18.1 Files, CSV, and JSON

Before you start

Work through the earlier fundamentals chapters. Use a Python 3 interpreter and run each example locally.

Core concepts

Use pathlib.Path for filesystem paths and with to close open files even when an error occurs. Specify UTF-8 when reading and writing text. Writing with mode w replaces an existing file; choose output paths deliberately.

Use csv.DictReader for header-based CSV records rather than splitting on commas: quoted fields may contain commas. CSV values are strings, so validate and convert fields. JSON supports nested objects and arrays; decoding untrusted or malformed input can fail.

Worked example

import csv
from io import StringIO

sample = "name,status\nweb-01,healthy\nweb-02,critical\n"
for row in csv.DictReader(StringIO(sample)):
    if row["status"] == "critical":
        print(row["name"])

Mini lab

Parse the sample CSV and serialize critical rows as JSON. Expected: [{"name": "web-02", "status": "critical"}]. Then try input with a header but no rows.

import csv
import json
from io import StringIO

sample = "name,status\nweb-01,healthy\nweb-02,critical\n"
rows = [row for row in csv.DictReader(StringIO(sample))
        if row["status"] == "critical"]
print(json.dumps(rows))

Knowledge check

Why not parse CSV with line.split(",")?

Common mistake

Validate required headers before processing records. Never overwrite the input file while you are reading it.

Completion checklist

• Run the example and explain its output.
• Complete the mini lab without copying the solution.
• Test an edge case and explain how the code handles it.
• Answer the knowledge check in your own words.

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