join_keys added based on keys

[mhallal1]

Feature description

In the example below, the first FilteredData object will not have joins_keys while the second will:

#won't have join_keys
ds <- init_filtered_data(list(
  ADSL = list(
    dataset = data.frame(USUBJID = "USUBJID", STUDYID = "STUDYID"), 
    keys = c("USUBJID", "STUDYID")
    )
  ))
ds$get_join_keys()

# will have join_keys

ds2 <- init_filtered_data(list(
  ADSL = list(
    dataset = data.frame(USUBJID = "USUBJID", STUDYID = "STUDYID"), 
    keys = c("USUBJID", "STUDYID")
  )),
  join_keys = teal.data::join_keys(
    teal.data::join_key("ADSL", "ADSL", c("USUBJID", "STUDYID"))
  )
)
ds2$get_join_keys()

A suggestion would be to add by default the keys as join_keys for the dataset.
This would make it easier to extract the primary keys of a dataset in data_extrac_srv.

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[gogonzo]

Issue no longer relevant. Join keys are handed over from a teal_data object and FilterPanel only stores keys for own needs (although get_join_keys() is public, which is kept only for historical reasons)