After this, the client and the server have an **encrypted TCP connection**, this is what TLS provides. And then they can use that connection to start the actual **HTTP communication**.

And that's what **HTTPS** is, it's just plain **HTTP** inside a **secure TLS connection** instead of a pure (unencrypted) TCP connection.

/// tip

Notice that the encryption of the communication happens at the **TCP level**, not at the HTTP level.

///

		}
		if !obj.DeleteMarker && !rule.Filter.BySize(obj.Size) {
			continue
		}
		rules = append(rules, rule)
	}
	return rules
}

// ObjectOpts provides information to deduce the lifecycle actions
// which can be triggered on the resultant object.
type ObjectOpts struct {
	Name             string
	UserTags         string
	ModTime          time.Time
	Size             int64
	VersionID        string

// an object is encrypted using SSE-C or SSE-KMS. Maybe AWS S3
// computes the ETag as MD5 of the encrypted content but there is
// no way to verify this assumption since the encryption happens
// inside AWS S3.
// Therefore, S3 clients must not make any assumption about ETags
// in case of SSE-C or SSE-KMS except that the ETag is well-formed.
//
// To put all of this into a simple rule:
//
//	SSE-S3 : ETag == MD5

- For pod resizes requested on nodes where the resize request exceeds the node's allocatable capacity or the node is running an OS that does not support resize, the request will now fail in admission rather than be marked as Infeasible in the pod status later. ([#136043](https://github.com/kubernetes/kubernetes/pull/136043), [@natasha41575](https://gi...

Many of the tutorials have blocks of code.

In most of the cases, these blocks of code are actual complete applications that can be run as is.

In fact, those blocks of code are not written inside the Markdown, they are Python files in the `./docs_src/` directory.

And those Python files are included/injected in the documentation when generating the site.

### Docs for tests

These types that can take type parameters are called **Generic types** or **Generics**.

You can use the same builtin types as generics (with square brackets and types inside):

* `list`
* `tuple`
* `set`
* `dict`

#### List { #list }

For example, let's define a variable to be a `list` of `str`.

Declare the variable, with the same colon (`:`) syntax.

                    } finally {
                        updateCheckManager.touch(metadata, repository, file);
                    }
                }

                // TODO should this be inside the above check?
                // touch file so that this is not checked again until interval has passed
                if (file.exists()) {
                    file.setLastModified(System.currentTimeMillis());

		if err != nil {
			return nil, ObjectInfo{}, err
		}
		if size > len(b) {
			size = len(b)
		}

		// Calculate the object real size if encrypted
		if _, ok := crypto.IsEncrypted(gr.ObjInfo.UserDefined); ok {
			objSize, err = gr.ObjInfo.DecryptedSize()
			if err != nil {
				return nil, ObjectInfo{}, err
			}
		} else {
			objSize = gr.ObjInfo.Size
		}

    vbox.customize ["modifyvm", :id, "--audio", "none"]
  end

  # Switch the default share for the project root from /vagrant to
  # /elasticsearch because /vagrant is confusing when there is a project inside
  # the elasticsearch project called vagrant....
  config.vm.synced_folder '.', '/vagrant', disabled: true
  config.vm.synced_folder '.', '/elasticsearch'
  # TODO: make these syncs work for windows!!!

The `model_config` attribute is used just for Pydantic configuration. You can read more at [Pydantic: Concepts: Configuration](https://docs.pydantic.dev/latest/concepts/config/).

///

Here we define the config `env_file` inside of your Pydantic `Settings` class, and set the value to the filename with the dotenv file we want to use.

### Creating the `Settings` only once with `lru_cache` { #creating-the-settings-only-once-with-lru-cache }