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{!> ../../docs_src/generate_clients/tutorial003.py!}
```

////

### Generate a TypeScript Client with Custom Operation IDs

Now if you generate the client again, you will see that it has the improved method names:

<img src="/img/tutorial/generate-clients/image07.png">

As you see, the method names now have the tag and then the function name, now they don't include information from the URL path and the HTTP operation.

 *   <li>Dependency on {@code com.google.common} / Guava.
 * </ul>
 *
 * <p>Advantages compared to {@link com.google.common.collect.ImmutableList ImmutableList}{@code
 * <Long>}:
 *
 * <ul>
 *   <li>Improved memory compactness and locality.
 *   <li>Can be queried without allocating garbage.
 *   <li>Access to {@code LongStream} features (like {@link LongStream#sum}) using {@code stream()}

 *   <li>Dependency on {@code com.google.common} / Guava.
 * </ul>
 *
 * <p>Advantages compared to {@link com.google.common.collect.ImmutableList ImmutableList}{@code
 * <Integer>}:
 *
 * <ul>
 *   <li>Improved memory compactness and locality.
 *   <li>Can be queried without allocating garbage.
 *   <li>Access to {@code IntStream} features (like {@link IntStream#sum}) using {@code stream()}

 *   <li>Dependency on {@code com.google.common} / Guava.
 * </ul>
 *
 * <p>Advantages compared to {@link com.google.common.collect.ImmutableList ImmutableList}{@code
 * <Integer>}:
 *
 * <ul>
 *   <li>Improved memory compactness and locality.
 *   <li>Can be queried without allocating garbage.
 *   <li>Access to {@code IntStream} features (like {@link IntStream#sum}) using {@code stream()}

        features by binning their values
*   Improved **image preprocessing** layers: `CenterCrop`, `Rescaling`
*   Improved **image augmentation** layers: `RandomCrop`, `RandomFlip`,
    `RandomTranslation`, `RandomRotation`, `RandomHeight`, `RandomWidth`,
    `RandomZoom`, `RandomContrast`
*   Improved **`TextVectorization`** layer, which handles string tokenization,

#### Newer versions of Python

The syntax using `typing` is **compatible** with all versions, from Python 3.6 to the latest ones, including Python 3.9, Python 3.10, etc.

As Python advances, **newer versions** come with improved support for these type annotations and in many cases you won't even need to import and use the `typing` module to declare the type annotations.

 *   <li>Dependency on {@code com.google.common} / Guava.
 * </ul>
 *
 * <p>Advantages compared to {@link com.google.common.collect.ImmutableList ImmutableList}{@code
 * <Double>}:
 *
 * <ul>
 *   <li>Improved memory compactness and locality.
 *   <li>Can be queried without allocating garbage.
 *   <li>Access to {@code DoubleStream} features (like {@link DoubleStream#sum}) using {@code

 *       significantly worse than a {@code PriorityQueue} with manual eviction above the maximum
 *       size. In many cases {@link Ordering#leastOf} may work for your use case with significantly
 *       improved (and asymptotically superior) performance.
 *   <li>The retrieval operations {@link #peek}, {@link #peekFirst}, {@link #peekLast}, {@link
 *       #element}, and {@link #size} are constant-time.

 *       significantly worse than a {@code PriorityQueue} with manual eviction above the maximum
 *       size. In many cases {@link Ordering#leastOf} may work for your use case with significantly
 *       improved (and asymptotically superior) performance.
 *   <li>The retrieval operations {@link #peek}, {@link #peekFirst}, {@link #peekLast}, {@link
 *       #element}, and {@link #size} are constant-time.