* The **file** that can be **executed** by the operating system, for example: `python`, `python.exe` or `uvicorn`.
* A particular program while it is **running** on the operating system, using the CPU, and storing things on memory. This is also called a **process**.

### What is a Process

The word **process** is normally used in a more specific way, only referring to the thing that is running in the operating system (like in the last point above):

"docs_src/dependencies/tutorial010.py" = ["F821"]
"docs_src/custom_response/tutorial007.py" = ["B007"]
"docs_src/dataclasses/tutorial003.py" = ["I001"]
"docs_src/path_operation_advanced_configuration/tutorial007.py" = ["B904"]
"docs_src/path_operation_advanced_configuration/tutorial007_pv1.py" = ["B904"]
"docs_src/custom_request_and_route/tutorial002.py" = ["B904"]
"docs_src/dependencies/tutorial008_an.py" = ["F821"]

An <a href="https://en.wikipedia.org/wiki/Environment_variable" class="external-link" target="_blank">environment variable</a> (also known as "env var") is a variable that lives outside of the Python code, in the operating system, and could be read by your Python code (or by other programs as well).

You can create and use environment variables in the shell, without needing Python:

=== "Linux, macOS, Windows Bash"

    <div class="termy">

Your code needs to run on [all versions of Java that Gradle supports](platforms/documentation/docs/src/docs/userguide/releases/compatibility.adoc) and across all supported operating systems (macOS, Windows, Linux). The [Gradle CI system](http://builds.gradle.org/) will verify this, but here are some pointers that will avoid surprises:

#     elinux_armhf:    Embedded Linux options for armhf (ARMv7) CPU support.
#
# Release build options (for all operating systems)
#     release_base:                    Common options for all builds on all operating systems.
#     release_cpu_linux:               Toolchain and CUDA options for Linux CPU builds.
#     release_gpu_linux:               Toolchain and CUDA options for Linux GPU builds.

Linux containers run using the same Linux kernel of the host (machine, virtual machine, cloud server, etc). This just means that they are very lightweight (compared to full virtual machines emulating an entire operating system).

This way, containers consume **little resources**, an amount comparable to running the processes directly (a virtual machine would consume much more).

```Python hl_lines="3  25"
{!../../../docs_src/openapi_callbacks/tutorial001.py!}
```

### Create the callback *path operation*

To create the callback *path operation* use the same `APIRouter` you created above.

It should look just like a normal FastAPI *path operation*:

* It should probably have a declaration of the body it should receive, e.g. `body: InvoiceEvent`.

* All **automatically handled** by the framework.
* All the dependencies can require data from requests and **augment the path operation** constraints and automatic documentation.
* **Automatic validation** even for *path operation* parameters defined in dependencies.
* Support for complex user authentication systems, **database connections**, etc.

## Documenting webhooks with **FastAPI** and OpenAPI

With **FastAPI**, using OpenAPI, you can define the names of these webhooks, the types of HTTP operations that your app can send (e.g. `POST`, `PUT`, etc.) and the request **bodies** that your app would send.

```JSON
{"item_id": 5, "q": "somequery"}
```

You already created an API that:

* Receives HTTP requests in the _paths_ `/` and `/items/{item_id}`.
* Both _paths_ take `GET` operations (also known as HTTP _methods_).
* The _path_ `/items/{item_id}` has a _path parameter_ `item_id` that should be an `int`.
* The _path_ `/items/{item_id}` has an optional `str` _query parameter_ `q`.