@app.get("/")
async def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
async def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

**Nota**:

Se você não sabe, verifique a seção _"In a hurry?"_ sobre <a href="https://fastapi.tiangolo.com/async/#in-a-hurry" target="_blank">`async` e `await` nas docs</a>.

</details>

### Rode

## Replication - Number of Processes

@app.get("/")
async def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
async def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

**Nota**:

Si no lo sabes, revisa la sección _"¿Con prisa?"_ sobre <a href="https://fastapi.tiangolo.com/es/async/#con-prisa" target="_blank">`async` y `await` en la documentación</a>.

</details>

### Córrelo

    *   Extending the TF 2.0 support for `shuffle(...,
        reshuffle_each_iteration=True)` and `cache()` to work across different
        Python iterators for the same dataset.
    *   Removing the `experimental_numa_aware` option from `tf.data.Options`.
    *   Add `num_parallel_reads` and passing in a Dataset containing filenames
        into `TextLineDataset` and `FixedLengthRecordDataset`.