# links
#https://www.programmableweb.com/news/how-to-access-any-restful-api-using-r-language/how-to/2017/07/21
#https://www.r-bloggers.com/accessing-apis-from-r-and-a-little-r-programming/
# packages used

rm(list=ls()) 

listofpackages <- c("httr", "jsonlite", "lubridate")

for (j in listofpackages){
  if(sum(installed.packages()[, 1] == j) == 0) {
    install.packages(j)
  }
  library(j, character.only = T)
}
options(stringsAsFactors = FALSE)

url  <- "http://api.epdb.eu"
path <- "eurlex/directory_code"
raw.result <- GET(url = url, path = path)
names(raw.result)
#problem which is the most popular day for having energy relted documents into force ?
raw.result$status_code
head(raw.result$content)
this.raw.content <- rawToChar(raw.result$content)
nchar(this.raw.content)
substr(this.raw.content, 1, 100)
this.content <- fromJSON(this.raw.content)
class(this.content) #it's a list
length(this.content)
this.content[[1]]
this.content.df <- do.call(what = "rbind",
                           args = lapply(this.content, as.data.frame))
head(this.content.df)
headClass <- substr(x = this.content.df[, "directory_code"],
                    start = 1,
                    stop = 2)
isEnergy <- headClass == "12"
table(isEnergy) # 19 of the topic classifiers start with 12
relevant.df <- this.content.df[isEnergy, ]
relevant.dc <- relevant.df[, "directory_code"]
relevant.dc

#NOW RETRIEVING ENERGY DOCUMENTS METADATA 
makeQuery <- function(classifier) {
  this.query <- list(classifier)
  names(this.query) <- "dc"
  return(this.query)
}
queries <- lapply(as.list(relevant.dc), makeQuery)

#Now we have a list (queries) that is composed of all the individual
#queries that result from our function. Now we are good to go to
#actually execute the API calls.
this.raw.result <- GET(url = url, path = path, query = queries[[1]])
this.result <- fromJSON(rawToChar(this.raw.result$content))
names(this.result[[1]])
#NOW FOR ALL 
all.results <- vector(mode = "list",
                      length = length(relevant.dc))
for (i in 1:length(all.results)) {
  this.query <- queries[[i]]
  this.raw.answer <- GET(url = url, path = path, query = this.query)
  this.answer <- fromJSON(rawToChar(this.raw.answer$content))
  all.results[[i]] <- this.answer
  message(".", appendLF = FALSE)
  Sys.sleep(time = 1)
}

#all.results is now no empty list no more. It is filled with the answers
#the API has produced as result to our 19 queries.
#Of all the parts of the  answer, we are interested in form, date_document and of_effect. Let's
#create another function that returns just these parts as a data frame.

parseAnswer <- function(answer) {
  this.form <- answer$form
  this.date <- answer$date
  this.effect <- answer$of_effect
  result <- data.frame(form = this.form,
                       date = this.date,
                       effect = this.effect)
  return(result)
}
parseAnswer(all.results[[1]][[2]])
parsedAnswers <- lapply(all.results,
                        function(x) do.call("rbind", lapply(x, parseAnswer)))

#Let's combine these 19 data frames in a single one.

finalResult <- do.call("rbind", parsedAnswers)
class(finalResult) #data.frame

#All the final results are now contained neatly in a single data frame.
#Note that the data frame's row names are actually the document IDs.
#We can use them to retrieve the actual document's meta data.

#NOW DATES 
date.character <- "1981-05-02"
date.POSIXct <- ymd(date.character)


finalResult$date <- ymd(finalResult$date)
finalResult$effect <- ymd(finalResult$effect)
finalResult$effectDay <- wday(finalResult$effect, label = TRUE)
table(finalResult$effectDay)