validated. See the report in

#884 (comment).

library(scoringutils)
#> Note: scoringutils is currently undergoing major development changes (with an update planned for the first quarter of 2024). We would very much appreciate your opinions and feedback on what should be included in this major update: https://github.com/epiforecasts/scoringutils/discussions/333

f <- as_forecast_quantile(example_quantile)
#> ℹ Some rows containing NA values may be removed. This is fine if not
#>   unexpected.
f <- f |> 
  dplyr::select(-observed)
#> Warning: ! Error in validating forecast object: Error : Assertion on 'data' failed:
#>   Column 'observed' not found in data.

^{Created on 2024-08-27 with reprex v2.1.1}

I could add tests for this but it would mean adding dplyr as Suggests.

[seabbs]

I could add tests for this but it would mean adding dplyr as

What about adding to the testthat config and only running the tests if dplyr is installed (i.e only on our CI). Might be a bit of a hack

[nikosbosse]

Sweet, thanks a lot!

What about adding to the testthat config and only running the tests if dplyr is installed (i.e only on our CI). Might be a bit of a hack

I like this

[Bisaloo]

What about adding to the testthat config and only running the tests if dplyr is installed (i.e only on our CI). Might be a bit of a hack

From what I remember, this doesn't solve the issue since R CMD check sees library(dplyr) or dplyr:: in the tests (even if guarded with skip_if_not_installed()) and gives a warning if it's not listed as a dependency.

[nikosbosse]

Thank so much, @Bisaloo !