---

"_If you're looking to learn one **modern framework** for building REST APIs, check out **FastAPI** [...] It's fast, easy to use and easy to learn [...]_"

"_We've switched over to **FastAPI** for our **APIs** [...] I think you'll like it [...]_"

But it is way more complex than that.

!!! tip
    If you are in a hurry or don't care, continue with the next sections for step by step instructions to set everything up with different techniques.

To **learn the basics of HTTPS**, from a consumer perspective, check <a href="https://howhttps.works/" class="external-link" target="_blank">https://howhttps.works/</a>.

    ```Python
    from .routers import items, users
    ```

    The second version is an "absolute import":

    ```Python
    from app.routers import items, users
    ```

    To learn more about Python Packages and Modules, read <a href="https://docs.python.org/3/tutorial/modules.html" class="external-link" target="_blank">the official Python documentation about Modules</a>.

### Avoid name collisions

    {!> ../../../docs_src/python_types/tutorial011_py39.py!}
    ```

=== "Python 3.8+"

    ```Python
    {!> ../../../docs_src/python_types/tutorial011.py!}
    ```

!!! info
    To learn more about <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic, check its docs</a>.

**FastAPI** is all based on Pydantic.

@asynccontextmanager
async def lifespan(app: FastAPI):
    # Load the ML model
    ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):
    result = ml_models["answer_to_everything"](x)

Sebastián Ramírez <******@****.***> 1544407273 +0400

ml_models = {}


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Load the ML model
    ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):
    result = ml_models["answer_to_everything"](x)

## Future

By this point, it's already clear that **FastAPI** with its ideas is being useful for many people.

It is being chosen over previous alternatives for suiting many use cases better.

All the framework was designed to be easy and intuitive to use, all the decisions were tested on multiple editors even before starting development, to ensure the best development experience.

In the Python developer surveys, it's clear <a href="https://www.jetbrains.com/research/python-developers-survey-2017/#tools-and-features" class="external-link" target="_blank">that one of the most used features is "autocompletion"</a>.

FastAPI will now:

* **Validate** the data making sure that the max length is 50 characters
* Show a **clear error** for the client when the data is not valid
* **Document** the parameter in the OpenAPI schema *path operation* (so it will show up in the **automatic docs UI**)

## Alternative (old) `Query` as the default value