In almost any framework handling the security becomes a rather complex subject quite quickly.

Many packages that simplify it a lot have to make many compromises with the data model, database, and available features. And some of these packages that simplify things too much actually have security flaws underneath.

---

**FastAPI** doesn't make any compromise with any database, data model or tool.

///

```Python hl_lines="1  4-6" title="app/dependencies.py"
{!> ../../docs_src/bigger_applications/app/dependencies.py!}
```

////

/// tip

We are using an invented header to simplify this example.

But in real cases you will get better results using the integrated [Security utilities](security/index.md){.internal-link target=_blank}.

///

We will create a FastAPI **dependency** with `yield` that will provide a new `Session` for each request. This is what ensures that we use a single session per request. 🤓

Then we create an `Annotated` dependency `SessionDep` to simplify the rest of the code that will use this dependency.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[25:30]  hl[25:27,30] *}

### Create Database Tables on Startup { #create-database-tables-on-startup }

// does various checks while doing so. `input_nodes` will contain the same
// information as input_tensors just in a different structure to make
// following processing easier. TODO(iga): Simplify this nested structure.
absl::Status ProcessInputs(
    const TF_Graph* fn_body, const char* fn_name, int ninputs,
    const TF_Output* inputs, std::vector<OutputTensor>* input_tensors,

        File lmhostsFile = tempDir.resolve("lmhosts_include").toFile();

        try (FileWriter writer = new FileWriter(lmhostsFile)) {
            // Write main content without include directive to simplify test
            writer.write("192.168.1.100 HOST1\n");
            writer.write("# Test comment\n");
            writer.write("192.168.1.101 HOST2\n");
        }

## Recap { #recap }

You can use Pydantic Settings to handle the settings or configurations for your application, with all the power of Pydantic models.

* By using a dependency you can simplify testing.
* You can use `.env` files with it.

func (c *LRU[K, V]) Cap() int {
	return c.size
}

// Entry is an LRU Entry
type Entry[K comparable, V any] struct {
	// Next and previous pointers in the doubly-linked list of elements.
	// To simplify the implementation, internally a list l is implemented
	// as a ring, such that &l.root is both the next element of the last
	// list element (l.Back()) and the previous element of the first list
	// element (l.Front()).

		sr := s[i]
		tr := t[i]
		if sr|tr >= utf8.RuneSelf {
			goto hasUnicode
		}

		// Easy case.
		if tr == sr {
			continue
		}

		// Make sr < tr to simplify what follows.
		if tr < sr {
			tr, sr = sr, tr
		}
		// ASCII only, sr/tr must be upper/lower case
		if 'A' <= sr && sr <= 'Z' && tr == sr+'a'-'A' {
			continue
		}
		return false
	}

## Deployment Concepts { #deployment-concepts }

Let's talk again about some of the same [Deployment Concepts](concepts.md){.internal-link target=_blank} in terms of containers.

Containers are mainly a tool to simplify the process of **building and deploying** an application, but they don't enforce a particular approach to handle these **deployment concepts**, and there are several possible strategies.