| import json |
| import unittest |
|
|
| from ingest import ingest_meta |
| from metrics import SEED, compute |
|
|
|
|
| class MetricLockTests(unittest.TestCase): |
| def test_moses_seed_metrics_are_canonical(self): |
| metrics = compute(*SEED["MO§ES (ccusage)"]) |
|
|
| self.assertAlmostEqual(metrics["yield"], 18436.98, places=2) |
| self.assertAlmostEqual(metrics["leverage"], 2042.2, places=1) |
| self.assertAlmostEqual(metrics["dev10x"], 3.31, places=2) |
| self.assertAlmostEqual(metrics["avg_cost_1m"], 0.527, places=3) |
|
|
| def test_cascade_identity_holds_for_every_seed_row(self): |
| for name, raw in SEED.items(): |
| with self.subTest(operator=name): |
| metrics = compute(*raw) |
| self.assertIsNotNone(metrics["dev10x"]) |
|
|
| lhs = ( |
| metrics["transmission"] |
| * metrics["commitment"] |
| * metrics["reuse"] |
| ) |
|
|
| self.assertAlmostEqual(lhs, metrics["leverage"], places=12) |
|
|
|
|
| class CodexParserLockTests(unittest.TestCase): |
| def test_alpha_path_uses_output_times_two_baseline(self): |
| payload = { |
| "data": [ |
| { |
| "inputTokens": 1_000, |
| "cachedInputTokens": 3_000, |
| "outputTokens": 200, |
| "reasoningOutputTokens": 50, |
| } |
| ] |
| } |
|
|
| input_tokens, output_tokens, cache_create, cache_read, meta = ingest_meta( |
| json.dumps(payload) |
| ) |
|
|
| self.assertEqual(input_tokens, 500) |
| self.assertEqual(output_tokens, 250) |
| self.assertEqual(cache_create, 500) |
| self.assertEqual(cache_read, 3_000) |
| self.assertEqual(meta["source"], "codex") |
| self.assertIs(meta["estimated"], True) |
| self.assertTrue(meta["caveat"].startswith("* AA 2:1 baseline")) |
|
|
| def test_beta_path_uses_claude_operator_ratio(self): |
| payload = { |
| "totals": { |
| "input_tokens": 2_000, |
| "cached_input_tokens": 5_000, |
| "output_tokens": 300, |
| "reasoning_output_tokens": 100, |
| } |
| } |
| operator_profile = {"model_type": "claude", "io_ratio": 1.25} |
|
|
| input_tokens, output_tokens, cache_create, cache_read, meta = ingest_meta( |
| json.dumps(payload), operator_profile=operator_profile |
| ) |
|
|
| self.assertEqual(input_tokens, 500) |
| self.assertEqual(output_tokens, 400) |
| self.assertEqual(cache_create, 1_500) |
| self.assertEqual(cache_read, 5_000) |
| self.assertEqual(meta["source"], "codex") |
| self.assertIs(meta["estimated"], True) |
| self.assertTrue(meta["caveat"].startswith("* Claude operating-ratio 1.250:1")) |
|
|
|
|
| if __name__ == "__main__": |
| unittest.main() |
|
|
