# Copyright 2021 Observational Health Data Sciences and Informatics
#
# This file is part of CohortGenerator
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#' Computes the checksum for a value
#'
#' @description
#' This is used as part of the incremental operations to hash a value
#' to store in a record keeping file. This function leverages the md5
#' hash from the digest package
#'
#' @param val The value to hash. It is converted to a character to perform
#' the hash.
#'
#' @return
#' Returns a string containing the checksum
#'
#' @export
computeChecksum <- function(val) {
return(sapply(as.character(val), digest::digest, algo = "md5", serialize = FALSE))
}
#' Is a task required when running in incremental mode
#'
#' @description
#' This function will attempt to check the \code{recordKeepingFile}
#' to determine if an individual operation has completed by comparing the
#' keys passed into the function with the checksum supplied
#'
#' @param ... Parameter values used to identify the key
#' in the incremental record keeping file
#'
#' @param checksum The checksum representing the operation to check
#'
#' @param recordKeepingFile A file path to a CSV file containing the record
#' keeping information.
#'
#' @param verbose When TRUE, this function will output if a particular operation
#' has completed based on inspecing the recordKeepingFile.
#'
#' @return
#' Returns TRUE if the operation has completed according to the contents of
#' the record keeping file.
#'
#' @export
isTaskRequired <- function(..., checksum, recordKeepingFile, verbose = TRUE) {
if (file.exists(recordKeepingFile)) {
recordKeeping <- readr::read_csv(recordKeepingFile, col_types = readr::cols())
task <- recordKeeping[getKeyIndex(list(...), recordKeeping), ]
if (nrow(task) == 0) {
return(TRUE)
}
if (nrow(task) > 1) {
stop("Duplicate key ", as.character(list(...)), " found in recordkeeping table")
}
if (task$checksum == checksum) {
if (verbose) {
key <- list(...)
key <- paste(sprintf("%s = '%s'", names(key), key), collapse = ", ")
ParallelLogger::logInfo("Skipping ", key, " because unchanged from earlier run")
}
return(FALSE)
} else {
return(TRUE)
}
} else {
return(TRUE)
}
}
#' Get a list of task stiaareqask required when running in incremental mode
#'
#' @description
#' This function will attempt to check the \code{recordKeepingFile}
#' to determine if a list of operations have completed by comparing the
#' keys passed into the function with the checksum supplied
#'
#' @param ... Parameter values used to identify the key
#' in the incremental record keeping file
#'
#' @param checksum The checksum representing the operation to check
#'
#' @param recordKeepingFile A file path to a CSV file containing the record
#' keeping information.
#'
#' @return
#' Returns a list of outstanding tasks based on inspecting the full contents
#' of the record keeping file
#'
#' @export
getRequiredTasks <- function(..., checksum, recordKeepingFile) {
tasks <- list(...)
if (file.exists(recordKeepingFile) && length(tasks[[1]]) > 0) {
recordKeeping <- readr::read_csv(recordKeepingFile, col_types = readr::cols())
tasks$checksum <- checksum
tasks <- tibble::as_tibble(tasks)
if (all(names(tasks) %in% names(recordKeeping))) {
idx <- getKeyIndex(recordKeeping[, names(tasks)], tasks)
} else {
idx <- c()
}
tasks$checksum <- NULL
if (length(idx) > 0) {
text <- paste(sprintf("%s = %s", names(tasks), tasks[idx, ]), collapse = ", ")
ParallelLogger::logInfo("Skipping ", text, " because unchanged from earlier run")
tasks <- tasks[-idx, ]
}
}
return(tasks)
}
#' Record a task as complete
#'
#' @description
#' This function will record a task as completed in the \code{recordKeepingFile}
#'
#' @param ... Parameter values used to identify the key
#' in the incremental record keeping file
#'
#' @param checksum The checksum representing the operation to check
#'
#' @param recordKeepingFile A file path to a CSV file containing the record
#' keeping information.
#' @param incremental When TRUE, this function will record tasks otherwise
#' it will return without attempting to perform any action
#'
#' @export
recordTasksDone <- function(..., checksum, recordKeepingFile, incremental = TRUE) {
if (!incremental) {
return()
}
if (length(list(...)[[1]]) == 0) {
return()
}
if (file.exists(recordKeepingFile)) {
recordKeeping <- readr::read_csv(recordKeepingFile, col_types = readr::cols())
idx <- getKeyIndex(list(...), recordKeeping)
if (length(idx) > 0) {
recordKeeping <- recordKeeping[-idx, ]
}
} else {
recordKeeping <- tibble::tibble()
}
newRow <- tibble::as_tibble(list(...))
newRow$checksum <- checksum
newRow$timeStamp <- Sys.time()
recordKeeping <- dplyr::bind_rows(recordKeeping, newRow)
readr::write_csv(recordKeeping, recordKeepingFile)
}
#' Used in incremental mode to save values to a file
#'
#' @description
#' When running in incremental mode, we may need to update results in a CSV
#' file. This function will replace the \code{data} in \code{fileName} based
#' on the key parameters
#'
#' @param data The data to record in the file
#'
#' @param fileName A CSV holding results in the same structure as the data
#' parameter
#'
#' @param ... Parameter values used to identify the key
#' in the results file
#'
#' @export
saveIncremental <- function(data, fileName, ...) {
if (length(list(...)[[1]]) == 0) {
return()
}
if (file.exists(fileName)) {
previousData <- readr::read_csv(fileName, col_types = readr::cols())
idx <- getKeyIndex(list(...), previousData)
if (length(idx) > 0) {
previousData <- previousData[-idx, ]
}
data <- dplyr::bind_rows(previousData, data)
}
readr::write_csv(data, fileName)
}
getKeyIndex <- function(key, recordKeeping) {
if (nrow(recordKeeping) == 0 || length(key[[1]]) == 0 || !all(names(key) %in% names(recordKeeping))) {
return(c())
} else {
key <- unique(tibble::as_tibble(key))
recordKeeping$idxCol <- 1:nrow(recordKeeping)
idx <- merge(recordKeeping, key)$idx
return(idx)
}
}
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