When building a real application like a To-Do List, you need to save the user’s data so it persists after the program closes. The most common ways to serialize data in Python are using the JSON and CSV formats.
JSON (JavaScript Object Notation) is a lightweight data-interchange format. Python parses JSON into standard native types like dicts, lists, strings, and booleans.
To convert a Python dictionary into a JSON string, you use json.dumps():
import json
data = {'name': 'Alice', 'score': 100}
print(json.dumps(data)){"name": "Alice", "score": 100} If you are reading from a file, use json.load() to directly deserialize the file-like object into a Python object:
import json
# Simulating a file containing JSON
json_str = '{"status": "ok", "count": 5}'
with open('data.json', 'w') as f:
f.write(json_str)
with open('data.json', 'r') as f:
parsed = json.load(f)
print(parsed['count'])5
CSV (Comma Separated Values) is a classic format for tabular data. Instead of manually splitting strings with .split(',')—which breaks if commas are inside quoted fields—you should always use the csv module.
You can read a CSV file row by row as lists:
import csv
with open('temp.csv', 'w', newline='') as f:
f.write('id,name\n1,Alice\n2,Bob')
with open('temp.csv', 'r') as f:
reader = csv.reader(f)
for row in reader:
print(row)['id', 'name'] ['1', 'Alice'] ['2', 'Bob']
Writing delimited rows is just as easy using csv.writer():
import csv
with open('out.csv', 'w', newline='') as f:
writer = csv.writer(f)
writer.writerow(['item', 'cost'])
writer.writerow(['apple', 1.5])
with open('out.csv', 'r') as f:
print(f.read().strip())item,cost apple,1.5
If your CSV has a header row, it is usually much safer and easier to read each row as a dictionary using csv.DictReader():
import csv
with open('dict.csv', 'w', newline='') as f:
f.write('id,name\n10,Charlie')
with open('dict.csv', 'r') as f:
reader = csv.DictReader(f)
for row in reader:
print(row['name'])Charlie
Similarly, csv.DictWriter() makes it simple to write dictionaries back into CSV rows:
import csv
with open('dict_out.csv', 'w', newline='') as f:
writer = csv.DictWriter(f, fieldnames=['user', 'age'])
writer.writeheader()
writer.writerow({'user': 'Dave', 'age': 30})
with open('dict_out.csv', 'r') as f:
print(f.read().strip())user,age Dave,30
Why is the csv module preferred over manually calling .split(',') on a text file line?
Manual splitting breaks if commas are present inside quoted fields, whereas the csv module handles these edge cases correctly. — Manual splitting breaks if commas are inside quoted fields; always use the csv module to handle edge cases.
Which method should you use to convert a Python dictionary into a JSON string?
json.dumps() — json.dumps() stands for 'dump string'. It serializes a Python object into a JSON formatted string.
What is the difference between json.load() and json.loads()?
json.load() reads from a file-like object, while json.loads() parses a string. — json.loads() is used for strings ('s' for string), whereas json.load() is used for reading directly from a file.
Fix the bug! The code attempts to read a JSON string but it fails. Correct the function used and fix the syntax error in the JSON string so it successfully prints 'Jane'.
Remove the trailing comma in the JSON string, and use json.loads() for strings instead of json.load().
import json
bad_json = '{"name": "Jane", "age": 25}'
# Fix the errors below
data = json.loads(bad_json)
print(data['name'])Complete the script to use csv.DictReader to print the 'score' for each row.
Initialize csv.DictReader(f) and iterate over it, printing row['score'].
import csv
# Setup test file
with open('scores.csv', 'w') as f:
f.write('name,score\nAlice,90\nBob,85')
with open('scores.csv', 'r') as f:
# Write your DictReader code here
reader = csv.DictReader(f)
for row in reader:
print(row['score'])