Failure when running introduction-to-tidyjson.Rmd vignette: parse error: premature EOF

[barracuda156]

> knitr::opts_chunk$set(collapse = T, comment = "#>")

> options(tibble.print_min = 4, tibble.print_max = 4)

> library(tidyjson)

Attaching package: ‘tidyjson’

The following object is masked from ‘package:stats’:

    filter


> library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union


> people <- c("{\"age\": 32, \"name\": {\"first\": \"Bob\",   \"last\": \"Smith\"}}", 
+     "{\"age\": 54, \"name\": {\"first\": \"Susan\", \"last\": ..." ... [TRUNCATED] 

> people %>% spread_all
# A tbl_json: 3 x 5 tibble with a "JSON" attribute
  ..JSON                  document.id   age name.first name.last
  <chr>                         <int> <dbl> <chr>      <chr>    
1 "{\"age\":32,\"name..."           1    32 Bob        Smith    
2 "{\"age\":54,\"name..."           2    54 Susan      Doe      
3 "{\"age\":18,\"name..."           3    18 Ann        Jones    

> worldbank %>% str
 chr [1:500] "{\"_id\":{\"$oid\":\"52b213b38594d8a2be17c780\"},\"boardapprovaldate\":\"2013-11-12T00:00:00Z\",\"closingdate\""| __truncated__ ...

> worldbank %>% spread_all
# A tbl_json: 500 x 9 tibble with a "JSON" attribute
  ..JSON document.id boardapprovaldate closingdate countryshortname project_name
  <chr>        <int> <chr>             <chr>       <chr>            <chr>       
1 "{\"_…           1 2013-11-12T00:00… 2018-07-07… Ethiopia         Ethiopia Ge…
2 "{\"_…           2 2013-11-04T00:00… <NA>        Tunisia          TN: DTF Soc…
3 "{\"_…           3 2013-11-01T00:00… <NA>        Tuvalu           Tuvalu Avia…
4 "{\"_…           4 2013-10-31T00:00… <NA>        Yemen, Republic… Gov't and C…
# ℹ 496 more rows
# ℹ 3 more variables: regionname <chr>, totalamt <dbl>, `_id.$oid` <chr>

> worldbank %>% spread_all %>% select(regionname, totalamt)
# A tbl_json: 500 x 3 tibble with a "JSON" attribute
  ..JSON                   regionname                    totalamt
  <chr>                    <chr>                            <dbl>
1 "{\"_id\":{\"$oid\":..." Africa                       130000000
2 "{\"_id\":{\"$oid\":..." Middle East and North Africa         0
3 "{\"_id\":{\"$oid\":..." East Asia and Pacific          6060000
4 "{\"_id\":{\"$oid\":..." Middle East and North Africa         0
# ℹ 496 more rows

> options(tibble.print_min = 10, tibble.print_max = 10)

> worldbank %>% gather_object %>% json_types %>% count(name, 
+     type)
# A tibble: 8 × 3
  name                type       n
  <chr>               <fct>  <int>
1 _id                 object   500
2 boardapprovaldate   string   500
3 closingdate         string   370
4 countryshortname    string   500
5 majorsector_percent array    500
6 project_name        string   500
7 regionname          string   500
8 totalamt            number   500

> options(tibble.print_min = 4, tibble.print_max = 4)

> worldbank %>% enter_object(majorsector_percent)
# A tbl_json: 500 x 2 tibble with a "JSON" attribute
  ..JSON                  document.id
  <chr>                         <int>
1 "[{\"Name\":\"Educa..."           1
2 "[{\"Name\":\"Publi..."           2
3 "[{\"Name\":\"Trans..."           3
4 "[{\"Name\":\"Healt..."           4
# ℹ 496 more rows

> worldbank %>% enter_object(majorsector_percent) %>% 
+     gather_array
# A tbl_json: 1,405 x 3 tibble with a "JSON" attribute
  ..JSON                  document.id array.index
  <chr>                         <int>       <int>
1 "{\"Name\":\"Educat..."           1           1
2 "{\"Name\":\"Educat..."           1           2
3 "{\"Name\":\"Public..."           1           3
4 "{\"Name\":\"Educat..."           1           4
# ℹ 1,401 more rows

> worldbank %>% enter_object(majorsector_percent) %>% 
+     gather_array %>% spread_all
# A tbl_json: 1,405 x 5 tibble with a "JSON" attribute
  ..JSON                  document.id array.index Name                   Percent
  <chr>                         <int>       <int> <chr>                    <dbl>
1 "{\"Name\":\"Educat..."           1           1 Education                   46
2 "{\"Name\":\"Educat..."           1           2 Education                   26
3 "{\"Name\":\"Public..."           1           3 Public Administration…      16
4 "{\"Name\":\"Educat..."           1           4 Education                   12
# ℹ 1,401 more rows

> worldbank %>% spread_all %>% select(region = regionname, 
+     funding = totalamt) %>% enter_object(majorsector_percent) %>% 
+     gather_array %> .... [TRUNCATED] 
`summarise()` has grouped output by 'region'. You can override using the
`.groups` argument.
# A tibble: 63 × 3
# Groups:   region [7]
  region sector                                 funding
  <chr>  <chr>                                    <dbl>
1 Africa Agriculture, fishing, and forestry 96648500000
2 Africa Education                          83370000000
3 Africa Energy and mining                  86709960000
4 Africa Finance                            30761000000
# ℹ 59 more rows

> worldbank %>% spread_all %>% select(regionname, totalamt)
# A tbl_json: 500 x 3 tibble with a "JSON" attribute
  ..JSON                   regionname                    totalamt
  <chr>                    <chr>                            <dbl>
1 "{\"_id\":{\"$oid\":..." Africa                       130000000
2 "{\"_id\":{\"$oid\":..." Middle East and North Africa         0
3 "{\"_id\":{\"$oid\":..." East Asia and Pacific          6060000
4 "{\"_id\":{\"$oid\":..." Middle East and North Africa         0
# ℹ 496 more rows

> worldbank %>% gather_object %>% json_types %>% count(name, 
+     type)
# A tibble: 8 × 3
  name              type       n
  <chr>             <fct>  <int>
1 _id               object   500
2 boardapprovaldate string   500
3 closingdate       string   370
4 countryshortname  string   500
# ℹ 4 more rows

> worldbank %>% enter_object(majorsector_percent) %>% 
+     gather_array
# A tbl_json: 1,405 x 3 tibble with a "JSON" attribute
  ..JSON                  document.id array.index
  <chr>                         <int>       <int>
1 "{\"Name\":\"Educat..."           1           1
2 "{\"Name\":\"Educat..."           1           2
3 "{\"Name\":\"Public..."           1           3
4 "{\"Name\":\"Educat..."           1           4
# ℹ 1,401 more rows

> companies[1] %>% gather_object %>% filter(is_json_array(.)) %>% 
+     gather_array
# A tbl_json: 8 x 4 tibble with a "JSON" attribute
  ..JSON                  document.id name           array.index
  <chr>                         <int> <chr>                <int>
1 "{\"is_past\":fals..."            1 relationships            1
2 "{\"id\":6252,\"rou..."           1 funding_rounds           1
3 "{\"id\":15229,\"ro..."           1 funding_rounds           2
4 "{\"id\":22565,\"ro..."           1 funding_rounds           3
# ℹ 4 more rows

> companies[1] %>% gather_object %>% filter(is_json_object(.)) %>% 
+     gather_object
Warning in gather_object(.) :
  name column name already exists, changing to name.2
# A tbl_json: 3 x 4 tibble with a "JSON" attribute
  ..JSON                document.id name  name.2         
  <chr>                       <int> <chr> <chr>          
1 "\"52cdef7e4bab8b..."           1 _id   $oid           
2 "[[[150,22],\"ass..."           1 image available_sizes
3 "null"                          1 image attribution    

> json <- "{\"2015\": 5, \"2016\": 10}"

> json %>% gather_object("year") %>% append_values_number("count")
# A tbl_json: 2 x 4 tibble with a "JSON" attribute
  ..JSON document.id year  count
  <chr>        <int> <chr> <dbl>
1 5                1 2015      5
2 10               1 2016     10

> worldbank %>% as.tbl_json
# A tbl_json: 500 x 2 tibble with a "JSON" attribute
  ..JSON                   document.id
  <chr>                          <int>
1 "{\"_id\":{\"$oid\":..."           1
2 "{\"_id\":{\"$oid\":..."           2
3 "{\"_id\":{\"$oid\":..."           3
4 "{\"_id\":{\"$oid\":..."           4
# ℹ 496 more rows

> bad_json <- "{\"key\": \"value\""

> bad_json %>% as.tbl_json

  When sourcing ‘introduction-to-tidyjson.R’:
Error: ℹ In index: 1.
Caused by error:
! parse error: premature EOF
                                       {"key": "value"
                     (right here) ------^
Execution halted

All tests pass.