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Level 0 / Project 08 - string Cleaner Starter

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Concept This project — Quiz Flashcards Diagram Browser

Estimated time: 20 minutes

Focus

  • trim, lowercase, and replace transformations

Why this project exists

Clean messy strings by stripping whitespace, lowercasing, removing special characters, and collapsing multiple spaces. You will build a multi-step cleaning pipeline and see how order of operations matters.

Run (copy/paste)

Use <repo-root> as the folder containing this repository's README.md.

cd <repo-root>/projects/level-0/08-string-cleaner-starter
python project.py --input data/sample_input.txt
pytest -q

Expected terminal output

=== String Cleaning Results ===

  "   Hello,   World!!!"  =>  "hello world"
  "***URGENT*** Check this NOW!"  =>  "urgent check this now"
  "   spaces   everywhere   in   this   line"  =>  "spaces everywhere in this line"

3 lines cleaned. Output written to data/output.json
5 passed

Expected artifacts

  • data/output.json
  • Passing tests
  • Updated notes.md

Checkpoint: Baseline code runs and all tests pass. Commit your work before continuing.

Alter it (required) — Extension

  1. Add a remove_digits() step that strips all numeric characters from the string.
  2. Add a --steps flag that lets the user choose which cleaning steps to apply (e.g. --steps strip,lower).
  3. Re-run script and tests.

Break it (required) — Core

  1. Feed in a string that is already perfectly clean -- does clean_string() return it unchanged?
  2. Feed in a string of only special characters like @#$%^&* -- does the cleaner return an empty string?
  3. Feed in a string with tab characters (\t) -- does collapse_spaces() handle tabs or only spaces?

Fix it (required) — Core

  1. Ensure collapse_spaces() also collapses tabs and other whitespace, not just spaces.
  2. Handle the all-special-characters case gracefully (return empty string without error).
  3. Add a test for the tab-handling edge case.

Checkpoint: All modifications done, tests still pass. Good time to review your changes.

Explain it (teach-back)

  1. Why does the cleaning pipeline apply steps in a specific order (strip, then lowercase, then remove specials, then collapse)?
  2. What happens if you collapse spaces before removing special characters?
  3. Why does isalnum() keep letters and digits but remove punctuation?
  4. Where would string cleaning appear in real software (search indexing, data import, form validation)?

Mastery check

You can move on when you can: - run baseline without docs, - explain one core function line-by-line, - break and recover in one session, - keep tests passing after your change.

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