///

## Create a Project { #create-a-project }

First, create a directory for your project.

What I normally do is that I create a directory named `code` inside my home/user directory.

And inside of that I create one directory per project.

<div class="termy">

```console
// Go to the home directory
$ cd

and can be asserted as desired.

You can change/extend these stubs, and tests should not be breaking too much, since most tests
assert using expected values from the stubs. Normally, when you try to use data from the stubs that
have not been properly populated, you'll get a nullpointer in your test and you then have to
identify which stub creates that specific piece of data.

The most important stubs are:

For example:

* **Audio** or **image processing**.
* **Computer vision**: an image is composed of millions of pixels, each pixel has 3 values / colors, processing that normally requires computing something on those pixels, all at the same time.
* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.

## What Does Deployment Mean { #what-does-deployment-mean }

To **deploy** an application means to perform the necessary steps to make it **available to the users**.

For a **web API**, it normally involves putting it in a **remote machine**, with a **server program** that provides good performance, stability, etc, so that your **users** can **access** the application efficiently and without interruptions or problems.

You can use the same dependency *functions* you use normally.

### Dependency requirements { #dependency-requirements }

They can declare request requirements (like headers) or other sub-dependencies:

{* ../../docs_src/dependencies/tutorial006_an_py39.py hl[8,13] *}

### Raise exceptions { #raise-exceptions }

These dependencies can `raise` exceptions, the same as normal dependencies:

# Return a Response Directly { #return-a-response-directly }

When you create a **FastAPI** *path operation* you can normally return any data from it: a `dict`, a `list`, a Pydantic model, a database model, etc.

By default, **FastAPI** would automatically convert that return value to JSON using the `jsonable_encoder` explained in [JSON Compatible Encoder](../tutorial/encoder.md){.internal-link target=_blank}.

# from the current origin/master.
# copy and edit the 'go run' command by hand to use a different branch.
v%.zip:
	git fetch origin master
	go run ../../src/cmd/go/internal/fips140/mkzip.go v$*

# normally mkzip refuses to overwrite an existing zip file.
# make v1.2.3.rm removes the zip file and unpacked
# copy from the module cache.
v%.rm:
	rm -f v$*.zip

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

{* ../../docs_src/response_headers/tutorial002_py39.py hl[1, 7:8] *}

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.

When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs.

## Install the Server Program { #install-the-server-program }

When you install FastAPI, it comes with a production server, Uvicorn, and you can start it with the `fastapi run` command.

Also, HTTP headers are case-insensitive, so, you can declare them with standard Python style (also known as "snake_case").

So, you can use `user_agent` as you normally would in Python code, instead of needing to capitalize the first letters as `User_Agent` or something similar.