GPT-6.1 Sol (effort default (no reasoning-effort override) · thinking on) on Optimise an O(n·m) price lookup to <4s on 200k orders with byte-identical output
OGPT-6.1 Soldefault · thinking on · Codex CLI 0.163.0 (codex exec --json) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.06
- Wall time
- 2m
- Human step-ins
- 0
- Outcome
- Pass
Compare with other models on this task →
Summary
Exact prompt
# Task: make price_orders fast `pricing.py::price_orders` is correct but O(orders × prices). Production runs it on 200k orders, 100k price rows and 20k promos and it takes hours. Make it fast: it must produce EXACTLY the same output (same list, same order, same rounding, same tie-breaking described in the docstring) and run on 200k/100k/20k in under ~3 seconds on this machine. `make_data.py` generates test data. Keep the function name/signature; stdlib only; no network. Add a small correctness test comparing against the original on random data.
Needs sorting+bisect while preserving subtle tie-breaking (last row wins on equal timestamps) and promo max-pct; a tie-heavy dataset catches near-misses. Timing threshold is wall-clock. Original benchmark task written for usecaserank.com. Headless, offline run on a reproducible fixture. Cost shown is a list-price API-equivalent estimate (run on a ChatGPT subscription, not billed).
Success criteria: 1. Output must be exactly equal (==) to the original implementation on 5 seeded datasets, including one tie-heavy dataset with many equal timestamps and short promo windows. 2. On 200k orders / 100k prices / 20k promos, a single run must take < 4.0 s wall-clock (run in a subprocess capped at 30 s; timeout = fail).
Setup notes: Use Case Scout batch4 case d03-perf-price-lookup (offline fixture). Prepared with batch4/prepare.sh on the shared box; only TASK.md + starting files were copied to the agent machine, hidden key/tests stayed on the box. Prompt = TASK.md verbatim on stdin. Flags: --json -s workspace-write --skip-git-repo-check --ephemeral --ignore-user-config --ignore-rules -C <workdir>. Scored on the box with the scout's scorer: `python score.py WORKDIR`. Single run, no retries. User-level AGENTS.md (846 bytes, sha256 83ec4fe50da8) may have been in context; --ignore-user-config does not document excluding it. Serving model not confirmed: requested via -m; the event log does not echo the serving model id. Price source is secondary (pricing.json verification='secondary', https://www.actuia.com/en/news/ai-api-pricing-in-october-2026-050-to-50-for-output/), not an official OpenAI price page. Score: 1/1 checks. Cost is an ESTIMATE: measured tokens x pricing.json list price (ChatGPT plan, nothing billed); input_tokens include cached reads; output_tokens include reasoning tokens. Tool calls 9 (3 failed, recovered). Single run.
Estimated cost List-price estimate; not actually billed.
Metrics
- Estimated cost
- $0.06
- Wall time
- 2m
- Human step-ins
- 0
- Turns
- 1
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| OGPT-6.1 Solopenai/gpt-6.1-soleffort default (no reasoning-effort override) · thinking on | 117,056 | 3,358 | $0.06 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: GPT-6.1 Sol (openai/gpt-6.1-sol, effort default (no reasoning-effort override) · thinking on) via
Codex CLI 0.163.0 (codex exec --json), cloud. - It counts as a success only if it meets every success criterion: 1. Output must be exactly equal (==) to the original implementation on 5 seeded datasets, including one tie-heavy dataset with many equal timestamps and short promo windows. 2. On 200k orders / 100k prices / 20k promos, a single run must take < 4.0 s wall-clock (run in a subprocess capped at 30 s; timeout = fail).
- Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.
How runs are scored: Methodology.
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Automated checks
Trust 80% comes from these checks (how Trust % works).
- Run date is not in the future : passed
- Model is in the dated pricing table : passed
- Cost recomputed from tokens matches : passed
- Cached tokens are consistent : passed
- Output throughput is plausible : passed
- Autonomy matches step-ins : passed
- Step-ins do not exceed turns : passed
- Retries agree with first-try result : passed
- Evidence log SHA-256 matches : passed
- Evidence log is substantial : passed
Evidence log
{"type": "thread.started", "thread_id": "01a16422-4128-7832-98d2-c4e749a83ef7"}
{"type": "turn.started"}
{"type": "item.completed", "item": {"id": "item_0", "type": "agent_message", "text": "I\u2019ll inspect the pricing rules, replace the repeated scans with indexes, and verify exact results and runtime on the full dataset.\n"}}
{"type": "item.started", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc \"pwd && rg --files -g 'AGENTS.md' -g '*.py'\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc \"pwd && rg --files -g 'AGENTS.md' -g '*.py'\"", "aggregated_output": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/151_d03/work\npricing.py\nmake_data.py\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'cat pricing.py make_data.py'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'cat pricing.py make_data.py'", "aggregated_output": "\"\"\"Price lookup: for each order, find the price of its SKU effective at the order time\n(latest price row with effective_at <= order ts; ties: the row appearing LAST in the list wins).\nOrders before any price for their SKU get None. Discounts: apply the latest promo for the SKU\nwhose window [start, end) contains the order ts (if several, the largest pct wins).\"\"\"\n\ndef price_orders(orders, prices, promos):\n out = []\n for o in orders:\n best = None\n for idx, p in enumerate(prices):\n if p[\"sku\"] == o[\"sku\"] and p[\"effective_at\"] <= o[\"ts\"]:\n if best is None or p[\"effective_at\"] >= best[\"effective_at\"]:\n best = p\n if best is None:\n out.append({\"order_id\": o[\"id\"], \"unit\": None, \"total\": None})\n continue\n pct = 0\n for pr in promos:\n if pr[\"sku\"] == o[\"sku\"] and pr[\"start\"] <= o[\"ts\"] < pr[\"end\"]:\n pct = max(pct, pr[\"pct\"])\n unit = round(best[\"price\"] * (100 - pct) / 100, 2)\n out.append({\"order_id\": o[\"id\"], \"unit\": unit, \"total\": round(unit * o[\"qty\"], 2)})\n return out\nimport random\ndef make(n_orders, n_prices, n_promos, seed=1):\n r = random.Random(seed); skus = [f\"S{i}\" for i in range(n_prices // 20 + 1)]\n prices = [{\"sku\": r.choice(skus), \"effective_at\": r.randint(0, 10**6), \"price\": round(r.uniform(1, 500), 2)} for _ in range(n_prices)]\n promos = []\n for _ in range(n_promos):\n s = r.randint(0, 10**6); promos.append({\"sku\": r.choice(skus), \"start\": s, \"end\": s + r.randint(1, 50000), \"pct\": r.choice([5, 10, 15, 20, 30])})\n orders = [{\"id\": i, \"sku\": r.choice(skus), \"ts\": r.randint(0, 10**6), \"qty\": r.randint(1, 9)} for i in range(n_orders)]\n return orders, prices, promos\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc 'ls -la'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc 'ls -la'", "aggregated_output": "total 20\ndrwxr-xr-x 6 bob bob 4096 Oct 22 11:02 .\ndrwxrwxr-x 3 bob bob 4096 Oct 22 11:02 ..\ndr-xr-xr-x 2 bob bob 40 Oct 22 11:02 .agents\ndr-xr-xr-x 2 bob bob 40 Oct 22 11:02 .aws\ndr-xr-xr-x 2 bob bob 40 Oct 22 11:02 .codex\ndr-xr-xr-x 2 bob bob 40 Oct 22 11:02 .git\n-rw-r--r-- 1 bob bob 552 Oct 22 10:08 TASK.md\n-rw-r--r-- 1 bob bob 640 Oct 22 10:08 make_data.py\n-rw-r--r-- 1 bob bob 1128 Oct 22 10:08 pricing.py\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc 'git status --short'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc 'git status --short'", "aggregated_output": "fatal: not a git repository (or any of the parent directories): .git\n", "exit_code": 128, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_5", "type": "command_execution", "command": "/bin/bash -lc 'cp pricing.py /tmp/pricing_original.py'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_5", "type": "command_execution", "command": "/bin/bash -lc 'cp pricing.py /tmp/pricing_original.py'", "aggregated_output": "", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_6", "type": "file_change", "changes": [{"path": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/151_d03/work/pricing.py", "kind": "update"}], "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_6", "type": "file_change", "changes": [{"path": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/151_d03/work/pricing.py", "kind": "update"}], "status": "completed"}}
{"type": "item.started", "item": {"id": "item_7", "type": "command_execution", "command": "/bin/bash -lc \"python - <<'PY'\nfrom pathlib import Path\noriginal = Path('/tmp/pricing_original.py').read_text().split('def price_orders', 1)[1]\nPath('test_pricing.py').write_text('''import copy\nimport random\nimport unittest\n\nfrom pricing import price_orders\n\n\ndef original_price_orders''' + original + '''\n\nclass PricingTests(unittest.TestCase):\n def test_random_matches_original(self):\n for seed in range(100):\n r = random.Random(seed)\n # Small timestamp range deliberately creates ties and shared boundaries.\n prices = [{\\\"sku\\\": r.randrange(5), \\\"effective_at\\\": r.randrange(15),\n \\\"price\\\": r.choice([1.005, 2.675, 19.99, 123.45])}\n for _ in range(r.randrange(80))]\n promos = [{\\\"sku\\\": r.randrange(5), \\\"start\\\": r.randrange(15),\n \\\"end\\\": r.randrange(20), \\\"pct\\\": r.choice([-10, 0, 5, 20, 100])}\n for _ in range(r.randrange(50))]\n orders = [{\\\"id\\\": i, \\\"sku\\\": r.randrange(6), \\\"ts\\\": r.randrange(-1, 21),\n \\\"qty\\\": r.randrange(1, 10)} for i in range(100)]\n before = copy.deepcopy((orders, prices, promos))\n with self.subTest(seed=seed):\n self.assertEqual(price_orders(orders, prices, promos),\n original_price_orders(orders, prices, promos))\n self.assertEqual((orders, prices, promos), before)\n\n def test_boundaries_ties_and_order(self):\n prices = [{\\\"sku\\\": \\\"A\\\", \\\"effective_at\\\": 5, \\\"price\\\": 10},\n {\\\"sku\\\": \\\"A\\\", \\\"effective_at\\\": 5, \\\"price\\\": 20}]\n promos = [{\\\"sku\\\": \\\"A\\\", \\\"start\\\": 5, \\\"end\\\": 10, \\\"pct\\\": 30},\n {\\\"sku\\\": \\\"A\\\", \\\"start\\\": 7, \\\"end\\\": 12, \\\"pct\\\": 10}]\n orders = [{\\\"id\\\": i, \\\"sku\\\": \\\"A\\\", \\\"ts\\\": ts, \\\"qty\\\": 3}\n for i, ts in enumerate([10, 4, 7, 12, 5])]\n result = price_orders(orders, prices, promos)\n self.assertEqual(result, original_price_orders(orders, prices, promos))\n self.assertEqual([row[\\\"unit\\\"] for row in result], [18.0, None, 14.0, 20.0, 14.0])\n self.assertEqual(price_orders([], prices, promos), [])\n\n\nif __name__ == \\\"__main__\\\":\n unittest.main()\n''')\nPY\npython -m unittest -v\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_7", "type": "command_execution", "command": "/bin/bash -lc \"python - <<'PY'\nfrom pathlib import Path\noriginal = Path('/tmp/pricing_original.py').read_text().split('def price_orders', 1)[1]\nPath('test_pricing.py').write_text('''import copy\nimport random\nimport unittest\n\nfrom pricing import price_orders\n\n\ndef original_price_orders''' + original + '''\n\nclass PricingTests(unittest.TestCase):\n def test_random_matches_original(self):\n for seed in range(100):\n r = random.Random(seed)\n # Small timestamp range deliberately creates ties and shared boundaries.\n prices = [{\\\"sku\\\": r.randrange(5), \\\"effective_at\\\": r.randrange(15),\n \\\"price\\\": r.choice([1.005, 2.675, 19.99, 123.45])}\n for _ in range(r.randrange(80))]\n promos = [{\\\"sku\\\": r.randrange(5), \\\"start\\\": r.randrange(15),\n \\\"end\\\": r.randrange(20), \\\"pct\\\": r.choice([-10, 0, 5, 20, 100])}\n for _ in range(r.randrange(50))]\n orders = [{\\\"id\\\": i, \\\"sku\\\": r.randrange(6), \\\"ts\\\": r.randrange(-1, 21),\n \\\"qty\\\": r.randrange(1, 10)} for i in range(100)]\n before = copy.deepcopy((orders, prices, promos))\n with self.subTest(seed=seed):\n self.assertEqual(price_orders(orders, prices, promos),\n original_price_orders(orders, prices, promos))\n self.assertEqual((orders, prices, promos), before)\n\n def test_boundaries_ties_and_order(self):\n prices = [{\\\"sku\\\": \\\"A\\\", \\\"effective_at\\\": 5, \\\"price\\\": 10},\n {\\\"sku\\\": \\\"A\\\", \\\"effective_at\\\": 5, \\\"price\\\": 20}]\n promos = [{\\\"sku\\\": \\\"A\\\", \\\"start\\\": 5, \\\"end\\\": 10, \\\"pct\\\": 30},\n {\\\"sku\\\": \\\"A\\\", \\\"start\\\": 7, \\\"end\\\": 12, \\\"pct\\\": 10}]\n orders = [{\\\"id\\\": i, \\\"sku\\\": \\\"A\\\", \\\"ts\\\": ts, \\\"qty\\\": 3}\n for i, ts in enumerate([10, 4, 7, 12, 5])]\n result = price_orders(orders, prices, promos)\n self.assertEqual(result, original_price_orders(orders, prices, promos))\n self.assertEqual([row[\\\"unit\\\"] for row in result], [18.0, None, 14.0, 20.0, 14.0])\n self.assertEqual(price_orders([], prices, promos), [])\n\n\nif __name__ == \\\"__main__\\\":\n unittest.main()\n''')\nPY\npython -m unittest -v\"", "aggregated_output": "/bin/bash: line 1: python: command not found\n/bin/bash: line 49: python: command not found\n", "exit_code": 127, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_8", "type": "command_execution", "command": "/bin/bash -lc \"python - <<'PY'\nfrom make_data import make\nfrom pricing import price_orders\nfrom time import perf_counter\norders, prices, promos = make(200_000, 100_000, 20_000)\nfor run in range(3):\n start = perf_counter()\n result = price_orders(orders, prices, promos)\n elapsed = perf_counter() - start\n assert len(result) == 200_000\n assert all(row['order_id'] == order['id'] for row, order in zip(result, orders))\n print(f'Run {run + 1}: {elapsed:.3f}s, {len(result):,} rows')\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_8", "type": "command_execution", "command": "/bin/bash -lc \"python - <<'PY'\nfrom make_data import make\nfrom pricing import price_orders\nfrom time import perf_counter\norders, prices, promos = make(200_000, 100_000, 20_000)\nfor run in range(3):\n start = perf_counter()\n result = price_orders(orders, prices, promos)\n elapsed = perf_counter() - start\n assert len(result) == 200_000\n assert all(row['order_id'] == order['id'] for row, order in zip(result, orders))\n print(f'Run {run + 1}: {elapsed:.3f}s, {len(result):,} rows')\nPY\"", "aggregated_output": "/bin/bash: line 1: python: command not found\n", "exit_code": 127, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_9", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nfrom pathlib import Path\noriginal = Path('/tmp/pricing_original.py').read_text().split('def price_orders', 1)[1]\nPath('test_pricing.py').write_text('''import copy\nimport random\nimport unittest\n\nfrom pricing import price_orders\n\n\ndef original_price_orders''' + original + '''\n\nclass PricingTests(unittest.TestCase):\n def test_random_matches_original(self):\n for seed in range(100):\n r = random.Random(seed)\n # Small ranges deliberately create ties and shared boundaries.\n prices = [{\\\"sku\\\": r.randrange(5), \\\"effective_at\\\": r.randrange(15),\n \\\"price\\\": r.choice([1.005, 2.675, 19.99, 123.45])}\n for _ in range(r.randrange(80))]\n promos = [{\\\"sku\\\": r.randrange(5), \\\"start\\\": r.randrange(15),\n \\\"end\\\": r.randrange(20), \\\"pct\\\": r.choice([-10, 0, 5, 20, 100])}\n for _ in range(r.randrange(50))]\n orders = [{\\\"id\\\": i, \\\"sku\\\": r.randrange(6), \\\"ts\\\": r.randrange(-1, 21),\n \\\"qty\\\": r.randrange(1, 10)} for i in range(100)]\n before = copy.deepcopy((orders, prices, promos))\n with self.subTest(seed=seed):\n self.assertEqual(price_orders(orders, prices, promos),\n original_price_orders(orders, prices, promos))\n self.assertEqual((orders, prices, promos), before)\n\n def test_boundaries_ties_and_order(self):\n prices = [{\\\"sku\\\": \\\"A\\\", \\\"effective_at\\\": 5, \\\"price\\\": 10},\n {\\\"sku\\\": \\\"A\\\", \\\"effective_at\\\": 5, \\\"price\\\": 20}]\n promos = [{\\\"sku\\\": \\\"A\\\", \\\"start\\\": 5, \\\"end\\\": 10, \\\"pct\\\": 30},\n {\\\"sku\\\": \\\"A\\\", \\\"start\\\": 7, \\\"end\\\": 12, \\\"pct\\\": 10}]\n orders = [{\\\"id\\\": i, \\\"sku\\\": \\\"A\\\", \\\"ts\\\": ts, \\\"qty\\\": 3}\n for i, ts in enumerate([10, 4, 7, 12, 5])]\n result = price_orders(orders, prices, promos)\n self.assertEqual(result, original_price_orders(orders, prices, promos))\n self.assertEqual([row[\\\"unit\\\"] for row in result], [18.0, None, 14.0, 20.0, 14.0])\n self.assertEqual(price_orders([], prices, promos), [])\n\n\nif __name__ == \\\"__main__\\\":\n unittest.main()\n''')\nPY\npython3 -m unittest -v\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_9", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nfrom pathlib import Path\noriginal = Path('/tmp/pricing_original.py').read_text().split('def price_orders', 1)[1]\nPath('test_pricing.py').write_text('''import copy\nimport random\nimport unittest\n\nfrom pricing import price_orders\n\n\ndef original_price_orders''' + original + '''\n\nclass PricingTests(unittest.TestCase):\n def test_random_matches_original(self):\n for seed in range(100):\n r = random.Random(seed)\n # Small ranges deliberately create ties and shared boundaries.\n prices = [{\\\"sku\\\": r.randrange(5), \\\"effective_at\\\": r.randrange(15),\n \\\"price\\\": r.choice([1.005, 2.675, 19.99, 123.45])}\n for _ in range(r.randrange(80))]\n promos = [{\\\"sku\\\": r.randrange(5), \\\"start\\\": r.randrange(15),\n \\\"end\\\": r.randrange(20), \\\"pct\\\": r.choice([-10, 0, 5, 20, 100])}\n for _ in range(r.randrange(50))]\n orders = [{\\\"id\\\": i, \\\"sku\\\": r.randrange(6), \\\"ts\\\": r.randrange(-1, 21),\n \\\"qty\\\": r.randrange(1, 10)} for i in range(100)]\n before = copy.deepcopy((orders, prices, promos))\n with self.subTest(seed=seed):\n self.assertEqual(price_orders(orders, prices, promos),\n original_price_orders(orders, prices, promos))\n self.assertEqual((orders, prices, promos), before)\n\n def test_boundaries_ties_and_order(self):\n prices = [{\\\"sku\\\": \\\"A\\\", \\\"effective_at\\\": 5, \\\"price\\\": 10},\n {\\\"sku\\\": \\\"A\\\", \\\"effective_at\\\": 5, \\\"price\\\": 20}]\n promos = [{\\\"sku\\\": \\\"A\\\", \\\"start\\\": 5, \\\"end\\\": 10, \\\"pct\\\": 30},\n {\\\"sku\\\": \\\"A\\\", \\\"start\\\": 7, \\\"end\\\": 12, \\\"pct\\\": 10}]\n orders = [{\\\"id\\\": i, \\\"sku\\\": \\\"A\\\", \\\"ts\\\": ts, \\\"qty\\\": 3}\n for i, ts in enumerate([10, 4, 7, 12, 5])]\n result = price_orders(orders, prices, promos)\n self.assertEqual(result, original_price_orders(orders, prices, promos))\n self.assertEqual([row[\\\"unit\\\"] for row in result], [18.0, None, 14.0, 20.0, 14.0])\n self.assertEqual(price_orders([], prices, promos), [])\n\n\nif __name__ == \\\"__main__\\\":\n unittest.main()\n''')\nPY\npython3 -m unittest -v\"", "aggregated_output": "test_boundaries_ties_and_order (test_pricing.PricingTests.test_boundaries_ties_and_order) ... ok\ntest_random_matches_original (test_pricing.PricingTests.test_random_matches_original) ... ok\n\n----------------------------------------------------------------------\nRan 2 tests in 0.095s\n\nOK\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_10", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nfrom make_data import make\nfrom pricing import price_orders\nfrom time import perf_counter\norders, prices, promos = make(200_000, 100_000, 20_000)\nfor run in range(3):\n start = perf_counter()\n result = price_orders(orders, prices, promos)\n elapsed = perf_counter() - start\n assert len(result) == 200_000\n assert all(row['order_id'] == order['id'] for row, order in zip(result, orders))\n print(f'Run {run + 1}: {elapsed:.3f}s, {len(result):,} rows')\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_10", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nfrom make_data import make\nfrom pricing import price_orders\nfrom time import perf_counter\norders, prices, promos = make(200_000, 100_000, 20_000)\nfor run in range(3):\n start = perf_counter()\n result = price_orders(orders, prices, promos)\n elapsed = perf_counter() - start\n assert len(result) == 200_000\n assert all(row['order_id'] == order['id'] for row, order in zip(result, orders))\n print(f'Run {run + 1}: {elapsed:.3f}s, {len(result):,} rows')\nPY\"", "aggregated_output": "Run 1: 0.554s, 200,000 rows\nRun 2: 0.760s, 200,000 rows\nRun 3: 0.761s, 200,000 rows\n", "exit_code": 0, "status": "completed"}}
{"type": "item.completed", "item": {"id": "item_11", "type": "agent_message", "text": "Updated `pricing.py` to use per-SKU sorting and a promo heap, preserving output order, rounding, and tie-breaking without mutating inputs.\n\nFull 200k/100k/20k benchmark: **0.55\u20130.76 seconds** across three runs.\n\nAdded `test_pricing.py`: 100 randomized comparisons against the original plus boundary and tie cases. All tests pass with `python3 -m unittest -v`."}}
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