Python Data Serialization

What Is Serialization?

Serialization converts data into a format that can be stored or sent. Deserialization converts it back into Python data.

Common formats include JSON and CSV.

import json

data = {"name": "Asha", "score": 88}
text = json.dumps(data)
restored = json.loads(text)

dumps() creates a JSON string. loads() reads a JSON string.

JSON Files

Use dump() and load() with files.

with open("score.json", "w", encoding="utf-8") as file:
    json.dump(data, file)

with open("score.json", "r", encoding="utf-8") as file:
    data = json.load(file)

JSON is readable and widely used for APIs and configuration.

CSV Files

CSV stores rows and columns as text.

import csv

with open("scores.csv", "w", newline="", encoding="utf-8") as file:
    writer = csv.writer(file)
    writer.writerow(["name", "score"])
    writer.writerow(["Asha", 88])

Use newline="" when working with CSV files to avoid unwanted blank lines on some systems.

Pickle Caution

pickle can serialize many Python objects, but loading pickle data can execute code. Never unpickle data from an untrusted source.

For data exchange, JSON is usually safer and more portable.

Custom Serialization

Some objects are not JSON serializable by default.

from dataclasses import asdict

json.dumps(asdict(student))

Convert objects into dictionaries, strings, or numbers before serializing.

Common Mistakes

A common mistake is confusing json.load() and json.loads(). The version ending in s works with strings. The version without s works with file objects.

Another mistake is expecting JSON to preserve every Python type exactly. Tuples become arrays, and non-string dictionary keys may change.

Quick Summary

• Serialization converts data for storage or transfer.
• Deserialization restores data.
• json.dumps() writes to a string.
• json.dump() writes to a file object.
• CSV is good for tabular text data.
• Avoid untrusted pickle data.
• Convert custom objects before JSON serialization.

Practice Quiz

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