csv.DictReader & in-memory streams

Read a small CSV report

Lesson 18 of 20 · 14 min · Module 6: Reliable inputs & practical reports

CSV is a common way to exchange table-shaped information. A real CSV reader understands quoted fields and column headers.

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By the end, you’ll be able to…

Read CSV by header names
Preserve quoted values and skip invalid rows

The idea

csv.DictReader turns each row into a dictionary keyed by the header. Wrap text in io.StringIO to read it in memory; this exercise does not access files on your computer.

import csv, io
rows = csv.DictReader(io.StringIO("name,minutes\nAlex,12\n"))
print(list(rows))

01Let the format reader do its job

A title such as Lists, tuples contains a comma that belongs to one field. Splitting a row on every comma loses that distinction.

02Normalize a row at the boundary

Strip the title and convert minutes before appending a clean dictionary. The rest of the application then sees a consistent shape.

03Decide what rejection means

This exercise skips invalid rows. Other applications might instead collect errors with line numbers. Choose a policy and communicate it.

Your turn

Write read_sessions(text) for CSV with title and minutes headers. Return dictionaries with a stripped, nonempty title and integer minutes greater than zero. Skip invalid rows, including missing fields and non-integer durations. Preserve valid input order and handle quoted titles containing commas.

What the checks look for

Parses and cleans valid rows
Understands a quoted comma
Skips broken, missing, and nonpositive values
Handles header-only and empty input

Try it in the editor →

Take this with you

Use a parser for a structured format, then validate the parsed values.

Go a little further

Return a separate list of rejected row numbers alongside the clean records.