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When designing APIs that bridge between programming languages and external data formats (like JSON, XML, etc.), maintain language-specific naming conventions in your code while using aliases to accommodate external data formats. For Python APIs:

1. Use snake_case for internal field names following Python conventions
2. Define aliases for external formats that use different conventions (e.g., camelCase in JSON)
3. Document methods clearly with parentheses in references (e.g., model_dump() not just model_dump)
4. Present JSON examples with proper formatting for readability

Example:

from pydantic import BaseModel, Field

class UserProfile(BaseModel):
    user_id: int = Field(validation_alias="userId", serialization_alias="userId") 
    first_name: str = Field(validation_alias="firstName", serialization_alias="firstName")
    
    # Python-native usage in code
    # user = UserProfile(user_id=1, first_name="John")
    
    # External data validation (JSON)
    # user = UserProfile.model_validate({"userId": 1, "firstName": "John"})
    
    # Example of well-formatted JSON output in documentation
    # import json
    # print(json.dumps(user.model_dump(by_alias=True), indent=2))
    # """
    # {
    #   "userId": 1,
    #   "firstName": "John"
    # }
    # """

This approach creates a clear separation between your language-specific implementation and external API contracts, improving code readability while maintaining compatibility with external systems. It also ensures your API documentation is consistent and easily understood by developers.