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library(httr)
endpoint <- "https://api.noopschallenge.com/hexbot"

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# Separate LHS and RHS rules
r1$rulecount <- as.character(r1$rule)
max_col <- max(sapply(strsplit(r1$rulecount,' => '),length))
r_sep <- separate(data = r1, col = rule, into = paste0("Time",1:max_col), sep = " => ")
r_sep$Time2 <- substring(r_sep$Time2,3,nchar(r_sep$Time2)-2)

# Strip LHS baskets
max_time1 <- max(sapply(strsplit(r_sep$Time1,'},'),length))
r_sep$TimeClean <- substring(r_sep$Time1,3,nchar(r_sep$Time1)-2)
r_sep$TimeClean <- gsub("\\},\\{", "zzz", r_sep$TimeClean)

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# Get induced temporal rules from frequent itemsets
r1 <- as(ruleInduction(s1, confidence = 0.5, control = list(verbose = TRUE)), "data.frame")

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library(checkpoint)
checkpoint("2018-08-14")
library(fortunes)
library(mscstts)

set_ms_tts_key("8e61ae64924647d1a2833d68eeced78e")

out <- ms_synthesize("hello, world!", output_format = "audio-16khz-128kbitrate-mono-mp3")
f <- tempfile(fileext=".mp3") 
writeBin(out$content, f)

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azure_mosaic <- readPNG("azure.png") %>% 
  scale_image(64) %>% 
  legoize() %>% 
  collect_bricks() 

azure_mosaic %>% display_set("Bit and Azure")

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hotdog_predict <- function(imageURL, threshold = 0.5) {
 predURL <- paste0(cvision_api_endpoint_pred, "/", cvision_id,"/url?",
                   "iterationId=",train.id,
                   "&application=R"
                   )

 body.pred <- toJSON(list(Url=imageURL[1]), auto_unbox = TRUE)

 APIresponse = POST(url = predURL,
                    content_type_json(),

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image_caption <- function(URL) {
 reqURL = paste0(vision_api_endpoint,
                 "/analyze?visualFeatures=Description",
                 "&details=Celebrities,Landmarks")
 
 APIresponse = POST(url = reqURL,
                    content_type('application/json'),
                    add_headers(.headers = c('Ocp-Apim-Subscription-Key' = vision_api_key)),
                    body=list(url = URL),
                    encode = "json") 

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random_image <- function() {
 ## Return the URL random image in Wikimedia Commons
 random_query <- paste0("https://commons.wikimedia.org/w/api.php?",
                        "action=query",
                        "&generator=random", # get a random page
                        "&grnlimit=1",       # return 1 page
                        "&grnnamespace=6",   # category: File
                        "&prop=imageinfo",
                        "&iiprop=url|size|extmetadata",
                        "&iiurlheight=1080",  # limit images height (sometimes)

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library(tidyverse)
library(stringr)
library(stringi)
simplify_name <- function(n)
 ## Extract just the name, removing any quotes, and normalize accented characters 
 stri_trans_general(str_trim(str_match(n,"^[\'\"]?([^\'\",(<]+).*<")[,2]),"latin-ascii")       
pkglist <- tools::CRAN_package_db()
pkglist <- tbl_df(pkglist[-40]) ## remove duplicate MD5sum column
pkglist %>% 
 select(Maintainer, Author, Package) %>% 

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{
  "name": "davidsmiDAP8p",
  "vmSize": "Standard_D2_v2",
  "maxTasksPerNode": 4,
  "poolSize": {
    "dedicatedNodes": {
      "min": 0,
      "max": 0
    },
    "lowPriorityNodes": {