Serializing Python objects into JSON or other formats using Python, or deserializing JSON or other formatted data into Python objects

Environmental preparation: 1. Install Python 3 and pip package management tools. 2. Create and activate a virtual environment (optional). Class library dependencies: 1. Python: A Python library for data validation and parsing. Installing Pydantic: Install Pydantic using the following command: pip install pydantic Data sample: Suppose we have a 'Person' class that contains two attributes, namely 'name' and 'age'. python from pydantic import BaseModel class Person(BaseModel): name: str age: int Complete sample code: python from pydantic import BaseModel import json #Define a Person class that inherits from BaseModel class Person(BaseModel): name: str age: int #Instantiating a Person object person = Person(name="John", age=30) #Serializing Python objects into JSON json_data = person.json() Print (json_data) # Output: {"name": "John", "age": 30} #Deserialize JSON data into Python objects json_str = '{"name": "Alice", "age": 25}' person_from_json = Person.parse_raw(json_str) Print (person_from_json) # Output: Person (name='Alice ', age=25) Summary: Pydantic is a powerful library that can be used for data validation and parsing. It uses Python's type hints and annotations to define the data model and provides easy-to-use methods for serializing and deserializing Python objects. Using Pydantic can simplify the process of data validation and transformation, and improve development efficiency.