## Common Use Cases

### E-commerce Search

```java
// Product search suggestions
SuggestItem product = new SuggestItem(
    new String[]{"iPhone 15 Pro", "Apple iPhone 15 Pro"},
    new String[][]{{"iphone"}, {"apple", "phone"}},
    1.5f,                               // boost popular products
    new String[]{"electronics", "mobile"},
    new String[]{"customer"},
    SuggestItem.Kind.DOCUMENT
);

                   prod code. It's disabled automatically for "test code"
                   (which is good: our tests have intentional violations), but
                   Error Prone doesn't know it's building test code unless we
                   pass -XepCompilingTestOnlyCode, and that argument needs to
                   be passed as part of the same <arg> as -Xplugin:ErrorProne,

                   prod code. It's disabled automatically for "test code"
                   (which is good: our tests have intentional violations), but
                   Error Prone doesn't know it's building test code unless we
                   pass -XepCompilingTestOnlyCode, and that argument needs to
                   be passed as part of the same <arg> as -Xplugin:ErrorProne,

                this.fileLocator.updateType(response.getFileType());
                info = response;
                fileSize = response.getDataSize();

                // this is so damn unreliable, needs another race-prone query if required
                haveAttributes = false;

                // This seems to be the only way to obtain a reliable (with respect to locking) file size here

kubectl output format, `kyaml`. KYAML was a strict subset of YAML and should be accepted by any YAML processor. The formatting of KYAML was halfway between JSON and YAML.  Because it was more explicit than the default YAML style, it was less error-prone. ([#132942](https://github.com/kubernetes/kubernetes/pull/132942), [@thockin](https://github.com/thockin)) [SIG API Machinery, Architecture, Auth, CLI, Cloud Provider, Cluster Lifecycle, Contributor Experience, Instrumentation, Network, Node, Scheduling,...

        layers and happens to work before TF 2.4. These will explicitly be
        unsupported now. Converting these ops to Functional API op layers was
        unreliable before TF 2.4, and prone to erroring incomprehensibly or
        being silently buggy.
    *   Code that directly asserts on a Keras symbolic value in cases where ops
        like `tf.rank` used to return a static or symbolic value depending on if