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.
Let's imagine that you have a database fake_db that only receives JSON compatible data.
For example, it doesn't receive datetime objects, as those are not compatible with JSON.
So, a datetime object would have to be converted to a str containing the data in ISO format.
The same way, this database wouldn't receive a Pydantic model (an object with attributes), only a dict.
You can use jsonable_encoder for that.
It receives an object, like a Pydantic model, and returns a JSON compatible version:
=== "Python 3.10+"
```Python hl_lines="4 21"
{!> ../../../docs_src/encoder/tutorial001_py310.py!}
```
=== "Python 3.8+"
```Python hl_lines="5 22"
{!> ../../../docs_src/encoder/tutorial001.py!}
```
In this example, it would convert the Pydantic model to a dict, and the datetime to a str.
The result of calling it is something that can be encoded with the Python standard json.dumps().
It doesn't return a large str containing the data in JSON format (as a string). It returns a Python standard data structure (e.g. a dict) with values and sub-values that are all compatible with JSON.
!!! note
jsonable_encoder is actually used by FastAPI internally to convert data. But it is useful in many other scenarios.