chart configuration.
      See the [chartconfig](https://pkg.go.dev/golang.org/x/telemetry/internal/chartconfig)
      package for an explanation of the chart config format.
      For an example change, see [CL 564619](https://go.dev/cl/564619).
  validations:

/test/run.out
/test/times.out

# This file includes artifacts of Go build that should not be checked in.
# For files created by specific development environment (e.g. editor),
# use alternative ways to exclude files from git.

```Python hl_lines="20"
{!> ../../docs_src/dependencies/tutorial011.py!}
```

////

/// tip | "Dica"

Tudo isso parece não ser natural. E pode não estar muito claro ou aparentar ser útil ainda.

Estes exemplos são intencionalmente simples, porém mostram como tudo funciona.

Nos capítulos sobre segurança, existem funções utilitárias que são implementadas desta maneira.

policy grants access to buckets with name starting with example. ## In addition, grants objects read permissions on buckets starting with example. # - name: readonlyexamplepolic # statements: # - resources: # - 'arn:aws:s3:::example*/*' # actions: # - "s3:GetObject" # - resources: # - 'arn:aws:s3:::example*' # actions: # - "s3:GetBucketLocation" # - "s3:ListBucket" # - "s3:ListBucketMultipartU" ## conditionsexample policy creates all access to example bucket with aws:username="johndoe" and source ip range...

}

// ExampleWriter_ReadFrom demonstrates how to use the ReadFrom method of Writer.
func ExampleWriter_ReadFrom() {
	var buf bytes.Buffer
	writer := bufio.NewWriter(&buf)

	data := "Hello, world!\nThis is a ReadFrom example."
	reader := strings.NewReader(data)

	n, err := writer.ReadFrom(reader)
	if err != nil {
		fmt.Println("ReadFrom Error:", err)
		return
	}

	if err = writer.Flush(); err != nil {

policy grants access to buckets with name starting with example. ## In addition, grants objects read permissions on buckets starting with example. # - name: readonlyexamplepolic # statements: # - resources: # - 'arn:aws:s3:::example*/*' # actions: # - "s3:GetObject" # - resources: # - 'arn:aws:s3:::example*' # actions: # - "s3:GetBucketLocation" # - "s3:ListBucket" # - "s3:ListBucketMultipartU" ## conditionsexample policy creates all access to example bucket with aws:username="johndoe" and source ip range...

writeexamplepolicy policy grants creation or deletion of buckets with name ## starting with example. In addition, grants objects write permissions on buckets starting with ## example. # - name: writeexamplepolicy # statements: # - resources: # - 'arn:aws:s3:::example*/*' # actions: # - "s3:AbortMultipartUpload" # - "s3:GetObject" # - "s3:DeleteObject" # - "s3:PutObject" # - "s3:ListMultipartUploadP" # - resources: # - 'arn:aws:s3:::example*' # actions: # - "s3:CreateBucket" # - "s3:DeleteBucket" # - "s3:GetBucketLocation"...

writeexamplepolicy policy grants creation or deletion of buckets with name ## starting with example. In addition, grants objects write permissions on buckets starting with ## example. # - name: writeexamplepolicy # statements: # - resources: # - 'arn:aws:s3:::example*/*' # actions: # - "s3:AbortMultipartUpload" # - "s3:GetObject" # - "s3:DeleteObject" # - "s3:PutObject" # - "s3:ListMultipartUploadP" # - resources: # - 'arn:aws:s3:::example*' # actions: # - "s3:CreateBucket" # - "s3:DeleteBucket" # - "s3:GetBucketLocation"...

writeexamplepolicy policy grants creation or deletion of buckets with name ## starting with example. In addition, grants objects write permissions on buckets starting with ## example. # - name: writeexamplepolicy # statements: # - resources: # - 'arn:aws:s3:::example*/*' # actions: # - "s3:AbortMultipartUpload" # - "s3:GetObject" # - "s3:DeleteObject" # - "s3:PutObject" # - "s3:ListMultipartUploadP" # - resources: # - 'arn:aws:s3:::example*' # actions: # - "s3:CreateBucket" # - "s3:DeleteBucket" # - "s3:GetBucketLocation"...

Поэтому, если мы создадим Pydantic-объект `user_in` таким способом:

```Python
user_in = UserIn(username="john", password="secret", email="john.doe@example.com")
```

и затем вызовем:

```Python
user_dict = user_in.dict()
```

то теперь у нас есть `dict` с данными модели в переменной `user_dict` (это `dict` вместо объекта Pydantic-модели).