<li>The scope of a type identifier declared inside a function
	    begins at the identifier in the TypeSpec
	    and ends at the end of the innermost containing block.</li>
</ol>

<p>
An identifier declared in a block may be redeclared in an inner block.
While the identifier of the inner declaration is in scope, it denotes
the entity declared by the inner declaration.
</p>

<p>

The function parameters will be recognized as follows:

* If the parameter is also declared in the **path**, it will be used as a path parameter.
* If the parameter is of a **singular type** (like `int`, `float`, `str`, `bool`, etc) it will be interpreted as a **query** parameter.
* If the parameter is declared to be of the type of a **Pydantic model**, it will be interpreted as a request **body**.

/// note

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[13] *}

Let's focus on the parameters declared:

* Even though this function is a dependency ("dependable") itself, it also declares another dependency (it "depends" on something else).

{* ../../docs_src/response_model/tutorial003_py310.py hl[24] *}

...we declared the `response_model` to be our model `UserOut`, that doesn't include the password:

{* ../../docs_src/response_model/tutorial003_py310.py hl[22] *}

So, **FastAPI** will take care of filtering out all the data that is not declared in the output model (using Pydantic).

### `response_model` or Return Type { #response-model-or-return-type }

You can declare the type of a path parameter in the function, using standard Python type annotations:

{* ../../docs_src/path_params/tutorial002_py39.py hl[7] *}

In this case, `item_id` is declared to be an `int`.

/// check

This will give you editor support inside of your function, with error checks, completion, etc.

///

            if (isMultiModule) {
                // Multi-module project: artifactId may match any declared module name
                message = String.format(
                        "Cannot attach artifact to project: groupId and version must match the project, "
                                + "and artifactId must match either the project or a declared module name.%n"
                                + "  Project coordinates:  %s:%s:%s%n"

      entries.forEach(action);
    }

    @Override
    ImmutableList<Entry<K, V>> createAsList() {
      return new RegularImmutableAsList<>(this, entries);
    }

    // redeclare to help optimizers with b/310253115
    @SuppressWarnings("RedundantOverride")
    @Override
    @J2ktIncompatible
    @GwtIncompatible
        Object writeReplace() {
      return super.writeReplace();
    }
  }

We can do better...

## What makes a dependency { #what-makes-a-dependency }

Up to now you have seen dependencies declared as functions.

But that's not the only way to declare dependencies (although it would probably be the more common).

The key factor is that a dependency should be a "callable".

{* ../../docs_src/response_change_status_code/tutorial001_py39.py hl[1,9,12] *}

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.

* `Field(index=True)` tells SQLModel that it should create a **SQL index** for this column, that would allow faster lookups in the database when reading data filtered by this column.

    SQLModel will know that something declared as `str` will be a SQL column of type `TEXT` (or `VARCHAR`, depending on the database).

### Create an Engine { #create-an-engine }