Columns: []clause.Column{{Name: "role"}},
				Having:  []clause.Expression{clause.Eq{"role", "admin"}},
			}},
			"SELECT * FROM `users` GROUP BY `role` HAVING `role` = ?",
			[]interface{}{"admin"},
		},
		{
			[]clause.Interface{clause.Select{}, clause.From{}, clause.GroupBy{
				Columns: []clause.Column{{Name: "role"}},
				Having:  []clause.Expression{clause.Eq{"role", "admin"}},
			}, clause.GroupBy{

		t.Errorf("name should be groupby, but got %v, total should be 60, but got %v", name, total)
	}

	if err := DB.Model(&User{}).Select("name, sum(age) as total").Where("name LIKE ?", "groupby%").Group("name").Having("name = ?", "groupby1").Row().Scan(&name, &total); err != nil {
		t.Errorf("no error should happen, but got %v", err)
	}

	if name != "groupby1" || total != 660 {

	})
	return
}

// Having specify HAVING conditions for GROUP BY
//
//	// Select the sum age of users with name jinzhu
//	db.Model(&User{}).Select("name, sum(age) as total").Group("name").Having("name = ?", "jinzhu").Find(&result)
func (db *DB) Having(query interface{}, args ...interface{}) (tx *DB) {
	tx = db.getInstance()
	tx.Statement.AddClause(clause.GroupBy{
		Having: tx.Statement.BuildCondition(query, args...),

It's the most popular Python framework and is widely trusted. It is used to build systems like Instagram.

It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.

For example:

* 200: `status.HTTP_200_OK`
* 403: `status.HTTP_403_FORBIDDEN`
* etc.

It can be convenient to quickly access HTTP (and WebSocket) status codes in your app, using autocompletion for the name without having to remember the integer status codes by memory.

Read more about it in the [FastAPI docs about Response Status Code](https://fastapi.tiangolo.com/tutorial/response-status-code/).

## Example

```python

    * If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers.
* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.

/// tip

Having the return model ensure that a value is always available and always `int` (not `None`) is very useful for the API clients, they can write much simpler code having this certainty.

But you can still document it as described in [Additional Responses in OpenAPI](additional-responses.md){.internal-link target=_blank}.

# Advanced Dependencies

## Parameterized dependencies

All the dependencies we have seen are a fixed function or class.

But there could be cases where you want to be able to set parameters on the dependency, without having to declare many different functions or classes.

Let's imagine that we want to have a dependency that checks if the query parameter `q` contains some fixed content.

But we want to be able to parameterize that fixed content.

      continue

    # In Python, MSYS, Linux-like paths are automatically read as Windows paths
    # with forward slashes, e.g. 'C:/Program Files', instead of
    # '/c/Program Files', thus becoming converted simply by virtue of having
    # been read.
    converted_vars[var] = value

  var_str = '\n'.join(f'{k}="{v}"'
                      for k, v in converted_vars.items())
  # The string can then be piped into `source`, to re-set the