Merge pull request #3 from colearendt/developclean

Development with Clean History

.Rbuildignore

@@ -5,3 +5,8 @@
 ^codecov\.yml$
 ^README\.Rmd$
 ^README-.*\.png$
+^packrat/
+^\.Rprofile$
+^working/
+^appveyor\.yml$
+^revdep/

.gitattributes

@@ -0,0 +1,4 @@
+* text=auto
+data/* binary
+src/* text=lf
+R/* text=lf

.gitignore

@@ -6,3 +6,7 @@ inst/doc
 .Rproj.user
 *.Rproj
 .DS_Store
+packrat/lib*/
+packrat/src/
+working/
+.Rprofile

.travis.yml

@@ -6,6 +6,14 @@ cache: packages
 
 r_packages:
   - covr
+
+script: 
+  - |
+    travis_wait 60 R CMD build --no-build-vignettes --no-manual --no-resave-data . 
+    travis_wait 60 R CMD check --no-build-vignettes --no-manual tidyjson*tar.gz
 
 after_success:
   - Rscript -e 'library(covr); codecov()'
+
+after_script:
+ - ./travis-tool.sh dump_logs

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: tidyjson
 Title: Tidy Complex JSON
-Version: 0.2.1.9000
+Version: 0.2.1.9001
 Author: Jeremy Stanley <[email protected]>
 Maintainer: Jeremy Stanley <[email protected]>
 Description: Turn complex JSON data into tidy data frames.
@@ -28,8 +28,9 @@ Suggests:
     listviewer,
     igraph,
     RColorBrewer,
-    covr
+    covr,
+    lubridate
 VignetteBuilder: knitr
 URL: https://github.com/jeremystan/tidyjson
 BugReports: https://github.com/jeremystan/tidyjson/issues
-RoxygenNote: 5.0.1
+RoxygenNote: 6.0.1

NAMESPACE

@@ -1,26 +1,39 @@
 # Generated by roxygen2: do not edit by hand
 
 S3method("[",tbl_json)
+S3method(arrange,tbl_json)
 S3method(arrange_,tbl_json)
 S3method(as.character,tbl_json)
 S3method(as.tbl_json,character)
 S3method(as.tbl_json,data.frame)
 S3method(as.tbl_json,tbl_json)
+S3method(filter,tbl_json)
 S3method(filter_,tbl_json)
+S3method(mutate,tbl_json)
 S3method(mutate_,tbl_json)
 S3method(print,tbl_json)
+S3method(slice,tbl_json)
 S3method(slice_,tbl_json)
 export("%>%")
+export(append_chr)
+export(append_dbl)
+export(append_lgl)
 export(append_values_logical)
 export(append_values_number)
 export(append_values_string)
 export(as.tbl_json)
+export(as_data_frame)
+export(as_tibble)
+export(bind_rows)
 export(enter_object)
 export(gather_array)
 export(gather_keys)
 export(gather_object)
 export(is.tbl_json)
 export(is_json_array)
+export(is_json_chr)
+export(is_json_dbl)
+export(is_json_lgl)
 export(is_json_logical)
 export(is_json_null)
 export(is_json_number)
@@ -29,8 +42,11 @@ export(is_json_scalar)
 export(is_json_string)
 export(jlogical)
 export(jnumber)
+export(json_chr)
 export(json_complexity)
+export(json_dbl)
 export(json_lengths)
+export(json_lgl)
 export(json_schema)
 export(json_structure)
 export(json_types)

NEWS.md

@@ -1,4 +1,39 @@
-# purrr 0.2.1.9000
+# tidyjson 0.2.1.9001
+
+## New functions
+
+* Add `bind_rows()` support.  Though currently not an S3 implementation, it behaves as much like the `dplyr` variant as possible, preserving the `attr(.,'JSON')` components if all components are `tbl_json` objects. (#58)
+
+## Documentation Changes
+
+* "Using Multiple APIs" vignette added to show support for using tidyjson with multiple APIs (#85)
+
+* Updated README.md to better explain `spread_all()` (#92)
+
+## Bug fixes and minor changes
+
+* `DROP=TRUE` caused an error.  Altered behavior to be consistent with `tbl_df` (throw a warning and do nothing)
+
+* Fix `spread_all(recursive=FALSE)` bug that caused an error (#65)
+
+* Alter `spread_all()` behavior to recursively check for deduplication of names (and thus avoid an error) (#76)
+
+* Add named support for the `NSE` versions of dplyr functions (`filter()`,`mutate()`,`slice()`, etc.) since the `SE` variants are no longer called behind-the-scenes since `dplyr 0.6.0`.  (#97)
+
+* Fix errors with `print.tbl_json()` when the JSON attribute is missing
+
+* Fix json_structure() failure if `document.id` missing by imputing 
+the missing `document.id`.  (#86)
+
+## Deprecated functions
+
+* `jstring()`, `jnumber()`, `jlogical()` -> use `json_chr()`, `json_dbl()`, `json_lgl()` instead (#93)
+
+* `is_json_string()`,`is_json_number()`,`is_json_logical()` -> use `is_json_chr()`, `is_json_dbl()`, `is_json_lgl()` instead (#93)
+
+* `append_values_string()`, `append_values_number()`, `append_values_logical()` -> use `append_chr()`, `append_dbl()`, `append_lgl()` instead (#93)
+
+# tidyjson 0.2.1.9000
 
 ## New functions
 

R/append_values.R

@@ -7,7 +7,7 @@
 #'
 #' Any values that can not be converted to the specified will be \code{NA} in
 #' the resulting column. This includes other scalar types (e.g., numbers or
-#' logicals if you are using \code{append_values_string}) and *also* any rows
+#' logicals if you are using \code{append_chr}) and *also* any rows
 #' where the JSON is NULL or an object or array.
 #'
 #' Note that the \code{append_values} functions do not alter the JSON
@@ -30,17 +30,17 @@
 #' # Stack names
 #' '{"first": "bob", "last": "jones"}' %>%
 #'   gather_object %>%
-#'   append_values_string
+#'   append_chr
 #'
 #' # This is most useful when data is stored in name-value pairs
 #' # For example, tags in recipes:
 #' recipes <- c('{"name": "pie", "tags": {"apple": 10, "pie": 2, "flour": 5}}',
 #'              '{"name": "cookie", "tags": {"chocolate": 2, "cookie": 1}}')
 #' recipes %>%
-#'   spread_values(name = jstring(name)) %>%
+#'   spread_values(name = json_chr(name)) %>%
 #'   enter_object(tags) %>%
 #'   gather_object("tag") %>%
-#'   append_values_number("count")
+#'   append_dbl("count")
 NULL
 
 #' Creates the append_values_* functions
@@ -52,12 +52,12 @@ append_values_factory <- function(type, as.value) {
 
     if (!is.tbl_json(.x)) .x <- as.tbl_json(.x)
 
-    if (force == FALSE) assert_that(recursive == FALSE)
+    if (force == FALSE) assertthat::assert_that(recursive == FALSE)
 
     # Extract json
     json <- attr(.x, "JSON")
 
-    assert_that(length(json) == nrow(.x))
+    assertthat::assert_that(length(json) == nrow(.x))
 
     # if json is empty, return empty
     if (length(json) == 0) {
@@ -78,7 +78,7 @@ append_values_factory <- function(type, as.value) {
           new_val[loc] <- NA
        }
        new_val <- new_val %>% as.value
-       assert_that(length(new_val) == nrow(.x))
+       assertthat::assert_that(length(new_val) == nrow(.x))
        .x[column.name] <- new_val
     }
 
@@ -92,7 +92,7 @@ append_values_factory <- function(type, as.value) {
 #' @param l a list that we want to unlist
 #' @param recursive logical indicating whether to unlist nested lists
 my_unlist <- function(l, recursive = FALSE) {
-  nulls <- map_int(l, length) != 1
+  nulls <- purrr::map_int(l, length) != 1
   l[nulls] <- NA
   unlist(l, recursive = recursive)
 }
@@ -120,12 +120,33 @@ append_values_type <- function(json, type) {
 
 #' @export
 #' @rdname append_values
-append_values_string <- append_values_factory("string", as.character)
+append_chr <- append_values_factory("string", as.character)
 
 #' @export
 #' @rdname append_values
-append_values_number <- append_values_factory("number", as.numeric)
+append_values_string <- function(.x, column.name = 'string', force = TRUE, recursive = FALSE){
+  .Deprecated(new='append_chr')
+  append_chr(.x,column.name,force,recursive)
+}
+
+#' @export
+#' @rdname append_values
+append_dbl <- append_values_factory("number", as.numeric)
+
+#' @export
+#' @rdname append_values
+append_values_number <- function(.x, column.name = 'number', force = TRUE, recursive = FALSE){
+  .Deprecated(new='append_dbl')
+  append_dbl(.x,column.name,force,recursive)
+}
+
+#' @export
+#' @rdname append_values
+append_lgl <- append_values_factory("logical", as.logical)
 
 #' @export
 #' @rdname append_values
-append_values_logical <- append_values_factory("logical", as.logical)
+append_values_logical <- function(.x, column.name = 'logical', force = TRUE, recursive = FALSE){
+  .Deprecated(new='append_lgl')
+  append_lgl(.x,column.name,force,recursive)
+}

R/data-issues.R

@@ -28,7 +28,7 @@
 #' # Count issues labels by name
 #' labels <- issues %>%
 #'   gather_array %>%                    # stack issues as "issue.num"
-#'   spread_values(id = jnumber(id)) %>% # capture just issue id
+#'   spread_values(id = json_dbl(id)) %>% # capture just issue id
 #'   enter_object(labels) %>%            # filter just those with labels
 #'   gather_array("label.index") %>%     # stack labels
 #'   spread_all

R/data-worldbank.R

@@ -25,7 +25,7 @@
 #'   select(project_name, regionname) %>%
 #'   enter_object(majorsector_percent) %>% # Enter the 'sector' object
 #'   gather_array("sector.index") %>%      # Gather the array
-#'   spread_values(sector = jstring(Name)) # Spread the sector name
+#'   spread_values(sector = json_chr(Name)) # Spread the sector name
 #'
 #' # Examine the structured data
 #' wb_sectors %>% glimpse

R/enter_object.R

@@ -16,7 +16,7 @@
 #'
 #' @seealso \code{\link{gather_object}} to find sub-objects that could be
 #'    entered into, \code{\link{gather_array}} to gather an array in an object
-#'    and \code{\link{spread_all}} to spread values in an object.
+#'    and \code{\link{spread_all}} or \code{\link{spread_values}} to spread values in an object.
 #' @param .x a json string or tbl_json object
 #' @param ... a quoted or unquoted sequence of strings designating the object
 #'            name or sequences of names you wish to enter
@@ -44,10 +44,10 @@
 #' json %>% spread_all %>% enter_object(children) %>%
 #'   gather_array("child.num")
 #'
-#' # And append_values_string to add the children names
+#' # And append_chr to add the children names
 #' json %>% spread_all %>% enter_object(children) %>%
 #'   gather_array("child.num") %>%
-#'   append_values_string("child")
+#'   append_chr("child")
 #'
 #' # The path can be comma delimited to go deep into a nested object
 #' json <- '{"name": "bob", "attributes": {"age": 32, "gender": "male"}}'
@@ -71,7 +71,7 @@ enter_object <- function(.x, ...) {
   json <- attr(.x, "JSON")
 
   # Access path
-  json <- map(json, path %>% as.list)
+  json <- purrr::map(json, path %>% as.list)
 
   tbl_json(.x, json, drop.null.json = TRUE)
 

R/gather.R

@@ -12,8 +12,8 @@ gather_factory <- function(default.column.name, default.column.empty,
 
   function(.x, column.name = default.column.name) {
 
-    assert_that(!("..name" %in% names(.x)))
-    assert_that(!("..json" %in% names(.x)))
+    assertthat::assert_that(!("..name" %in% names(.x)))
+    assertthat::assert_that(!("..json" %in% names(.x)))
 
     if (!is.tbl_json(.x)) .x <- as.tbl_json(.x)
 
@@ -36,13 +36,13 @@ gather_factory <- function(default.column.name, default.column.empty,
       stop(sprintf("%s records are not %ss", sum(bad_type), required.type))
 
     y <- .x %>%
-      tbl_df %>%
-      mutate(
-        ..name = json %>% map(expand.fun),
+      dplyr::as_tibble() %>%
+      dplyr::mutate(
+        ..name = json %>% purrr::map(expand.fun),
         ..json = json %>%
-          map(~data_frame(..json = as.list(.)))
+          purrr::map(~dplyr::data_frame(..json = as.list(.)))
       ) %>%
-      unnest(..name, ..json, .drop = FALSE)
+      tidyr::unnest(..name, ..json, .drop = FALSE)
 
     # Check to see if column.name exists, otherwise, increment until not
     if (column.name %in% names(y)) {
@@ -58,10 +58,10 @@ gather_factory <- function(default.column.name, default.column.empty,
     }
 
     # Rename
-    y <- y %>% rename_(.dots = setNames("..name", column.name))
+    y <- y %>% dplyr::rename_(.dots = setNames("..name", column.name))
 
     # Construct tbl_json
-    tbl_json(y %>% select(-..json), y$..json)
+    tbl_json(y %>% dplyr::select(-..json), y$..json)
 
   }
 
@@ -107,14 +107,14 @@ gather_factory <- function(default.column.name, default.column.empty,
 #' # Then we can use the column.name argument to change the column name
 #' json %>% gather_object("year")
 #'
-#' # We can also use append_values_number to capture the values, since they are
+#' # We can also use append_dbl to capture the values, since they are
 #' # all of the same type
-#' json %>% gather_object("year") %>% append_values_number("count")
+#' json %>% gather_object("year") %>% append_dbl("count")
 #'
 #' # This can even work with a more complex, nested example
 #' json <- '{"2015": {"1": 10, "3": 1, "11": 5}, "2016": {"2": 3, "5": 15}}'
 #' json %>% gather_object("year") %>% gather_object("month") %>%
-#'   append_values_number("count")
+#'   append_dbl("count")
 #'
 #' # Most JSON starts out as an object (or an array of objects), and
 #' # gather_object can be used to inspect the top level (or 2nd level) objects
@@ -173,7 +173,7 @@ gather_keys <- function(.x, column.name = "key") {
 #' json %>% gather_array %>% json_types
 #'
 #' # Extract string values
-#' json %>% gather_array %>% append_values_string
+#' json %>% gather_array %>% append_chr
 #'
 #' # A more complex mixed type example
 #' json <- '["a", 1, true, null, {"name": "value"}]'
@@ -186,7 +186,7 @@ gather_keys <- function(.x, column.name = "key") {
 #'
 #' # Extract both levels
 #' json %>% gather_array("index.1") %>% gather_array("index.2") %>%
-#'   append_values_string
+#'   append_chr
 #'
 #' # Some JSON begins as an array
 #' commits %>% gather_array