dhis2 api demo.R

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# dhis api access
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# https://www.dhis2.org/doc/snapshot/en/developer/html/apas07.html
# https://github.com/jason-p-pickering/datim-validation
# http://www.r-fiddle.org/#/fiddle?id=wHglXleC&version=1
# :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

# setup =======================================================================
  require(RCurl)
  require(XML)
  require(httr)
  require(rjson)
  require(plyr)
  pass <- "admin:district"
  username <- "admin"
  password <- "district"
  url1 <- "https://play.dhis2.org/demo/api/"
  url3 <- ".xml?paging=false&links=false"
  
# specify targets =============================================================
  targets <- c("dataElements",
               "indicators",
               "dataSets",
               "programIndicators",
               "eventReports",
               "organisationUnits")
# get metadata ================================================================
  for (i in 1:length(targets)) {
    url2 <- targets[i]
    url <- paste0(url1, url2, url3)
    response <- getURL(url,
                       userpwd=pass,
                       httpauth=1L, 
                       header=FALSE,
                       ssl.verifypeer=FALSE)
  # parse the result
    bri <- xmlParse(response)
  # get the root
    r <- xmlRoot(bri)
  # parse out names and IDs
    name <- xmlSApply(r[[targets[i]]], xmlGetAttr, "name")
    id <- xmlSApply(r[[targets[i]]], xmlGetAttr, "id")
  # bind
    temp <- cbind(name, id)
  # recast as a data frame
    df <- as.data.frame(temp,
                        stringsAsFactors=FALSE,
                        row.names=1:nrow(temp))
    assign(targets[i], df)
    remove(df)
  }
  
# get the data ================================================================
# monthly periods
  periods <- paste(paste0("2015",
                          sprintf("%02d", seq(from=1, to=12, by=1)),
                          collapse=";"),
                   paste0("2014",
                          sprintf("%02d", seq(from=1, to=12, by=1)),
                          collapse=";"),
                   paste0("2013",
                          sprintf("%02d", seq(from=1, to=12, by=1)),
                          collapse=";"),
                   paste0("2012",
                          sprintf("%02d", seq(from=1, to=12, by=1)),
                          collapse=";"),
                   paste0("2011",
                          sprintf("%02d", seq(from=1, to=12, by=1)),
                          collapse=";"),
                   paste0("2010",
                          sprintf("%02d", seq(from=1, to=12, by=1)),
                          collapse=";"),
                   sep=";")
# specify the indicators
  ind <- c("ANC 1-3 Dropout Rate")
  indShort <- c("anc13drop")
# get
  for (i in 1:length(ind)) {
  # build the url
    indID <- indicators$id[indicators$name==ind[i]]
    urlA <- "https://play.dhis2.org/demo/api/analytics.json?"
    urlB <- paste0("dimension=dx:", indID)
    urlC <- paste0("dimension=pe:", periods)
    urlD <- paste0("dimension=ou:", organisationUnits$id[1:5])
    urlE <- "displayProperty=NAME&skipMeta=false"
  # URLencode
    url <- URLencode(paste(paste0(urlA, urlB),
                           urlC, urlD, urlE, 
                           sep="&"))
    r <- httr::GET(url, httr::authenticate(username,password),
                   httr::timeout(60))
    r <- httr::content(r, "text")
  # Convert the JSON to an R data structure
    d <- jsonlite::fromJSON(r, flatten=TRUE)
  # Get the metadata map
    metadata <- as.data.frame(unlist(d$metaData$names), stringsAsFactor=F)
    names(metadata)<-"name"
    metadata$uid <- rownames(metadata)
  # Get the base data
    data <- as.data.frame(d$rows,stringsAsFactors=FALSE)
  # Use the original response to get the names of the columns
    names(data) <- d$headers$column
  # Remap the UIDs in the response to something human readable
    data$Data<-plyr::mapvalues(data$Data, metadata$uid,
                               as.character(metadata$name), warn_missing=FALSE)
    data$ou <- plyr::mapvalues(data[,c("Organisation unit")],
                               metadata$uid,
                               as.character(metadata$name),
                               warn_missing=FALSE)
  # Change the column types
    data$Period <- as.numeric(as.character(data$Period))
    data$Value <- as.numeric(as.character(data$Value))
    assign(paste("df", indShort[i], sep="."), data)
    remove(data)
  }