Python uses Python to manage configurations, including reading, parsing, and verifying configuration files

Preparation work for environmental construction: 1. Install Python: Since using Python requires Python version 3.6 or higher, please ensure that Python has been installed and set the environment variables. 2. Create a virtual environment (optional): To isolate the dependent libraries required for the project, a virtual environment can be created. 3. Install Pydantic and related dependency libraries: In a virtual environment, use the pip command to install Pydantic and related dependency libraries. Dependent class libraries: 1. Pydantic: mainly used for managing configurations, reading, parsing, and verifying configuration files. 2. pydantic [dotenv] (optional): Used to load environment variables from an. env file. The following is a complete Python code example for managing configuration files: python from pydantic import BaseModel, Field, BaseSettings #Create a Pydantic model to define and verify the configured fields and default values class AppConfig(BaseModel): #Use Field to set default values, descriptions, and other validation options for fields api_key: str = Field(..., env='API_KEY', description='API Key') #Create a configuration management class that inherits from BaseSettings class Settings(BaseSettings): #Transfer the configuration model to the configuration management class app_config: AppConfig #Instantiate Configuration Management Class settings = Settings() #Obtain the value of the configuration and return an instance of the configuration model config = settings.app_config #Using configured values api_key = config.api_key print(f'API Key: {api_key}') Data sample: You can create a file called '. env' using the following content to set environment variables: API_KEY=your_api_key_here Summary: Pydantic provides a simple and powerful way to manage configuration files, making it easier to read, parse, and verify configurations. By defining a configuration model and using validation options and annotations to increase readability, we can easily manage the configuration of the application. Meanwhile, Pydantic also supports loading environment variables from. env files, making it more convenient to use different configurations in different environments.