Text statistics module

qwen3-30b-a3b

Pythononeshotrun 2sample 0906.0s wall

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deliverables (20%)—

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qwen3-30b-a3b: timed out

01 what the model was asked

Create textstats.py, a small text-statistics module with exactly these three functions:

1. word_count(text: str) -> int
   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.

2. top_words(text: str, n: int) -> list[tuple[str, int]]
   Count words case-insensitively (lowercase them). Return the n most frequent (word, count) pairs, most frequent first; break count ties alphabetically by word.

3. reading_time(text: str) -> int
   Estimated minutes to read at 200 words per minute, rounded up, with a minimum of 1 (even for empty text).

Use only the Python standard library.

required deliverables + checks

✗deliverable: textstats.py

✗textstats.py must contain “def word_count”

✗textstats.py must contain “def top_words”

✗textstats.py must contain “def reading_time”

pytest suite it was graded against

test_textstats.py · 38 lines · 873 B

from textstats import word_count, top_words, reading_time  def test_word_count_basic():    assert word_count("the cat sat on the mat") == 6  def test_word_count_empty():    assert word_count("") == 0  def test_word_count_punctuation():    assert word_count("Hi, there! Hi.") == 3  def test_word_count_apostrophes():    assert word_count("don't stop") == 2  def test_top_words_orders_by_count():    assert top_words("a b a c a b", 2) == [("a", 3), ("b", 2)]  def test_top_words_ties_alphabetical():    assert top_words("beta alpha", 2) == [("alpha", 1), ("beta", 1)]  def test_top_words_case_insensitive():    assert top_words("The the THE", 1) == [("the", 3)]  def test_reading_time_rounds_up():    assert reading_time(" ".join(["w"] * 401)) == 3  def test_reading_time_minimum_one():    assert reading_time("hello") == 1    assert reading_time("") == 1

02 what it did — full transcript

promptthe exact instruction sent to the model

view full prompt

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.

Reply with ONE JSON object and nothing else:
{"files": {"<relative path>": "<complete file content>", ...}}

Required deliverable files: textstats.py

SPEC:
Create textstats.py, a small text-statistics module with exactly these three functions:

1. word_count(text: str) -> int
   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.

2. top_words(text: str, n: int) -> list[tuple[str, int]]
   Count words case-insensitively (lowercase them). Return the n most frequent (word, count) pairs, most frequent first; break count ties alphabetically by word.

3. reading_time(text: str) -> int
   Estimated minutes to read at 200 words per minute, rounded up, with a minimum of 1 (even for empty text).

Use only the Python standard library.

! errorqwen3-30b-a3b: timed out

03 what it wrote

The model produced no files.

04 how it was graded

✗ error —

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906.0s

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