///

## Types and validation { #types-and-validation }

These environment variables can only handle text strings, as they are external to Python and have to be compatible with other programs and the rest of the system (and even with different operating systems, as Linux, Windows, macOS).

We support development in IntelliJ versions IntelliJ 2020.1 and
onwards and Eclipse 2020-3 and onwards.

[Docker](https://docs.docker.com/install/) is required for building some Elasticsearch artifacts and executing certain test suites. You can run Elasticsearch without building all the artifacts with:

    ./gradlew :run

That'll spend a while building Elasticsearch and then it'll start Elasticsearch,

And it will also have both responses in the documentation, one for `404` and one for `403`.

///

## The main `FastAPI` { #the-main-fastapi }

Now, let's see the module at `app/main.py`.

Here's where you import and use the class `FastAPI`.

This will be the main file in your application that ties everything together.

	}
	return +1
}

// DivModInt sets q = x / y and r = x % y.
func DivModInt(q, r, x, y *Int) {
	q.doinit()
	r.doinit()
	x.doinit()
	y.doinit()
	C.mpz_tdiv_qr(&q.i[0], &r.i[0], &x.i[0], &y.i[0])
}

// GcdInt sets d to the greatest common divisor of a and b,
// which must be positive numbers.
// If x and y are not nil, GcdInt sets x and y such that d = a*x + b*y.

When using Veeam Backup and Replication, you can use S3 compatible object storage such as MinIO as a capacity tier for backups.  This disaggregates storage for the Veeam infrastructure and allows you to retain control of your data. With the ease of use of setup and administration of MinIO, it allows a Veeam backup admin to easily deploy their own object store for capacity tiering.

## Prerequisites

    * In requests and responses will be represented as a `str`.
* `datetime.datetime`:
    * A Python `datetime.datetime`.
    * In requests and responses will be represented as a `str` in ISO 8601 format, like: `2008-09-15T15:53:00+05:00`.
* `datetime.date`:
    * Python `datetime.date`.

And then you can set cookies in that *temporal* response object.

{* ../../docs_src/response_cookies/tutorial002_py310.py hl[1, 8:9] *}

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

    }

    /**
     * Creates and returns a new instance of {@link ArrayDeque}.
     *
     * @param <E> the element type of {@link ArrayDeque}
     * @return a new instance of {@link ArrayDeque}
     * @see ArrayDeque#ArrayDeque()
     */
    public static <E> ArrayDeque<E> newArrayDeque() {
        return new ArrayDeque<>();
    }

    /**
     * Creates and returns a new instance of {@link ArrayDeque}.

///

## Dependencies with `yield` and `HTTPException` { #dependencies-with-yield-and-httpexception }

You saw that you can use dependencies with `yield` and have `try` blocks that try to execute some code and then run some exit code after `finally`.

You can also use `except` to catch the exception that was raised and do something with it.

For example, you can raise a different exception, like `HTTPException`.

$ uv sync --extra all

---> 100%
```

</div>

It will install all the dependencies and your local FastAPI in your local environment.

### Using your local FastAPI

If you create a Python file that imports and uses FastAPI, and run it with the Python from your local environment, it will use your cloned local FastAPI source code.