use all collections, datasets, files to determine available columns

- e.g., 'first' data set did not contain 'batch_conditions', so
  column was not included
- use rjsoncons instead of jsonlite throughout

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: cellxgenedp
 Title: Discover and Access Single Cell Data Sets in the CELLxGENE Data Portal
-Version: 1.7.2
+Version: 1.7.3
 Authors@R: 
     c(person(
         given = "Martin",
@@ -21,7 +21,7 @@ Encoding: UTF-8
 Collate: db.R collections.R datasets.R files.R facets.R keys.R
     cellxgene.R utilities.R publisher_metadata.R cxg.R
 Depends: dplyr
-Imports: httr, curl, jsonlite, utils, tools, shiny, DT, rjsoncons
+Imports: httr, curl, utils, tools, shiny, DT, rjsoncons
 Suggests:
     zellkonverter,
     SingleCellExperiment,
@@ -36,6 +36,6 @@ biocViews: SingleCell, DataImport, ThirdPartyClient
 URL: https://mtmorgan.github.io/cellxgenedp/, https://github.com/mtmorgan/cellxgenedp
 BugReports: https://github.com/mtmorgan/cellxgenedp/issues
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 VignetteBuilder: knitr
 Config/testthat/edition: 3

NAMESPACE

@@ -49,8 +49,8 @@ importFrom(httr,progress)
 importFrom(httr,status_code)
 importFrom(httr,stop_for_status)
 importFrom(httr,write_disk)
-importFrom(jsonlite,parse_json)
-importFrom(rjsoncons,jmespath)
+importFrom(rjsoncons,j_pivot)
+importFrom(rjsoncons,j_query)
 importFrom(shiny,actionButton)
 importFrom(shiny,hr)
 importFrom(shiny,icon)

NEWS.md

@@ -1,8 +1,23 @@
 # cellxgenedp 1.8
-
+
+SIGNIFICANT USER-VISIBLE CHANGES
+
 * (v 1.7.2) Add vignette 'Case studies', include identifying dataset
   authors and using ontolgies to identify datasets
+
 * (v 1.7.1) Update vignette section on dataset visualization to
+
+BUG FIXES
+
+* (v 1.7.3) Use all collections, datasets, files to determine
+  available columns
+
+
+# cellxgenedp 1.6
+
+SIGNIFICANT USER-VISIBLE CHANGES
+
+* (v 1.6.1) Update vignette section on dataset visualization to
   accomodate changes in the 'Discover' API.
   https://github.com/mtmorgan/cellxgenedp/issues/15
 
@@ -12,6 +27,11 @@
   some return values. See 'API changes' of the 'Discover and download
   datasets...' vignette.
 
+BUG FIXES
+
+* (v 1.6.2) Use all collections, datasets, and files when
+  identifying available columns.
+
 # cellxgenedp 1.4
 
 SIGNIFICANT USER-VISIBLE CHANGES

R/db.R

@@ -1,12 +1,14 @@
 #' @importFrom dplyr bind_rows mutate arrange desc
+#'
+#' @importFrom rjsoncons j_pivot
 .db <-
     function(overwrite)
 {
     path <- .cellxgene_cache_get(
         .COLLECTIONS, "collections", overwrite = overwrite
     )
     readLines(path) |>
-        parse_json(simplifyVector = TRUE) |>
+        j_pivot(as = "tibble") |>
         bind_rows()
 }
 

R/facets.R

@@ -35,7 +35,7 @@ FACETS <- c(
 }
 
 #' @importFrom dplyr group_by ungroup count bind_cols tibble .data
-#' @importFrom jsonlite parse_json
+#'
 #' @rdname facets
 #'
 #' @description `facets()` is used to query the cellxgene database for

R/keys.R

@@ -6,9 +6,10 @@
     query <- paste0(query_base, ".keys(@)")
     key_names <-
         .jmes_to_r(db, query) |>
+        unlist() |>
+        sort() |>
         setdiff(.KEYS_BLOCKLIST)
-    path_base <- gsub("[0]", "[]", query_base, fixed = TRUE)
-    key_paths <- paste0(path_base, ".", key_names)
+    key_paths <- paste0(query_base, ".", key_names)
     names(key_paths) <- key_names
     key_paths
 }
@@ -18,9 +19,9 @@ keys <-
     function(cellxgene_db = db())
 {
     queries <- c(
-        collections = "[0]",
-        datasets = "[0].datasets[0]",
-        files = "[0].datasets[0].assets[0]"
+        collections = "[]",
+        datasets = "[].datasets[]",
+        files = "[].datasets[].assets[]"
     )
     lapply(queries, .keys, db = cellxgene_db)
 }

R/publisher_metadata.R

@@ -54,7 +54,7 @@ authors <-
     function(cellxgene_db = db())
 {
     ## publisher_metadata can be NULL; filter for non-null values
-    cellxgene_db <- jmespath(cellxgene_db, "[?not_null(publisher_metadata)]")
+    cellxgene_db <- j_query(cellxgene_db, "[?not_null(publisher_metadata)]")
 
     author_length <-
         .jmes_to_r(cellxgene_db, "[*].publisher_metadata[].length(authors)")
@@ -87,7 +87,7 @@ publisher_metadata <-
     function(cellxgene_db = db())
 {
     ## publisher_metadata can be NULL; filter for non-null values
-    cellxgene_db <- jmespath(cellxgene_db, "[?not_null(publisher_metadata)]")
+    cellxgene_db <- j_query(cellxgene_db, "[?not_null(publisher_metadata)]")
 
     keys <- c(
         "is_preprint", "journal",

R/utilities.R

@@ -22,12 +22,11 @@
     .is_scalar(x) && is.logical(x)
 }
 
-#' @importFrom rjsoncons jmespath
+#' @importFrom rjsoncons j_query
 .jmes_to_r <-
     function(db, path, ..., simplifyVector = TRUE)
 {
-    jmespath(db, path) |>
-        parse_json(..., simplifyVector = simplifyVector)
+    j_query(db, path, as = "R")
 }
 
 .onLoad <-

tests/testthat/test-db.R

@@ -5,7 +5,7 @@ test_that("db() works", {
     db <- db()
     expect_s3_class(db, c("cellxgene_db", "character"))
     expect_true(nzchar(db))
-    json <- jsonlite::parse_json(db)
+    json <- j_query(db, as = "R")
     expect_type(json, "list")
     expect_true(length(json) >= 48L)
 })