Use configuration files (like JSON or YAML) to manage settings, and consider using libraries like `configparser` or `pydantic` for structured configuration management and validation.

Managing configuration settings effectively is vital for developing flexible and maintainable Python applications. One common approach is to use configuration files in formats such as JSON or YAML, which allow for easy editing without modifying the source code. Libraries like configparser provide a simple way to handle INI-style configuration files, while pydantic offers robust features for structured configuration management and data validation. When loading configuration settings, always consider default values and error handling for missing or invalid configurations. You might also want to implement environment-specific configurations to accommodate different deployment environments, like development, testing, and production. For security reasons, avoid hardcoding sensitive information (like API keys) directly in your code or configuration files; consider using environment variables or secret management services instead. By following these practices, you can ensure that your Python application's configuration is manageable, secure, and adaptable.