Commit ⋅ OuhscBbmc/REDCapR

    token              = token,
    records_collapsed  = records_collapsed,
    fields_collapsed   = metadata$data$field_name[id_position],
    forms_collapsed    = forms_collapsed,
    # forms_collapsed    = forms_collapsed,
    events_collapsed   = events_collapsed,
    filter_logic       = filter_logic,
    datetime_range_begin   = datetime_range_begin,

@@ -303,7 +303,7 @@

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  # Continue as intended if the initial query succeeded. --------------------
  unique_ids <- sort(unique(initial_call$data[[id_position]]))

  if (all(nchar(unique_ids)==32L))
  if (0L < length(unique_ids) & all(nchar(unique_ids)==32L))
    warn_hash_record_id()  # nocov

  ds_glossary            <- REDCapR::create_batch_glossary(row_count=length(unique_ids), batch_size=batch_size)

@@ -325,6 +325,11 @@

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        min(selected_ids), " through ", max(selected_ids),
        " (ie, ", length(selected_ids), " unique subject records)."
      )
      # message(
      #   "\nReading batch ", i, " of ", nrow(ds_glossary), ", with subjects ",
      #   paste(selected_ids, collapse = ','),
      #   "\n(ie, ", length(selected_ids), " unique subject records)."
      # )
    }
    read_result <- REDCapR::redcap_read_oneshot(
      redcap_uri                  = redcap_uri,

@@ -391,6 +396,30 @@

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      )
  }

  unique_ids_actual <- sort(unique(ds_stacked[[id_position]]))
  ids_missing_rows  <- setdiff(unique_ids, unique_ids_actual)

  if (0L < length(ids_missing_rows)) {
    message_template <-
      paste0(
        "There are %i subject(s) that are missing rows in the returned dataset. ",
        "REDCap's PHP code is likely trying to process too much text in one bite.\n\n",
        "Common solutions this problem are:\n",
        "  - specifying only the records you need (w/ `records`)\n",
        "  - specifying only the fields you need (w/ `fields`)\n",
        "  - specifying only the forms you need (w/ `forms`)\n",
        "  - specifying a subset w/ `filter_logic`\n",
        "  - reduce `batch_size`\n\n",
        "The missing ids are:\n",
        "%s."
      )
    stop(sprintf(
      message_template,
      length(ids_missing_rows),
      paste(ids_missing_rows, collapse=",")
    ))
  }

  elapsed_seconds          <- as.numeric(difftime( Sys.time(), start_time, units="secs"))
  status_code_combined     <- paste(lst_status_code    , collapse="; ")
  outcome_message_combined <- paste(lst_outcome_message, collapse="; ")

Files		•	•	•	Coverage
R	1,927	1,853	0	74	96.16%
Project Totals (36 files)	1,927	1,853	0	74	96.16%

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comment: false

coverage:
  status:
    project:
      default:
        target: auto
        threshold: 3%
    patch:
      default:
        target: auto
        threshold: 3%

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268	268		token = token,
269	269		records_collapsed = records_collapsed,
270	270		fields_collapsed = metadata$data$field_name[id_position],
271		-	forms_collapsed = forms_collapsed,
	271	+	# forms_collapsed = forms_collapsed,
272	272		events_collapsed = events_collapsed,
273	273		filter_logic = filter_logic,
274	274		datetime_range_begin = datetime_range_begin,

303	303		# Continue as intended if the initial query succeeded. --------------------
304	304		unique_ids <- sort(unique(initial_call$data[[id_position]]))
305	305
306		-	if (all(nchar(unique_ids)==32L))
	306	+	if (0L < length(unique_ids) & all(nchar(unique_ids)==32L))
307	307		warn_hash_record_id() # nocov
308	308
309	309		ds_glossary <- REDCapR::create_batch_glossary(row_count=length(unique_ids), batch_size=batch_size)

325	325		min(selected_ids), " through ", max(selected_ids),
326	326		" (ie, ", length(selected_ids), " unique subject records)."
327	327		)
	328	+	# message(
	329	+	# "\nReading batch ", i, " of ", nrow(ds_glossary), ", with subjects ",
	330	+	# paste(selected_ids, collapse = ','),
	331	+	# "\n(ie, ", length(selected_ids), " unique subject records)."
	332	+	# )
328	333		}
329	334		read_result <- REDCapR::redcap_read_oneshot(
330	335		redcap_uri = redcap_uri,

391	396		)
392	397		}
393	398
	399	+	unique_ids_actual <- sort(unique(ds_stacked[[id_position]]))
	400	+	ids_missing_rows <- setdiff(unique_ids, unique_ids_actual)
	401	+
	402	+	if (0L < length(ids_missing_rows)) {
	403	+	message_template <-
	404	+	paste0(
	405	+	"There are %i subject(s) that are missing rows in the returned dataset. ",
	406	+	"REDCap's PHP code is likely trying to process too much text in one bite.\n\n",
	407	+	"Common solutions this problem are:\n",
	408	+	" - specifying only the records you need (w/ `records`)\n",
	409	+	" - specifying only the fields you need (w/ `fields`)\n",
	410	+	" - specifying only the forms you need (w/ `forms`)\n",
	411	+	" - specifying a subset w/ `filter_logic`\n",
	412	+	" - reduce `batch_size`\n\n",
	413	+	"The missing ids are:\n",
	414	+	"%s."
	415	+	)
	416	+	stop(sprintf(
	417	+	message_template,
	418	+	length(ids_missing_rows),
	419	+	paste(ids_missing_rows, collapse=",")
	420	+	))
	421	+	}
	422	+
394	423		elapsed_seconds <- as.numeric(difftime( Sys.time(), start_time, units="secs"))
395	424		status_code_combined <- paste(lst_status_code , collapse="; ")
396	425		outcome_message_combined <- paste(lst_outcome_message, collapse="; ")

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1	comment: false
2
3	coverage:
4	status:
5	project:
6	default:
7	target: auto
8	threshold: 3%
9	patch:
10	default:
11	target: auto
12	threshold: 3%

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