Buyer interview signal scoring for a burning problem

The exact vocabulary the automated check enforces: keys, tokens, entry points, and worked examples. Generated from the verification source.

{
 "constants": {},
 "entryName": "score_buyer_interviews",
 "expectNote": "expect is the comparison-space value (your return value goes through normalize first when one is published)",
 "hiddenCaseCount": 11,
 "hiddenCaseNames": [
  "strong_clears_bar_exactly_8",
  "problem_just_below_bar",
  "solution_at_bar_exactly_6",
  "solution_just_below_bar",
  "rounding_7_5",
  "mixed_problems_and_solutions",
  "single_respondent",
  "empty_scores_no_data",
  "custom_bars_at_bar_not_flagged",
  "decimal_input_scores",
  "two_problems_both_clear"
 ],
 "inputKeys": [
  "label",
  "problem_bar",
  "problems",
  "scores",
  "solution_bar",
  "solutions"
 ],
 "normalizeSource": "def _buyer_signal_normalize(r):\n    try:\n        def ac(a):\n            return None if a is None else round(float(a), 1)\n\n        def rows(key):\n            return [{\"label\": str(x[\"label\"]), \"average\": ac(x[\"average\"]), \"band\": str(x[\"band\"]),\n                     \"below_bar\": bool(x[\"below_bar\"])} for x in r[key]]\n        flags = [{\"kind\": str(f[\"kind\"]), \"label\": str(f[\"label\"]), \"average\": ac(f[\"average\"]),\n                  \"bar\": round(float(f[\"bar\"]), 1)} for f in r[\"below_threshold_flags\"]]\n        return {\"problems\": rows(\"problems\"), \"solutions\": rows(\"solutions\"), \"below_threshold_flags\": flags}\n    except Exception:\n        return repr(r)\n",
 "returnShapes": [
  [
   "below_threshold_flags",
   "problems",
   "solutions"
  ],
  "no-data"
 ],
 "signature": "def score_buyer_interviews(inp):",
 "submission": "python exposing the entry function; inp is one input object; graded on held-out cases",
 "tier": "calculator",
 "visibleCases": [
  {
   "expect": {
    "below_threshold_flags": [],
    "problems": [
     {
      "average": 9.5,
      "band": "burning",
      "below_bar": false,
      "label": "P1"
     }
    ],
    "solutions": []
   },
   "input": {
    "problems": [
     {
      "label": "P1",
      "scores": [
       9,
       10,
       9,
       10
      ]
     }
    ],
    "solutions": []
   },
   "name": "single_burning_problem"
  }
 ],
 "vocabulary": [
  "average",
  "band",
  "bar",
  "below_bar",
  "below_threshold_flags",
  "burning",
  "kind",
  "label",
  "likely-adopted",
  "mild",
  "moderate",
  "nice-to-have",
  "no-data",
  "not-a-problem",
  "not-wanted",
  "problem",
  "problem_bar",
  "problems",
  "scores",
  "solution",
  "solution_bar",
  "solutions",
  "strong"
 ]
}