Operand  *Operand `parser:"  @@"`
}

// Like represents the RHS of a LIKE expression
type Like struct {
	Not        bool     `parser:" @\"NOT\"? "`
	Pattern    *Operand `parser:" \"LIKE\" @@ "`
	EscapeChar *Operand `parser:" (\"ESCAPE\" @@)? "`
}

// Between represents the RHS of a BETWEEN expression
type Between struct {

	cases := []string{
		`select * from s3object where Name like 'abcd'`,
		`select Name like 'abc' from s3object`,
		`select * from s3object where Name not like 'abc'`,
		`select * from s3object where Name like 'abc' escape 't'`,
		`select * from s3object where Name like 'a\%' escape '?'`,
		`select * from s3object where Name not like 'abc\' escape '?'`,
		`select * from s3object where Name like 'a\%' escape LOWER('?')`,

It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.

# JSON Compatible Encoder { #json-compatible-encoder }

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder` { #using-the-jsonable-encoder }

	}

	if name != "groupby" || total != 60 {
		t.Errorf("name should be groupby, but got %v, total should be 60, but got %v", name, total)
	}

	if err := DB.Model(&User{}).Select("name, sum(age) as total").Where("name LIKE ?", "groupby%").Group("name").Having("name = ?", "groupby1").Row().Scan(&name, &total); err != nil {
		t.Errorf("no error should happen, but got %v", err)
	}

	if name != "groupby1" || total != 660 {

going to shrink any further:  she felt a little nervous about
this; `for it might end, you know,' said Alice to herself, `in my
going out altogether, like a candle.  I wonder what I should be
like then?'  And she tried to fancy what the flame of a candle is
like after the candle is blown out, for she could not remember
ever having seen such a thing.

  After a while, finding that nothing more happened, she decided

In many cases your application could need some external settings or configurations, for example secret keys, database credentials, credentials for email services, etc.

Most of these settings are variable (can change), like database URLs. And many could be sensitive, like secrets.

For this reason it's common to provide them in environment variables that are read by the application.

/// tip

///

## Multiple body parameters { #multiple-body-parameters }

In the previous example, the *path operations* would expect a JSON body with the attributes of an `Item`, like:

```JSON
{
    "name": "Foo",
    "description": "The pretender",
    "price": 42.0,
    "tax": 3.2
}
```

But you can also declare multiple body parameters, e.g. `item` and `user`:

    * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself....

///

### `yield from` { #yield-from }

When you are iterating over something, like a file-like object, and then you are doing `yield` for each item, you could also use `yield from` to yield each item directly and skip the `for` loop.

This is not particular to FastAPI, it's just Python, but it's a nice trick to know. 😎