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docs/en/docs/tutorial/sql-databases.md
A common pattern is to use an "ORM": an "object-relational mapping" library. An ORM has tools to convert ("*map*") between *objects* in code and database tables ("*relations*"). With an ORM, you normally create a class that represents a table in a SQL database, each attribute of the class represents a column, with a name and a type. For example a class `Pet` could represent a SQL table `pets`.
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docs/fr/docs/history-design-future.md
De plus, la meilleure approche était d'utiliser des normes déjà existantes. Ainsi, avant même de commencer à coder **FastAPI**, j'ai passé plusieurs mois à étudier les spécifications d'OpenAPI, JSON Schema, OAuth2, etc. Comprendre leurs relations, leurs similarités et leurs différences. ## Conception Ensuite, j'ai passé du temps à concevoir l'"API" de développeur que je voulais avoir en tant qu'utilisateur (en tant que développeur utilisant FastAPI).
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docs/en/docs/release-notes.md
## 0.30.0 * Add support for Pydantic's ORM mode: * Updated documentation about SQL with SQLAlchemy, using Pydantic models with ORM mode, SQLAlchemy models with relations, separation of files, simplification of code and other changes. New docs: [SQL (Relational) Databases](https://fastapi.tiangolo.com/tutorial/sql-databases/).
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