Проектирование API: скрытие внутренностей и обратная совместимость
Проектируйте API так, чтобы изменения не ломали пользователей: скрывайте внутренности, используйте алиасы и KW_ONLY, не мутируйте входные данные.
Проектируйте API так, чтобы изменения не ломали пользователей: скрывайте внутренности, используйте алиасы и KW_ONLY, не мутируйте входные данные.
Правила из видео напрямую применимы при проектировании API для оркестрации моделей и автоматизации: используйте единый формат 'provider:model' и функцию infer_model() для унификации, скрывайте внутренние детали, обеспечивайте обратную совместимость через алиасы и KW_ONLY. Это упростит интеграцию новых провайдеров и снизит риск поломок у пользователей.
расшифровка ролика ↓
Title:
URL Source: https://raw.githubusercontent.com/pydantic/pydantic-ai/main/agent_docs/api-design.md
Markdown Content: # API Design & Interfaces
> Rules for designing public APIs, managing visibility, backward compatibility, and API patterns
**When to check**: When designing or modifying public APIs, parameters, or class interfaces
## Rules
<!-- rule:146 --> - Prefix implementation details with underscore (`_`) and exclude from `__all__` — prevents accidental API surface expansion and signals internal-only usage — Keeps the public API surface minimal and clearly separates internal implementation from stable public interfaces, preventing backward compatibility obligations for internal code. <!-- rule:29 --> - Export commonly-used types and classes from top-level `pydantic_ai` package — hides internal structure and simplifies user imports — Makes the public API easier to use and allows internal refactoring without breaking user code that would otherwise depend on specific submodule paths <!-- rule:124 --> - Use `_: KW_ONLY` marker before optional fields in dataclasses/Pydantic models — Prevents breakage when adding parameters — callers can't accidentally pass defaults positionally, ensuring backward compatibility when fields are added or reordered <!-- rule:56 --> - Prefer instance methods when accessing `self` attributes or enabling polymorphism; use module-level functions when no instance state is needed — Reduces unnecessary coupling and parameter passing while enabling proper polymorphism; extract shared logic to private top-level helpers to avoid duplication across classes <!-- rule:491 --> - Keep old names as deprecated aliases when renaming public API elements — prevents breaking existing code — Maintains backward compatibility so users can migrate gradually rather than experiencing immediate breakage when upgrading <!-- rule:775 --> - Return new collections from transform functions instead of mutating inputs — prevents surprising side effects and makes code easier to reason about (exceptions: performance-critical paths or functions named `update_*`/`*_inplace`) — Immutable transforms prevent surprising side effects and make code easier to reason about, improving maintainability across the codebase <!-- rule:367 --> - Don't access or modify private attributes (`_prefixed`) — use public APIs, properties, or constructor parameters — Prevents breakage when internal implementation changes and ensures compatibility with library updates <!-- rule:72 --> - Promote settings to base classes (`ModelSettings`, embedding settings) when 2-3+ providers support them; maintain backward compatibility with automatic mapping from new common fields to legacy provider-prefixed fields — Prevents API duplication across provider-specific subclasses (e.g., `OpenAIEmbeddingSettings`, `CohereEmbeddingSettings`) while preserving backward compatibility when refactoring provider-prefixed parameters (e.g., `cohere_`, `openai_`) to shared fields - Never change a shared default, public signature, or abstraction to accommodate one new feature — if a new type only behaves correctly once an existing public default is rewritten, the new type's design is wrong — Fix the new code instead, or split the shared change into its own PR with maintainer sign-off, so one caller's needs don't silently change behavior for every existing user <!-- rule:302 --> - Keep `NativeToolReturnPart.content` flat and non-redundant — avoid duplicating part fields, repeating `return_value` data, single-key wrappers, or unnecessary lists — Reduces API surface area, prevents inconsistencies between duplicate fields, and simplifies consumption for both users and AI assistants <!-- rule:265 --> - Use `'provider:model'` format (e.g., `'openai:gpt-4'`, `'anthropic:claude-3'`) and `infer_model()` for instantiation — Ensures consistent model reference syntax across code, docs, and CLI; provides unified instantiation interface that prevents fragmentation