INSTANCE;

      /*
       * Static final fields are presumed to be fastest, based on our experience with
       * UnsignedBytesBenchmark. TODO(cpovirk): benchmark this
       */
      /*
       * A CopyOnWriteArraySet<WeakReference> is faster than a newSetFromMap of a MapMaker map with
       * weakKeys() and concurrencyLevel(1), even up to at least 12 cached exception types.

    * If you are comparing Starlette, compare it against Sanic, Flask, Django, etc. Web frameworks (or microframeworks).
* **FastAPI**:
    * The same way that Starlette uses Uvicorn and cannot be faster than it, **FastAPI** uses Starlette, so it cannot be faster than it.

### Hey API { #hey-api }

Once we have a FastAPI app with the models, we can use Hey API to generate a TypeScript client. The fastest way to do that is via npx.

```sh
npx @hey-api/openapi-ts -i http://localhost:8000/openapi.json -o src/client
```

This will generate a TypeScript SDK in `./src/client`.

      INSTANCE;

      /*
       * Static final fields are presumed to be fastest, based on our experience with
       * UnsignedBytesBenchmark. TODO(cpovirk): benchmark this
       */
      /*
       * A CopyOnWriteArraySet<WeakReference> is faster than a newSetFromMap of a MapMaker map with
       * weakKeys() and concurrencyLevel(1), even up to at least 12 cached exception types.

//       purge:
//           # retainVersions: 0 # (default) delete all versions of the object. This option is the fastest.
//           # retainVersions: 5 # keep the latest 5 versions of the object.
//
//     - type: deleted # objects with delete marker as their latest version
//       name: NAME # match object names that satisfy the wildcard expression.

There are some additional dependencies you might want to install.

Additional optional Pydantic dependencies:

* <a href="https://docs.pydantic.dev/latest/usage/pydantic_settings/" target="_blank"><code>pydantic-settings</code></a> - for settings management.
* <a href="https://docs.pydantic.dev/latest/usage/types/extra_types/extra_types/" target="_blank"><code>pydantic-extra-types</code></a> - for extra types to be used with Pydantic.

* Seriously impressive performance. It is <a href="https://github.com/encode/starlette#performance" class="external-link" target="_blank">one of the fastest Python frameworks available, on par with **NodeJS** and **Go**</a>.
* **WebSocket** support.
* In-process background tasks.
* Startup and shutdown events.
* Test client built on HTTPX.

It was found that the directory staging committer was the fastest among the three, S3A connector should be configured with the following parameters for optimal results:

```
cat ${HADOOP_CONF_DIR}/core-site.xml | kv-pairify | grep "s3a"

fs.s3a.access.key=minio

It clearly inspired Uvicorn and Starlette, that are currently faster than Sanic in open benchmarks.

///

/// check | Inspired **FastAPI** to

Find a way to have a crazy performance.

That's why **FastAPI** is based on Starlette, as it is the fastest framework available (tested by third-party benchmarks).

///

There are some additional dependencies you might want to install.

Additional optional Pydantic dependencies:

* <a href="https://docs.pydantic.dev/latest/usage/pydantic_settings/" target="_blank"><code>pydantic-settings</code></a> - for settings management.
* <a href="https://docs.pydantic.dev/latest/usage/types/extra_types/extra_types/" target="_blank"><code>pydantic-extra-types</code></a> - for extra types to be used with Pydantic.