jennybc

curl 'https://sheets.googleapis.com/v4/spreadsheets/132Ij_8ggTKVLnLqCOM3ima6mV9F8rmY7HEcR-5hjWoQ?includeGridData=true&ranges=Sheet1!A1%3AF6&key=AIzaSyDXicV6oK4vR948PUAvlyr7QhkNwCoQ0cA' -H 'Accept: application/json' --compressed > spreadsheets_get_2.json

curl 'https://sheets.googleapis.com/v4/spreadsheets/132Ij_8ggTKVLnLqCOM3ima6mV9F8rmY7HEcR-5hjWoQ/values/Sheet1!A1%3AF6?key=AIzaSyDXicV6oK4vR948PUAvlyr7QhkNwCoQ0cA' -H 'Accept: application/json' --compressed > spreadsheets_values_get.json

jennybc

curl 'https://sheets.googleapis.com/v4/spreadsheets/1BzfL0kZUz1TsI5zxJF1WNF01IxvC67FbOJUiiGMZ_mQ?includeGridData=true&ranges=Africa!A1%3AF3&key=AIzaSyDXicV6oK4vR948PUAvlyr7QhkNwCoQ0cA' -H 'Accept: application/json' --compressed > spreadsheets_get.json

curl 'https://sheets.googleapis.com/v4/spreadsheets/1BzfL0kZUz1TsI5zxJF1WNF01IxvC67FbOJUiiGMZ_mQ/values/Africa!A1%3AF3?key=AIzaSyDXicV6oK4vR948PUAvlyr7QhkNwCoQ0cA' -H 'Accept: application/json' --compressed > spreadsheets_values_get.json

jennybc

library(tidyverse)

## approximates big_df in the post
big_df <- mtcars %>% 
  select(cyl, mpg, disp) %>% 
  arrange(cyl) %>% 
  slice(17:22) %>% 
  rename(ID = cyl)

## dummy function that needs access to ID and data

jennybc

#' ---
#' output:
#'   word_document
#' ---

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

#+
library(repurrrsive)
library(tidyverse)

jennybc

library(testthat)

rev_captcha <- function(x) {
  x <- as.integer(strsplit(x, "")[[1]])
  xd <- diff(c(x, x[1]))
  sum(x[xd == 0])
}

expect_equal(rev_captcha("1122"), 3)
expect_equal(rev_captcha("1111"), 4)

jennybc

library(tidyverse)
library(repurrrsive)

df <- tibble(
  name = map_chr(got_chars, "name"),
  titles = map(got_chars, "titles")
)
df

df <- got_chars %>% {

jennybc

library(tidyverse)
(df <- tibble(
  x = c(1, NA, 3, NA),
  y = c(1, NA, NA, 4),
  z = 1:4
))
#> # A tibble: 4 × 3
#>       x     y     z
#>   <dbl> <dbl> <int>
#> 1     1     1     1

jennybc

Install and load alm

install_github("ropensci/alm")

library("alm")

jennybc

httr::GET("http://catfacts-api.appspot.com/api/facts",
          query = list(number = 5)) %>% 
  httr::content(as = "text", encoding = "UTF-8") %>% 
  jsonlite::fromJSON()

jennybc

We set up knitr so it doesn't catch errors, then set
`options(error=recover)` to set up R's debug-on-error machinery.

We have to do one additional thing, before the options call though: 
trace the recover function with`sink(NULL)` to turn off the output 
capturing so the R console is useful when the debugging framework 
dumps us back into it. This has to happen before the options call
because that call grabs the `recover` object and stores it somewhere
so setting a trace on recover after the call won't affect the cached
version that gets called upon an error.