Este es solo un **tutorial rápido / recordatorio** sobre las anotaciones de tipos en Python. Cubre solo lo mínimo necesario para usarlas con **FastAPI**... que en realidad es muy poco.

**FastAPI** se basa completamente en estas anotaciones de tipos, dándole muchas ventajas y beneficios.

Pero incluso si nunca usas **FastAPI**, te beneficiaría aprender un poco sobre ellas.

/// note | Nota

///

Como SQLModel se basa en SQLAlchemy, puedes usar fácilmente **cualquier base de datos soportada** por SQLAlchemy (lo que las hace también soportadas por SQLModel), como:

* PostgreSQL
* MySQL
* SQLite
* Oracle
* Microsoft SQL Server, etc.

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        *   The new backend is used for 8 bits full integer post-training
            quantization
        *   The new backend removes the redundant rescales and fixes some bugs
            (shared weight/bias, extremely small scales, etc)
        *   Set `experimental_new_quantizer` in tf.lite.TFLiteConverter to False
            to disable this change
*   `tf.keras`
    *   `tf.keras.metrics.AUC` now support logit predictions.

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* Remove gender bias in docs for handling errors. PR [#780](https://github.com/tiangolo/fastapi/pull/780). Original idea in PR [#761](https://github.com/tiangolo/fastapi/pull/761) by [@classywhetten](https://github.com/classywhetten).

advances.
</p>

<pre>
RowLoop:
	for y, row := range rows {
		for x, data := range row {
			if data == endOfRow {
				continue RowLoop
			}
			row[x] = data + bias(x, y)
		}
	}
</pre>

<h3 id="Goto_statements">Goto statements</h3>

<p>
A "goto" statement transfers control to the statement with the corresponding label
within the same function.
</p>

pkg syscall (windows-386), type Timeval struct, Usec int32
pkg syscall (windows-386), type Timezoneinformation struct
pkg syscall (windows-386), type Timezoneinformation struct, Bias int32
pkg syscall (windows-386), type Timezoneinformation struct, DaylightBias int32
pkg syscall (windows-386), type Timezoneinformation struct, DaylightDate Systemtime