# Created by 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)

# Set target options:
tar_option_set(
  packages = strsplit(desc::desc_get_field("Depends"), ", ")[[1]],
  # For distributed computing in tar_make(), supply a {crew} controller
  # as discussed at https://books.ropensci.org/targets/crew.html.
  controller = crew::crew_controller_local(workers = 12),
  error = "null"
  # debug = "parquet_report_cover_path_e8fc956a"
)

# Run the R scripts in the R/ folder with your custom functions:
tar_source()

# Replace the target list below with your own:
list(
  tar_target(year, 2016:2023),
  tar_target(report, c("MY", "YE", "Q1", "Q2", "Q3", "Q4")),
  tar_target(
    doc_list,
    get_report_by_year_scrape(year, report),
    pattern = cross(year, report)
  ),
  tar_target(
    committees,
    doc_list |>
      # this is the list of committees and years reported
      # if `n_*` changes, we have to go re-read that year
      group_by(committee_name, sboe_id, year) |>
      summarize(
        n_reports = n(),
        n_amended = sum(amended),
        n_docs = sum(!is.na(report_id)),
      ) |>
      arrange(sboe_id)
  ),
  tar_target(
    report_list,
    doc_list |>
      filter(!is.na(report_id)) |>
      mutate(received = coalesce(received_data, received_image)) |>
      slice_max(received, by = report_id)
  ),
  tar_target(report_list_report_id, report_list$report_id),
  tar_target(report_list_sboe_id, report_list$sboe_id),
  tar_target(report_list_received, report_list$received),
  tar_target(
    reports_raw_path,
    save_raw_report_all(
      report_list_report_id,
      report_list_sboe_id,
      report_list_received
    ),
    pattern = map(
      report_list_report_id,
      report_list_sboe_id,
      report_list_received
    ),
    format = "file_fast"
  ),
  # Gets the JSON version of the report's receipts via an internal API call,
  # that is processed into a standard table before saving as CSV.
  tar_target(
    report_receipts_csv_path,
    save_report_receipts_csv(
      report_list_report_id,
      report_list_sboe_id,
      report_list_received
    ),
    pattern = map(
      report_list_report_id,
      report_list_sboe_id,
      report_list_received
    ),
    format = "file_fast"
  ),
  # Gets the JSON version of the report's expenses via an internal API call,
  # that is processed into a standard table before saving as CSV.
  tar_target(
    report_expenditures_csv_path,
    save_report_expenditures_csv(
      report_list_report_id,
      report_list_sboe_id,
      report_list_received
    ),
    pattern = map(
      report_list_report_id,
      report_list_sboe_id,
      report_list_received
    ),
    format = "file_fast"
  ),
  tar_target(
    dirs_all,
     fs::dir_ls("data-raw/reports", glob = "**/all", recurse = TRUE, type = "directory")
  ),
  tar_target(
    dirs_receipts,
     fs::dir_ls("data-raw/reports", glob = "**/receipts", recurse = TRUE, type = "directory")
  ),
  tar_target(
    dirs_expenditures,
     fs::dir_ls("data-raw/reports", glob = "**/expenditures", recurse = TRUE, type = "directory")
  )
  # tar_target(
  #   parquet_report_cover_path,
  #   write_reports_by_sboe_id(report_list_sboe_id),
  #   pattern = map(unique(report_list_sboe_id)),
  #   format = "file_fast"
  # )
)