Homework: Word-Frequency Report

作业: 词频报告

≈ 45 min · python-file-io python-strings python-lists · Open in WolfCode

Read → process → write. Five helpers, one orchestrator. The shape of every batch data job.

The five functions

read_words(in_path) — lowercased word list
count_word_frequencies(words) — dict word→count
top_n_words(freq, n) — sorted [(word, count), …]
format_report(top_words) — formatted string
write_report(in_path, out_path, n) — orchestrator

End-to-end

Python · runnable

with open("input.txt", "w") as f:
    f.write("the quick brown fox jumps over the lazy dog\nthe fox is quick and brown\n")

def read_words(in_path):
    with open(in_path) as f:
        return f.read().lower().split()

def count_word_frequencies(words):
    freq = {}
    for w in words:
        freq[w] = freq.get(w, 0) + 1
    return freq

def top_n_words(freq, n):
    items = sorted(freq.items(), key=lambda p: (-p[1], p[0]))
    return items[:n]

def format_report(top_words):
    return "".join(f"{w}: {c}\n" for w, c in top_words)

def write_report(in_path, out_path, n=10):
    words = read_words(in_path)
    freq = count_word_frequencies(words)
    top = top_n_words(freq, n)
    with open(out_path, "w") as f:
        f.write(format_report(top))

write_report("input.txt", "out.txt", n=5)
with open("out.txt") as f:
    print(f.read())

Loading Python runtime (~5 MB, one-time)…

Acceptance criteria

All 9 tests pass
write_report calls at least 3 of the 4 helpers
top_n_words sorts count-desc, then alphabetical-asc
format_report produces "word: count\n" per entry