The Word Counter

An easy Python interview practice problem on DataDriven. Write the Python and run it against test cases, with instant feedback.

Domain
Python
Difficulty
easy
Seniority
L3
Asked in
phData

Problem

Each whitespace-separated token in text is a word, possibly with any of the characters .,!?;:'"()- stuck to either end; those edge characters are not part of the word, but every other symbol is. Return how many times each word appears, skipping any token made up only of those edge characters.

How many times does each word show up in a file?

Example 1

Input:

text = "Hello world hello World"

Output:

{"hello":2,"world":2}

Example 2

Input:

text = "Ship it! Ship it... (now)"

Output:

{"ship":2,"it":2,"now":1}

Worked solution and explanation

Why this problem exists in real interviews

This tests text processing fundamentals: splitting, case normalization, punctuation stripping, and frequency counting. It is a complete mini-pipeline that mirrors real NLP preprocessing.

Break down the requirements

Step 1: Split the text on whitespace

Use .split() to handle multiple spaces and newlines.

Step 2: Normalize each word: lowercase and strip punctuation

Convert to lowercase and remove non-alphanumeric characters from the edges of each word.

Step 3: Count occurrences in a dict

Skip empty strings that result from stripping and accumulate counts.

The solution

Split, normalize, strip punctuation, count
def count_word_frequency(text: str) -> dict:
    words = text.lower().split()
    freq = {}
    for raw_word in words:
        word = raw_word.strip(".,!?;:'\"()-")
        if word:
            freq[word] = freq.get(word, 0) + 1
    return freq

Common follow-up questions