# 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 {

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

* Upload edilen dosyadan metadata alabilirsiniz.
* [file-like](https://docs.python.org/3/glossary.html#term-file-like-object) bir `async` arayüze sahiptir.
* [`SpooledTemporaryFile`](https://docs.python.org/3/library/tempfile.html#tempfile.SpooledTemporaryFile) nesnesini dışa açar; bunu, file-like nesne bekleyen diğer library’lere doğrudan geçebilirsiniz.

### `UploadFile` { #uploadfile }

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

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.

 *
 * The first element on each line is a single hex code point (like 0041) or a hex code point range
 * (like 0030..0039).
 *
 * The second element on each line is a mapping type, like `valid` or `mapped`.
 *
 * For lines that contain a mapping target, the next thing is a sequence of hex code points (like
 * 0031 2044 0034).
 *
 * All other data is ignored.
 */

<img src="/img/tutorial/security/image04.png">

After authenticating in the system, you will see it like:

<img src="/img/tutorial/security/image05.png">

### Get your own user data { #get-your-own-user-data }

Now use the operation `GET` with the path `/users/me`.

You will get your user's data, like:

```JSON
{
  "username": "johndoe",
  "email": "******@****.***",
  "full_name": "John Doe",

    * 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. 😎