Add basic pipeline for data fetching

Signed-off-by: Liang Zhang <[email protected]>

NAMESPACE

@@ -4,6 +4,7 @@ export(fetch_data)
 export(fetch_parameterized)
 export(prepare_fetch_data)
 export(preproc_data)
+export(use_targets)
 export(wrangle_data)
 import(rlang)
 import(tidyselect)

R/use_targets.R

@@ -0,0 +1,31 @@
+#' Create standard data fetching targets pipeline script
+#'
+#' This function creates a standard data fetching targets pipeline script
+#' for you to fill in.
+#'
+#' @return NULL (invisible). This function is called for its side effects.
+#' @export
+use_targets <- function() {
+  script <- "_targets.R"
+  if (file.exists(script)) {
+    cli::cli_alert_info(
+      sprintf("File {.file %s} exists. Stash and retry.", script)
+    )
+    return(invisible())
+  }
+  copy_success <- file.copy(
+    system.file(
+      "pipelines", "use_targets.R",
+      package = "tarflow.iquizoo"
+    ),
+    script
+  )
+  if (!copy_success) {
+    cli::cli_alert_danger("Sorry, copy template failed.")
+    return(invisible())
+  }
+  cli::cli_alert_success(
+    sprintf("File {.file %s} crated successfully.", script)
+  )
+  return(invisible())
+}

inst/pipelines/use_targets.R

@@ -0,0 +1,40 @@
+# Created by tarflow.iquizoo::use_targets().
+# Follow the comments below to fill in this target script.
+# Then follow the manual to check and run the pipeline:
+#   https://books.ropensci.org/targets/walkthrough.html#inspect-the-pipeline
+
+# Load packages required to define the pipeline:
+library(targets)
+# library(tarchetypes) # Load other packages as needed.
+
+# Set target options:
+tar_option_set(
+  packages = c("tarflow.iquizoo", "preproc.iquizoo") # packages that your targets need to run
+  # format = "qs", # Optionally set the default storage format. qs is fast.
+  #
+  # For distributed computing in tar_make(), supply a {crew} controller
+  # as discussed at https://books.ropensci.org/targets/crew.html.
+  # Choose a controller that suits your needs. For example, the following
+  # sets a controller with 2 workers which will run as local R processes:
+  #
+  #   controller = crew::crew_controller_local(workers = 2)
+  #
+  # Set other options as needed.
+)
+
+# Run the R scripts in the R/ folder with your custom functions:
+tar_source()
+# source("other_functions.R") # Source other scripts as needed.
+
+tbl_params <- tibble::tribble(
+  ~course_name, ~course_period,
+  # replace course name and course period with your own
+  "# COURSE NAME", "# COURSE PERIOD"
+)
+
+# Replace the target list below with your own:
+list(
+  # change what to scores or raw_data if you want to
+  tarflow.iquizoo::prepare_fetch_data(tbl_params, what = "all")
+  # more targets goes here
+)