| import json |
| from collections import Counter |
| from pathlib import Path |
|
|
| from server import TASKS, grade |
|
|
| MANIFEST = json.loads(Path('curriculum.json').read_text()) |
| SOLUTIONS = json.loads(Path('solutions.json').read_text()) |
| VIEWER = [json.loads(s) for s in Path('viewer_train.jsonl').read_text().splitlines()] |
|
|
|
|
| def test_curriculum_shape_and_training_selection(): |
| assert len(TASKS) == len(VIEWER) == 1200 |
| assert Counter(t['family'] for t in TASKS.values()) == {k:100 for k in MANIFEST['families']} |
| assert len({(t['family'],t['bug_pattern']) for t in TASKS.values()}) == 48 |
| assert len(set(MANIFEST['arena_task_ids'])) == 50 |
| assert set(MANIFEST['arena_task_ids']) <= TASKS.keys() |
| assert {(TASKS[t]['family'],TASKS[t]['bug_pattern']) for t in MANIFEST['arena_task_ids']} == {(t['family'],t['bug_pattern']) for t in TASKS.values()} |
|
|
|
|
| def test_variations_are_real_and_case_inputs_not_duplicated(): |
| for family in MANIFEST['families']: |
| rows = [t for t in TASKS.values() if t['family']==family] |
| assert len({t['starter'] for t in rows}) == 4 |
| assert len({t['case_seed'] for t in rows}) == 25 |
| assert len({json.dumps(t['cases'],sort_keys=True) for t in rows}) == 25 |
| assert len({t['prompt'] for t in rows}) >= 25 |
| for task in TASKS.values(): |
| assert len({json.dumps(c['args'],sort_keys=True) for c in task['cases']}) == len(task['cases']) |
|
|
|
|
| def test_lossless_viewer_rows_and_manifest_totals(): |
| assert sum(len(t['cases']) for t in TASKS.values()) == MANIFEST['cases_total'] |
| assert sum(r['arena_selected'] for r in VIEWER) == 50 |
| for row in VIEWER: |
| task = TASKS[row['task_id']] |
| assert row['num_cases']==len(task['cases']) |
| assert json.loads(row['cases_json'])==task['cases'] |
| for field in ('family','bug_pattern','case_seed','prompt','starter'): |
| assert row[field]==task[field] |
|
|
|
|
| def test_independent_hand_checked_semantics(): |
| examples = { |
| 'merge-intervals': ([[[4,7],[1,4],[2,3]]], [[1,7]]), |
| 'moving-sums': ([[2,-1,4],2], [1,3]), |
| 'weighted-mean': ([[2,8],[1,3]], 6.5), |
| 'stable-unique': ([[3,1,3,2,1]], [3,1,2]), |
| 'run-length': (['猫猫abbb'], [['猫',2],['a',1],['b',3]]), |
| 'luhn': (['79927398713'], True), |
| 'edit-distance': (['kitten','sitting'], 3), |
| 'meeting-rooms': ([[[0,1],[1,2]]], 1), |
| 'nearest-percentile': ([[1,2,3,4,5],50], 3), |
| 'fifo-inventory': ([[[2,10],[4,20]],3], [40,[[3,20]]]), |
| 'csv-row': (['"a,b","c""d",'], ['a,b','c"d','']), |
| 'shortest-path': ([{'a':[['b',9],['c',2]],'c':[['b',1]],'b':[['d',2]]},'a','d'], 5), |
| } |
| for family,(args,expected) in examples.items(): |
| result = grade(SOLUTIONS[family],{'cases':[{'args':args,'expected':expected}]}) |
| assert result['passed']==1, (family,result) |
|
|
