{
 "run_id": 2,
 "model": "llama3.2-3b",
 "mode": "oneshot",
 "challenge": "text-stats",
 "sample": 0,
 "status": "degenerate",
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 "wall_secs": 6.468571374993189,
 "slug": "run2-llama3.2-3b-oneshot-text-stats-s0",
 "challenge_title": "Text statistics module",
 "spec": "Create textstats.py, a small text-statistics module with exactly these three functions:\n\n1. word_count(text: str) -> int\n   Words are maximal runs of ASCII letters, digits, and apostrophes (regex [A-Za-z0-9']+). Return how many words text contains. Empty or word-free text returns 0.\n\n2. top_words(text: str, n: int) -> list[tuple[str, int]]\n   Count words case-insensitively (lowercase them). Return the n most frequent (word, count) pairs, most frequent first; break count ties alphabetically by word.\n\n3. reading_time(text: str) -> int\n   Estimated minutes to read at 200 words per minute, rounded up, with a minimum of 1 (even for empty text).\n\nUse only the Python standard library.",
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  "textstats.py"
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  "textstats.py": [
   "def word_count",
   "def top_words",
   "def reading_time"
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 "test_files": {
  "test_textstats.py": "from textstats import word_count, top_words, reading_time\n\n\ndef test_word_count_basic():\n    assert word_count(\"the cat sat on the mat\") == 6\n\n\ndef test_word_count_empty():\n    assert word_count(\"\") == 0\n\n\ndef test_word_count_punctuation():\n    assert word_count(\"Hi, there! Hi.\") == 3\n\n\ndef test_word_count_apostrophes():\n    assert word_count(\"don't stop\") == 2\n\n\ndef test_top_words_orders_by_count():\n    assert top_words(\"a b a c a b\", 2) == [(\"a\", 3), (\"b\", 2)]\n\n\ndef test_top_words_ties_alphabetical():\n    assert top_words(\"beta alpha\", 2) == [(\"alpha\", 1), (\"beta\", 1)]\n\n\ndef test_top_words_case_insensitive():\n    assert top_words(\"The the THE\", 1) == [(\"the\", 3)]\n\n\ndef test_reading_time_rounds_up():\n    assert reading_time(\" \".join([\"w\"] * 401)) == 3\n\n\ndef test_reading_time_minimum_one():\n    assert reading_time(\"hello\") == 1\n    assert reading_time(\"\") == 1\n"
 },
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   "challenge": "text-stats",
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   "event": "prompt",
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   "content": "You are completing a coding task in one shot. Write complete files that satisfy the spec below. Tests (pytest) will be run against your files; you cannot run them yourself.\n\nReply with ONE JSON object and nothing else:\n{\"files\": {\"<relative path>\": \"<complete file content>\", ...}}\n\nRequired deliverable files: textstats.py\n\nSPEC:\nCreate textstats.py, a small text-statistics module with exactly these three functions:\n\n1. word_count(text: str) -> int\n   Words are maximal runs of ASCII letters, digits, and apostrophes (regex [A-Za-z0-9']+). Return how many words text contains. Empty or word-free text returns 0.\n\n2. top_words(text: str, n: int) -> list[tuple[str, int]]\n   Count words case-insensitively (lowercase them). Return the n most frequent (word, count) pairs, most frequent first; break count ties alphabetically by word.\n\n3. reading_time(text: str) -> int\n   Estimated minutes to read at 200 words per minute, rounded up, with a minimum of 1 (even for empty text).\n\nUse only the Python standard library.\n"
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   "ts": "2026-07-17T16:13:33.401240+00:00",
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   "content": "{\"files\": {\"textstats.py\": \"import re\\n\\ndef word_count(text: str) -> int:\\n    return len(re.findall(r'[A-Za-z0-9]+', text))\\n\\ndef top_words(text: str, n: int) -> list[tuple[str, int]]:\\n    words = re.findall(r'\\w+', text.lower())\\n    counts = {word: words.count(word) for word in set(words)}\\n    return sorted(counts.items(), key=lambda x: (-x[1], x[0]))[:n]\\n\\ndef reading_time(text: str) -> int:\\n    if not text: return 1\\n    return -(-len(text) // 200)\"}}",
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