Error in `data_filter()` when rendering Rmd with `lapply()`

[etiennebacher]

Reprex:

• save this in "vignettes/reprex.Rmd"

---
output: rmarkdown::html_document
---

```{r}
dat <- data.frame() # dataset doesn't matter here
test <- c("a", "b", "c")
x <- "a"

data_filter(dat, x %in% test)
```

• remove all objects from global env
• run lapply("vignettes/reprex.Rmd", rmarkdown::render)

Originally posted by @etiennebacher in easystats/easystats#356 (comment)

[etiennebacher]

Also errors with purrr::map()

[strengejacke]

Now that we have .dynEval() and the experience with data_modify(), we could probably revise the code for data_filter(), to make it work with string variables?

[etiennebacher]

Simpler reprex:

library(datawizard)
lapply(1, \(x) {
  dat <- data.frame() # dataset doesn't matter here
  test <- c("a", "b", "c")
  x <- "a"
  
  data_filter(dat, x %in% test)
})
#> Error: Filtering did not work. Please check the syntax of your conditions.

^{Created on 2023-09-30 with reprex v2.0.2}

[etiennebacher]

The problem is that the .dynEval() call here is problematic:

datawizard/R/data_match.R

Line 209 in ec6a9ce

eval_symbol <- .dynEval(symbol, ifnotfound = NULL)

x is already defined in the function (it's the name of the dataframe argument) and will be (incorrectly) evaluated by .dynEval(). Even if we could start the search for x in the parent environment to avoid this, we'd still need to evaluate x in its dataframe first to get its values, and evaluate test in another environment. This is probably why the tidyverse prefers when we use .data$ or .env$ explicitly, it removes the risk of evaluating something in the wrong environment.

We should probably do something similar but this doesn't seem so simple. Also, the fact that data_filter() accepts both unquoted and quoted expressions doesn't help. Overall I think that data_filter() should be completely rewritten because the code looks like a lot of patches, but it would be good to clarify the design it should have first.

@IndrajeetPatil @strengejacke