Python: JSON Data Processing

Last updated: 2026-09-22

JSON (JavaScript Object Notation) is the most common data exchange format on the web. Almost all Web APIs return JSON data. Python's json module makes it easy to convert between Python objects and JSON strings.

Related Built-in Functions：object float bool dict list None int str

1. Python Objects <-> JSON Strings

▶ Example: Serializing to JSON String

Output:

# Executed successfully

Output:

{
  "name": "Zhang San",
  "age": 25,
  "is_student": false,
  "scores": [85, 92, 78],
  "address": null
}

Tip: ensure_ascii=False is important: Without this parameter, non-ASCII characters are escaped to Unicode codes. Use it to preserve original characters. indent=2 formats the output for readability. In production, use indent=None to compress into a single line, saving bandwidth.

2. JSON String -> Python Objects (Deserialization)

▶ Example: Deserializing a JSON String

Output:

# Executed successfully

(1) JSON Type to Python Type Mapping

3. JSON File I/O

▶ Example: Reading and Writing JSON Files

Output:

# Executed successfully

▶ Example: Data Persistence (Difficulty: Star-Star)

Output:

No notes yet

4. Handling Complex Data Types

By default, the json module only supports basic types. Custom objects need manual conversion:

▶ Example: Custom Serialization

Output:

# Function defined successfully

5. Common Use Cases

• Web API data: Send and receive JSON data when calling external APIs.
• Configuration files: Store configuration in JSON format — more flexible than INI.
• Data persistence: Save program data as JSON files — more structured than CSV (supports nesting).
• Data exchange: Transfer data between different languages and systems.

Related Built-in Functions：object float bool dict list None int str

❓ FAQ

📖 Summary

• json.dumps() Python -> JSON string; json.loads() JSON string -> Python
• json.dump() Python -> JSON file; json.load() JSON file -> Python
• ensure_ascii=False preserves non-ASCII characters; indent=2 formats output
• JSON type mapping: object->dict, array->list, number->int/float, null->None
• Custom types need a default serialization function

📝 Exercises

1. Beginner (Difficulty: Star): Create a dictionary containing your name, age, and three hobbies (list). Use json.dumps() to output a formatted JSON string (preserve characters, indent 2).

2. Intermediate (Difficulty: Star-Star): Write two functions: save_contacts(contacts) and load_contacts(). Save a contact list (list of dicts) to contacts.json and auto-load on program start. Each contact has a name, phone, and email.

3. Advanced (Difficulty: Star-Star-Star): Implement a "simple data exporter" using JSON. Given a student score list students = [{"name": "Zhang San", "scores": {"Chinese": 85, "Math": 92}}], output as: 1) A formatted JSON file; 2) A compressed (no indent) JSON string; 3) A JSON string with sorted keys (sort_keys=True).

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