test_that("the corpus contains no K-prefix rows, so the Direct leg omits K", {
  con <- .ensure_session()
  n <- DBI::dbGetQuery(con,
    "SELECT COUNT(*) AS n FROM long WHERE LEFT(item_code, 1) = 'K'")$n
  expect_equal(n, 0)

  sql_files <- c("20-spending_long.sql", "22-spending_long_harmonized.sql")
  for (f in sql_files) {
    txt <- paste(readLines(system.file("sql", f, package = "uscogdata")),
                 collapse = " ")
    expect_false(grepl("'K'", txt, fixed = TRUE),
                 label = paste(f, "must not reference the inert K prefix"))
  }
})

test_that("expenditure_concept defaults to direct and preserves today's numbers", {
  gov <- "010000226085"                      # Alabama state government
  base <- cog_spending(gov, years = 2019, category = "Police")
  expl <- cog_spending(gov, years = 2019, category = "Police",
                       expenditure_concept = "direct")
  expect_equal(base$amt_nominal, expl$amt_nominal)
  expect_false("intergovernmental" %in% base$spend_subtype)
})

test_that("expenditure_concept = 'total' adds an intergovernmental subtype", {
  gov <- "010000226085"
  d <- cog_spending(gov, years = 2019, category = "Police",
                    expenditure_concept = "direct")
  t <- cog_spending(gov, years = 2019, category = "Police",
                    expenditure_concept = "total")
  expect_true("intergovernmental" %in% t$spend_subtype)
  # Direct rows are untouched; Total only ever ADDS. Use %in% rather than
  # != : a category = NULL result can contain a NULL-subtype group (codes
  # with no summary_categories row, e.g. E16/E21/E85/F16/F85/G16/G21/G85),
  # and `NA != "intergovernmental"` is NA, not TRUE, which would silently
  # smuggle an all-NA phantom row into dt.
  dt <- t[!(t$spend_subtype %in% "intergovernmental"), ]
  expect_equal(sort(dt$amt_nominal), sort(d$amt_nominal))
  expect_gt(sum(t$amt_nominal), sum(d$amt_nominal))
})

test_that("legacy-era Total does not collapse to Direct (the is_aggregate trap)", {
  # In the wide era the IG dollars live almost entirely on aggregate-flagged
  # rows. A Total leg that inherited the Direct leg's NOT is_aggregate filter
  # would silently return Total == Direct here.
  gov <- "010000226085"
  d <- cog_spending(gov, years = 2011, category = "Education K-12",
                    expenditure_concept = "direct")
  t <- cog_spending(gov, years = 2011, category = "Education K-12",
                    expenditure_concept = "total")
  expect_true("intergovernmental" %in% t$spend_subtype)
  ig <- sum(t$amt_nominal[t$spend_subtype == "intergovernmental"])
  expect_gt(ig, 0)
  expect_gt(sum(t$amt_nominal), sum(d$amt_nominal))
})

test_that("the IG leg never includes the L-- family total", {
  con <- .ensure_session()
  codes <- DBI::dbGetQuery(con,
    "SELECT DISTINCT item_code FROM ig_long")$item_code
  expect_false(any(grepl("--$", codes)))
  expect_true(all(substr(codes, 1, 1) %in% c("M", "L")))
})

test_that("expenditure_concept rejects unknown values", {
  expect_error(
    cog_spending("010000226085", years = 2019, expenditure_concept = "gross"),
    class = "rlang_error"
  )
})

test_that("total composes with basis = 'raw' and basis = 'harmonized'", {
  gov <- "010000226085"
  h <- cog_spending(gov, years = 2011, category = "Education K-12",
                    expenditure_concept = "total", basis = "harmonized")
  r <- cog_spending(gov, years = 2011, category = "Education K-12",
                    expenditure_concept = "total", basis = "raw")
  ig_h <- sum(h$amt_nominal[h$spend_subtype == "intergovernmental"])
  ig_r <- sum(r$amt_nominal[r$spend_subtype == "intergovernmental"])
  # The only IG harmonization rule is M38 -> M36 (year-disjoint), so the IG
  # total must agree between bases even though the code labels may differ.
  expect_equal(ig_h, ig_r)
})

test_that("recipe = and expenditure_concept = 'total' together aborts", {
  expect_error(
    cog_spending("121011212191", 2020L, recipe = "corrections_combined",
                expenditure_concept = "total"),
    class = "uscogdata_recipe_concept_conflict"
  )
})

test_that("aggregate-sourced IG dollars are flagged aggregate_fallback = TRUE (bool_or, not bool_and)", {
  # Regression test: .build_verb_sql() originally used bool_and(is_aggregate)
  # for aggregate_fallback, which is correct for the Direct leg (a group can
  # never mix aggregate and non-aggregate rows there -- spending_long filters
  # NOT is_aggregate) but wrong for the IG leg. The wide era is dense -- every
  # government has a $0 row for every code in a family -- so a $0 leaf sits in
  # the same (year, gov, subtype, category) group as the real aggregate row
  # and flips bool_and() to FALSE. Measured: AL state 2011 had $5,740,775,000
  # of aggregate-sourced IG dollars (Corrections $31,358,000 + Education K-12
  # $5,152,385,000 + General Government $557,032,000) reporting
  # aggregate_fallback = FALSE under bool_and(), with the only TRUE row being
  # Transit Utilities at $0. bool_or() reports all of them correctly.
  gov <- "010000226085"
  t <- cog_spending(gov, years = 2011, category = "Education K-12",
                    expenditure_concept = "total")
  ig <- t[t$spend_subtype == "intergovernmental", ]
  expect_equal(nrow(ig), 1L)
  expect_true(ig$aggregate_fallback)
  expect_true(nzchar(ig$notes))
  expect_match(ig$notes, "Aggregate fallback applied", fixed = TRUE)
})

test_that("legacy aggregate IG codes are year-disjoint from their modern leaf components", {
  # The safety of ig_long's deliberate omission of `NOT is_aggregate` (see
  # inst/sql/24-ig_long.sql) rests entirely on each legacy code's AGGREGATE
  # instance being year-disjoint from the modern leaf codes it rolls up --
  # if a future corpus rebuild ever back-filled a leaf into a year where the
  # code is still flagged aggregate, `total` would silently double-count and
  # this suite would still pass. This test fails loudly if that ever
  # happens.
  #
  # Note the invariant is scoped to the AGGREGATE flag, not bare code
  # presence: M89/L89 do NOT disappear after the wide era the way M47/L47
  # do -- they continue past 2011 as their OWN independent leaf line item
  # (is_aggregate = FALSE) alongside M91-93/L91-93, which is fine because a
  # non-aggregate M89/L89 no longer represents a rollup of those codes.
  # (Verified in the fixture: M89/L89 are is_aggregate = TRUE only in 2011,
  # when M91-93/L91-93 don't exist yet; from 2012 on M89/L89 are
  # is_aggregate = FALSE leaves coexisting with M91-93/L91-93.)
  #
  # Pairs are the M/L-prefixed components (this package's ig_long only
  # covers M/L; other prefixes in the same rollup, e.g. N/O/P/Q/R, fall
  # outside its domain and are irrelevant here) enumerated in
  # cog_pipeline's data/wide_to_long_xwalk.csv `full_desc` column (read
  # once at authoring time, not at test time -- this test stays offline):
  #   M47 "To local governments, total (includes N47, O47, P47, R47, and M94)"
  #   M89 "To local governments, total (incl N89, O89, P89, R89, M91, M92, and M93)"
  #   L47 "To state government (includes L94)"
  #   L89 "To state government (includes L91, L92, and L93)"
  con <- .ensure_session()
  pairs <- list(
    list(aggregate = "M47", components = "M94"),
    list(aggregate = "M89", components = c("M91", "M92", "M93")),
    list(aggregate = "L47", components = "L94"),
    list(aggregate = "L89", components = c("L91", "L92", "L93"))
  )
  agg_years_by_code <- DBI::dbGetQuery(con,
    "SELECT DISTINCT year, item_code FROM ig_long WHERE is_aggregate")
  codes_by_year <- DBI::dbGetQuery(con, "SELECT DISTINCT year, item_code FROM ig_long")

  for (p in pairs) {
    agg_years <- agg_years_by_code$year[agg_years_by_code$item_code == p$aggregate]
    for (yr in agg_years) {
      codes_yr <- codes_by_year$item_code[codes_by_year$year == yr]
      has_component <- any(p$components %in% codes_yr)
      expect_false(
        has_component,
        label = sprintf(
          "year %s has aggregate-flagged %s co-occurring with a modern component (%s)",
          yr, p$aggregate, paste(p$components, collapse = ",")
        )
      )
    }
  }
})

test_that(".verb_spendrev rejects expenditure_concept = 'total' for a non-spending view_base", {
  # cog_revenue() never exposes expenditure_concept and always resolves it
  # to the "direct" default, so there is no revenue codepath that reaches
  # this today -- but .verb_spendrev() is shared, and nothing else stops a
  # future caller from passing expenditure_concept = "total" alongside
  # view_base = "revenue_annotated", which would UNION expenditure M/L rows
  # into a revenue result. Exercise the internal helper directly.
  expect_error(
    uscogdata:::.verb_spendrev(
      verb = "cog_revenue_test", view_base = "revenue_annotated",
      subtype_col = "revenue_subtype",
      flow_prefixes = c("T", "A", "U", "B", "C", "D"),
      call = quote(cog_revenue_test()),
      govid = "010000226085", years = 2019L, category = NULL,
      per_capita = FALSE, adjust_to_year = NULL, basis = "raw",
      recipe = NULL, expenditure_concept = "total"
    ),
    class = "uscogdata_expenditure_concept_unsupported"
  )
})

test_that("cog_geographic_rollup refuses expenditure_concept = 'total'", {
  expect_error(
    cog_geographic_rollup(
      govids = list(state = "010000226085"),
      category = "Police", years = 2019,
      expenditure_concept = "total"
    ),
    class = "uscogdata_concept_not_aggregatable"
  )
})

test_that("cog_peer_compare refuses expenditure_concept = 'total'", {
  expect_error(
    cog_peer_compare(
      target_govid = "010000226085", peers = "010000226085",
      category = "Police", years = 2019,
      expenditure_concept = "total"
    ),
    class = "uscogdata_concept_not_aggregatable"
  )
})

test_that("the refusal message names the fix and the reason", {
  err <- tryCatch(
    cog_geographic_rollup(govids = list(state = "010000226085"),
                          category = "Police", years = 2019,
                          expenditure_concept = "total"),
    condition = function(e) e
  )
  msg <- paste(conditionMessage(err), collapse = " ")
  expect_match(msg, "direct")
  expect_match(msg, "double-count|double count")
  expect_match(msg, "cog_geographic_rollup")

  # Test that cog_peer_compare's message names its own function
  err2 <- tryCatch(
    cog_peer_compare(target_govid = "010000226085", peers = "010000226085",
                     category = "Police", years = 2019,
                     expenditure_concept = "total"),
    condition = function(e) e
  )
  msg2 <- paste(conditionMessage(err2), collapse = " ")
  expect_match(msg2, "direct")
  expect_match(msg2, "double-count|double count")
  expect_match(msg2, "cog_peer_compare")
})

test_that("both cross-government verbs still accept the direct default", {
  expect_no_error(
    cog_geographic_rollup(govids = list(state = "010000226085"),
                          category = "Police", years = 2019)
  )
  expect_no_error(
    cog_peer_compare(target_govid = "010000226085", peers = "010000226085",
                     category = "Police", years = 2019)
  )
})

test_that("provenance always records the expenditure concept", {
  d <- cog_spending("010000226085", years = 2019, category = "Police")
  t <- cog_spending("010000226085", years = 2019, category = "Police",
                    expenditure_concept = "total")
  expect_equal(attr(d, "provenance")$expenditure_concept, "direct")
  expect_equal(attr(t, "provenance")$expenditure_concept, "total")
  # The note explains the non-obvious part: how legacy IG was assembled.
  expect_true(nzchar(attr(t, "provenance")$expenditure_concept_note))
  expect_true(is.na(attr(d, "provenance")$expenditure_concept_note) ||
              !nzchar(attr(d, "provenance")$expenditure_concept_note))
})

test_that("the provenance schema documents expenditure_concept", {
  sch <- jsonlite::fromJSON(
    system.file("schemas", "provenance-v1.json", package = "uscogdata"),
    simplifyVector = FALSE
  )
  expect_true("expenditure_concept" %in% names(sch$properties))
})