feature.
*   Full new features (e.g., a new op implementing a cutting-edge algorithm)
    typically will live in
    [tensorflow/addons](https://github.com/tensorflow/addons) to get some
    airtime before a decision is made regarding whether they are to be migrated
    to the core.
*   As every PR requires several CPU/GPU hours of CI testing, we discourage

  - [Changelog since v1.31.11](#changelog-since-v13111)
  - [Important Security Information](#important-security-information)
    - [CVE-2025-5187: Nodes can delete themselves by adding an OwnerReference](#cve-2025-5187-nodes-can-delete-themselves-by-adding-an-ownerreference)
  - [Changes by Kind](#changes-by-kind)
    - [Feature](#feature)
    - [Bug or Regression](#bug-or-regression)
  - [Dependencies](#dependencies)
    - [Added](#added)

- `kubeadm`: Introduced a new feature gate `UpgradeAddonsBeforeControlPlane` to
  fix a kube-proxy skew policy misalignment. Its default value is `false`. Upgrade
  of the CoreDNS and kube-proxy addons will now trigger after all the control plane
  instances have been upgraded, unless the fearure gate is set to true. This feature

*   `tf.contrib`:

    *   `tf.contrib` has been deprecated, and functionality has been either
        migrated to the core TensorFlow API, to an ecosystem project such as
        [tensorflow/addons](https://www.github.com/tensorflow/addons) or
        [tensorflow/io](https://www.github.com/tensorflow/io), or removed
        entirely.
    *   Remove `tf.contrib.timeseries` dependency on TF distributions.

- kubeadm: `kubeadm upgrade node` now supports `addon` and `post-upgrade` phases. Users can use `kubeadm upgrade node phase addon` to execute the addon upgrade, or use `kubeadm upgrade node --skip-phases addon` to skip the addon upgrade. If you were previously skipping an addon subphase on `kubeadm init` you should now skip the same addon when calling `kubeadm upgrade apply` and `kubeadm upgrade node`. Currently, the `post-upgrade` phase is...

    }

    public void test_addCondition() {
        // Test adding conditions
        generator = new TestThumbnailGenerator();

        // Test adding single condition
        generator.addCondition("field1", "value1");

        // Test adding multiple conditions for same field
        generator.addCondition("field1", "value2");

        // Test adding conditions for different fields

    }

    /**
     * Test adding a single rule
     */
    public void test_addRule_single() {
        TestRule rule = new TestRule("rule1", true);

        ruleManager.addRule(rule);

        assertTrue(ruleManager.hasRule(rule));
        assertEquals(1, ruleManager.getRuleCount());
    }

    /**
     * Test adding multiple rules
     */

		w.compressors = make(map[uint16]Compressor)
	}
	w.compressors[method] = comp
}

// AddFS adds the files from fs.FS to the archive.
// It walks the directory tree starting at the root of the filesystem
// adding each file to the zip using deflate while maintaining the directory structure.
func (w *Writer) AddFS(fsys fs.FS) error {
	return fs.WalkDir(fsys, ".", func(name string, d fs.DirEntry, err error) error {

     */
    public void test_init_withEmptySessionId() {
        urlFilter.init("");
        // Should handle empty session ID gracefully
        assertNotNull(urlFilter);
    }

    /**
     * Test adding a single include pattern
     */
    public void test_addInclude_singlePattern() {
        String sessionId = "test-session-002";
        urlFilter.init(sessionId);

        urlFilter.addInclude("https://example.com/.*");

    O SQLModel saberá que algo declarado como `str` será uma coluna SQL do tipo `TEXT` (ou `VARCHAR`, dependendo do banco de dados).

### Criar um Engine
Um `engine` SQLModel (por baixo dos panos, ele é na verdade um `engine` do SQLAlchemy) é o que **mantém as conexões** com o banco de dados.