Import the `Response` class (sub-class) you want to use and declare it in the *path operation decorator*.

For large responses, returning a `Response` directly is much faster than returning a dictionary.

Still, in both situations, chances are that **FastAPI** will [still be faster](index.md#performance){.internal-link target=_blank} than (or at least comparable to) your previous framework.

### Dependencies

            argumentMapping[valueArgument] = parameterSymbol
        }
    }

    private fun FirExpression.findSourceKtExpressionForCallArgument(): KtExpression? {
        // For smart-casted expression, refer to the source of the original expression
        // For spread, named, and lambda arguments, the source is the KtValueArgument.

    [`tf.debugging`](https://www.tensorflow.org/versions/master/api_docs/python/tf/debugging),
    [`tf.dtypes`](https://www.tensorflow.org/versions/master/api_docs/python/tf/dtypes),
    [`tf.image`](https://www.tensorflow.org/versions/master/api_docs/python/tf/image),
    [`tf.io`](https://www.tensorflow.org/versions/master/api_docs/python/tf/io),
    [`tf.linalg`](https://www.tensorflow.org/versions/master/api_docs/python/tf/linalg),

* To fix a typo you found on the documentation.
* To share an article, video, or podcast you created or found about FastAPI by <a href="https://github.com/tiangolo/fastapi/edit/master/docs/en/data/external_links.yml" class="external-link" target="_blank">editing this file</a>.
    * Make sure you add your link to the start of the corresponding section.

    receiving stream to process it.

    This change may increase OkHttp's memory use for applications that make many concurrent HTTP
    calls and that can receive data faster than they can process it. Previously, OkHttp limited
    HTTP/2 to 16 MiB of unacknowledged data per connection. With this fix there is a limit of 16 MiB
    of unacknowledged data per stream and no per-connection limit.

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[![Build Status](https://github.com/google/guava/workflows/CI/badge.svg?branch=master)](https://github.com/google/guava/actions)
[![OpenSSF Best Practices](https://bestpractices.coreinfrastructure.org/projects/7197/badge)](https://bestpractices.coreinfrastructure.org/projects/7197)

 * provides symbol names from binary libraries in Standalone mode, which the Standalone declaration provider does not contain (to avoid
 * stub-indexing binary libraries). And in general, querying the symbol names provider might be faster since its sets are cached, which is
 * not necessarily the case for declaration providers (e.g. the IDE declaration provider hitting the index without caching).
 *

    * 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.

* **Uvicorn** managing **Uvicorn workers**
    * One Uvicorn **process manager** would listen on the **IP** and **port**, and it would start **multiple Uvicorn worker processes**.
* **Kubernetes** and other distributed **container systems**
    * Something in the **Kubernetes** layer would listen on the **IP** and **port**. The replication would be by having **multiple containers**, each with **one Uvicorn process** running.