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#' Function to list all prediction jobs in a project
#'
#' @param project character. Either (1) a character string giving the unique alphanumeric
#' identifier for the project, or (2) a list containing the element projectId with this
#' identifier.
#' @param status character. The status of the desired jobs: one of JobStatus$Queue,
#' JobStatus$InProgress, orJobStatus$Error. If NULL (default), queued and inprogress jobs
#' are returned.
#' @return Dataframe with one row for each prediction job in the queue,
#' with the following columns:
#' \describe{
#' \item{status}{Prediction job status; one of JobStatus$Queue, JobStatus$InProgress, or
#' JobStatus$Error}
#' \item{predictJobId}{Character string specifying the job id}
#' \item{modelId}{Character string specifying the model from which
#' predictions have been requested}
#' \item{projectId}{Character string specifying the project that contains the model}
#' }
#' @examples
#' \dontrun{
#' projectId <- "59a5af20c80891534e3c2bde"
#' GetPredictJobs(projectId)
#' }
#' @export
GetPredictJobs <- function(project, status = NULL) {
projectId <- ValidateProject(project)
routeString <- UrlJoin("projects", projectId, "predictJobs")
query <- if (is.null(status)) NULL else list(status = status)
rawPredictJobStatus <- DataRobotGET(routeString, query = query)
predictJobStatus <- rawPredictJobStatus
predictJobId <- rawPredictJobStatus$id
predictJobStatus$id <- NULL
predictJobStatus$predictJobId <- predictJobId
return(as.dataRobotPredictJobStatus(predictJobStatus))
}
PredictJobRoute <- function(projectId, predictJobId) {
return(UrlJoin("projects", projectId, "predictJobs", predictJobId))
}
#' Request information about a predict job
#'
#' @inheritParams DeleteProject
#' @param predictJobId Character string specifying the job id
#' @return list with following elements:
#' \describe{
#' \item{status}{Prediction job status; an element of JobStatus, e.g. JobStatus$Queue}
#' \item{predictJobId}{Character string specifying the job id}
#' \item{modelId}{Character string specifying the model from which
#' predictions have been requested}
#' \item{projectId}{Character string specifying the project that contains the model}
#' }
#' @examples
#' \dontrun{
#' projectId <- "59a5af20c80891534e3c2bde"
#' initialJobs <- GetPredictJobs(project)
#' job <- initialJobs[[1]]
#' predictJobId <- job$predictJobId
#' GetPredictJob(projectId, predictJobId)
#' }
#' @export
GetPredictJob <- function(project, predictJobId) {
projectId <- ValidateProject(project)
routeString <- PredictJobRoute(projectId, predictJobId)
response <- DataRobotGET(routeString, followLocation = FALSE)
idIndex <- which(names(response) == "id")
names(response)[idIndex] <- "predictJobId"
as.dataRobotPredictJobStatus(response)
}
as.dataRobotPredictJobStatus <- function(inList) {
elements <- c("status",
"projectId",
"modelId",
"predictJobId")
ApplySchema(inList, elements)
}
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