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Digital · Guided lesson

Read CSV with explicit types

About 19 minutes · 4 reading + 15 practice and checks
Time includes reading, practice, and questions. Extra videos or further study are optional.
See this course’s project requirements

A local command-line converter that validates fictional attendance CSV, writes JSON to a chosen output and reports rejected rows without altering input.

Keep your working files in your own notebook or software. Save a private description, checklist, and work link in My Proof.

What to include

  • A converter contract with two accepted and two rejected records.
  • A CSV-to-typed-record trace with invalid-value evidence.
  • A failure report distinguishing rejected rows from failed runs.
  • A checked JSON output with 2 accepted and 2 rejected entries.
  • A reusable command contract and a missing-argument test.
  • A repeatable local CSV converter with failure and preservation evidence.

Review and revise

Use these criteria to check your work and choose what to improve.

  • The implementation or declared simulation follows the supplied contract and retains inspectable original inputs.
  • Normal, boundary and rejected cases are recorded with expected versus observed results.
  • The changed case has a correct explanation and does not rely on hidden state.
  • The project includes source, outputs, instructions and honest tool, privacy and verification limits.
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Before you begin

The idea in everyday life

CSV row A,30 yields strings A and 30. Row E, ten cannot be converted to an integer.

The idea

CSV fields arrive as text. Convert minutes to an integer deliberately; reject invalid values rather than silently interpreting a string or replacing it with zero.

Follow along

Read CSV with explicit types — original worked practice

CSV fields arrive as text. Convert minutes to an integer deliberately; reject invalid values rather than silently interpreting a string or replacing it with zero.

CSV row A,30 yields strings A and 30. Row E, ten cannot be converted to an integer.

  1. 1. Step 1

    Inspect DictReader’s field names.

    You should see: The expected order is id, minutes.

    This keeps the rule and its observable result together.

  2. 2. Step 2

    Read A and convert int(30 text).

    You should see: The accepted object has numeric minutes 30.

    This keeps the rule and its observable result together.

  3. 3. Step 3

    Try converting ten and record the exception.

    You should see: ValueError; the row is rejected.

    This keeps the rule and its observable result together.

  4. 4. Step 4

    Keep headers, line numbers and typed outputs together.

    You should see: A CSV-to-typed-record trace with invalid-value evidence.

    This keeps the rule and its observable result together.

Now change one thing

Replace E, ten with E,12. Enter minutes stored for E.

Your work

What to finish

A CSV-to-typed-record trace with invalid-value evidence.

Common mistake

Watch for this

Trusting CSV text as an integer without converting it and checking the allowed range.

How can I tell I understand it?

Explain and demonstrate the required distinction: CSV fields arrive as text. Convert minutes to an integer deliberately; reject invalid values rather than silently interpreting a string or replacing it with zero. Show a changed input and the expected result without weakening this contract.

Try 3 questions

Quick knowledge check

Answer all 3 questions. Get at least 2 right and the lesson completes automatically.

Not yet passed

You’ll get an explanation for each answer. Signed in? Your results save to your account.

1What type does CSV initially give the minutes field?
2What should int(ten text) cause here?
3What prevents malformed headers being misread?
0 of 3 answeredApply the lesson to a short question, then review the explanation.
2
Finish this lesson

Pass the check. We’ll save the progress.

Answer all 3 questions above and get at least 2 right. You can review the explanations and try again.

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Sources and further reading

Explore the references behind this lesson.

docs.python.org — csv.html
Source & access notes · checked 2026-10-01

Relevant documented module/API behavior inspected during expansion authoring; actual execution evidence is recorded separately. No grant eligibility is established.

Access: Official page retrieved with the web reader on 2026-10-01. Documentation reading does not certify execution in every native tool or browser.

Reuse: Original local practice files, fictional data, worked examples and questions. Concepts paraphrased and linked; source exercises are not copied.

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