*       the same.
   *   <li>The unreserved characters ".", "-", "~", and "_" remain the same.
   *   <li>The general delimiters "@" and ":" remain the same.
   *   <li>The subdelimiters "!", "$", "&amp;", "'", "(", ")", "*", "+", ",", ";", and "=" remain
   *       the same.
   *   <li>The space character " " is converted into %20.

But you are not restricted to using some specific data model, class or type.

Do you want to have an `id` and `email` and not have any `username` in your model? Sure. You can use these same tools.

Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.

# Cookie Parameters { #cookie-parameters }

You can define Cookie parameters the same way you define `Query` and `Path` parameters.

## Import `Cookie` { #import-cookie }

First import `Cookie`:

{* ../../docs_src/cookie_params/tutorial001_an_py310.py hl[3] *}

## Declare `Cookie` parameters { #declare-cookie-parameters }

Then declare the cookie parameters using the same structure as with `Path` and `Query`.

query_extractor --> query_or_cookie_extractor --> read_query
```

## Using the same dependency multiple times { #using-the-same-dependency-multiple-times }

If one of your dependencies is declared multiple times for the same *path operation*, for example, multiple dependencies have a common sub-dependency, **FastAPI** will know to call that sub-dependency only once per request.

All of them share the same parameters for additional validation and metadata you have seen.

///

/// note | Technical Details

When you import `Query`, `Path` and others from `fastapi`, they are actually functions.

That when called, return instances of classes of the same name.

This will be especially useful when you use it in a **large code base** where you use **the same dependencies** over and over again in **many *path operations***.

## To `async` or not to `async` { #to-async-or-not-to-async }

As dependencies will also be called by **FastAPI** (the same as your *path operation functions*), the same rules apply while defining your functions.

### Testing file { #testing-file }

Then you could have a file `test_main.py` with your tests. It could live on the same Python package (the same directory with a `__init__.py` file):

``` hl_lines="5"
.
├── app
│   ├── __init__.py
│   ├── main.py
│   └── test_main.py
```

Because this file is in the same package, you can use relative imports to import the object `app` from the `main` module (`main.py`):

    assertThat(network).isNotEqualTo(g2);
  }

  // Node sets are the same, but edge sets differ.
  @Test
  public void equivalent_edgeSetsDiffer() {
    network.addEdge(N1, N2, E12);

    MutableNetwork<Integer, String> g2 = createNetwork(edgeType);
    g2.addEdge(N1, N2, E13);

    assertThat(network).isNotEqualTo(g2);
  }

  // Node/edge sets are the same, but node/edge connections differ due to edge type.
  @Test

    assertThat(network).isNotEqualTo(g2);
  }

  // Node sets are the same, but edge sets differ.
  @Test
  public void equivalent_edgeSetsDiffer() {
    network.addEdge(N1, N2, E12);

    MutableNetwork<Integer, String> g2 = createNetwork(edgeType);
    g2.addEdge(N1, N2, E13);

    assertThat(network).isNotEqualTo(g2);
  }

  // Node/edge sets are the same, but node/edge connections differ due to edge type.
  @Test

- **Each object is written to a single EC set, and therefore is spread over no more than 16 drives.**
- **All the nodes running distributed MinIO setup are recommended to be homogeneous, i.e. same operating system, same number of drives and same network interconnects.**