Python - CSV

Overview

Estimated time: 20–30 minutes

CSV is a common interchange format. Learn how to read and write CSV safely using the standard library’s csv module.

Learning Objectives

• Read and write CSV files with csv.reader/csv.writer and DictReader/DictWriter.
• Handle newlines and encoding correctly across platforms.
• Customize dialects (delimiter, quotechar) and avoid common pitfalls.

Prerequisites

• Files & I/O basics (open, context managers)

Examples

import csv
from pathlib import Path

rows = [
    {"id": 1, "name": "Ada"},
    {"id": 2, "name": "Alan"},
]

# Write
with Path("people.csv").open("w", newline="", encoding="utf-8") as f:
    w = csv.DictWriter(f, fieldnames=["id", "name"])
    w.writeheader()
    w.writerows(rows)

# Read
with Path("people.csv").open("r", newline="", encoding="utf-8") as f:
    r = csv.DictReader(f)
    for row in r:
        print(row)

Expected Output: dict rows printed with id and name fields.

Common Pitfalls

• On Windows, pass newline="" to open when using csv to avoid blank lines.
• Always specify the encoding (usually utf-8); be deliberate with files from Excel/legacy systems.
• Don’t parse CSV with split—use the csv module for proper quoting/escaping.

Best Practices

• Prefer DictReader/DictWriter for clearer code.
• Validate and sanitize data; be robust to missing columns and extra whitespace.
• Document delimiters and quote conventions if you deviate from the default dialect.

Checks for Understanding

1. Why is newline="" important when writing CSV on Windows?
2. When should you prefer DictWriter over writer?

Exercises

1. Read a CSV with a semicolon delimiter; write a cleaned version with a comma delimiter and trimmed fields.
2. Aggregate a CSV of transactions by user, outputting totals.