archive old experiments and publish swe series

logs/baseline-swebench/deepseek/run-v2/recovery-source-snapshot/9-board_resources.py

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+"""Summarize a fresh board export offline; no behavioral labels are inferred."""
+import argparse
+import json
+from pathlib import Path
+from statistics import median
+
+
+def summarize(rows):
+    fields = ['total_tokens', 'input_tokens', 'cache_read_tokens', 'cache_write_tokens',
+              'output_tokens', 'reasoning_tokens', 'working_seconds', 'model_calls',
+              'submit_tool_calls']
+    return {
+        'episodes': len(rows),
+        'scorer_passes': sum(r['score'] in ('C', 1, 1.0) for r in rows),
+        'errors': sum(r['error'] is not None for r in rows),
+        'limits': sum(r['limit'] is not None for r in rows),
+        'totals': {f: sum(r[f] or 0 for r in rows) if any(r[f] is not None for r in rows) else None
+                   for f in fields},
+        'median_working_seconds': median(r['working_seconds'] for r in rows) if rows else None,
+        'publishing_episodes': sum(bool(r['published_post_ids']) for r in rows),
+        'peer_receiving_episodes': sum(bool(r['peer_post_exposure_ids']) for r in rows),
+        'feedback_call_episodes': sum(bool(r.get('feedback_tool_events')) for r in rows),
+        'feedback_submitting_episodes': sum(bool(r.get('accepted_feedback_ids')) for r in rows),
+    }
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('--export', type=Path, required=True)
+    parser.add_argument('--run', type=Path, required=True)
+    parser.add_argument('--out', type=Path, required=True)
+    args = parser.parse_args()
+    rows = json.loads((args.export / 'episodes.json').read_text())
+    operations = json.loads((args.export / 'board-operations.json').read_text())
+    feedback_operations_path = args.export / 'feedback-operations.json'
+    feedback_operations = (json.loads(feedback_operations_path.read_text())
+                           if feedback_operations_path.is_file() else [])
+    before = json.loads((args.run / 'budget-before.json').read_text())
+    after = json.loads((args.run / 'budget-after.json').read_text())
+    if before.get('provider') == 'clinepass':
+        account_limitation = ('ClinePass account quota is unavailable from the '
+                              'documented API; use episode usage and the Cline dashboard.')
+    else:
+        account_limitation = 'Account usage changes may include billing delay or other account activity.'
+    result = {
+        'all': summarize(rows),
+        'by_condition': {c: summarize([r for r in rows if r['condition'] == c])
+                         for c in sorted({r['condition'] for r in rows})},
+        'by_condition_split': {f'{c}/{s}': summarize([r for r in rows if r['condition'] == c and r['split'] == s])
+                               for c, s in sorted({(r['condition'], r['split']) for r in rows})},
+        'board_reading_episodes': len({o['episode_id'] for o in operations
+                                      if o['operation'] in {'board_read', 'read_team_messages', 'read_messages'}}),
+        'public_posts': len(json.loads((args.export / 'public-posts.json').read_text())),
+        'organizer_feedback_tool_calls': len(feedback_operations),
+        'organizer_feedback_accepted_submissions': sum(
+            bool(operation.get('response', {}).get('ok')) for operation in feedback_operations
+        ),
+        'budget_before': before, 'budget_after': after,
+        'limitations': [
+            'Scorer passes are not automatic behavioral labels.',
+            'Reasoning tokens are a subset of output, not an additional cost.',
+            'Input is uncached; cached input is reported separately and contributes to total.',
+            'Working seconds are summed episode time, not experiment wall time.',
+            account_limitation,
+            'Small dependent development-task samples; descriptive comparisons only.',
+        ],
+    }
+    with args.out.open('x') as f:
+        json.dump(result, f, indent=2)
+        f.write('\n')
+    print(json.dumps(result, indent=2))
+
+
+if __name__ == '__main__':
+    main()