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  1. docs/pt/docs/index.md

    ---
    
    FastAPI é um moderno e rápido (alta performance) _framework web_ para construção de APIs com Python 3.8 ou superior, baseado nos _type hints_ padrões do Python.
    
    Os recursos chave são:
    
    * **Rápido**: alta performance, equivalente a **NodeJS** e **Go** (graças ao Starlette e Pydantic). [Um dos frameworks mais rápidos disponíveis](#performance).
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  2. docs/en/docs/tutorial/body.md

    And will be also used in the API docs inside each *path operation* that needs them:
    
    <img src="/img/tutorial/body/image02.png">
    
    ## Editor support
    
    In your editor, inside your function you will get type hints and completion everywhere (this wouldn't happen if you received a `dict` instead of a Pydantic model):
    
    <img src="/img/tutorial/body/image03.png">
    
    You also get error checks for incorrect type operations:
    
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  3. docs/az/docs/index.md

    **Qaynaq Kodu**: <a href="https://github.com/tiangolo/fastapi" target="_blank">https://github.com/tiangolo/fastapi</a>
    
    ---
    
    FastAPI Python 3.8+ ilə API yaratmaq üçün standart Python <abbr title="Tip Məsləhətləri: Type Hints">tip məsləhətlərinə</abbr> əsaslanan, müasir, sürətli (yüksək performanslı) framework-dür.
    
    Əsas xüsusiyyətləri bunlardır:
    
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  4. docs/vi/docs/index.md

    ---
    
    FastAPI là một web framework hiện đại, hiệu năng cao để xây dựng web APIs với Python 3.8+ dựa trên tiêu chuẩn Python type hints.
    
    Những tính năng như:
    
    * **Nhanh**: Hiệu năng rất cao khi so sánh với **NodeJS** và **Go** (cảm ơn Starlette và Pydantic). [Một trong những Python framework nhanh nhất](#hieu-nang).
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  5. CHANGELOG/CHANGELOG-1.23.md

    - Topology Aware Hints now ignores unready endpoints when assigning hints. ([#106510](https://github.com/kubernetes/kubernetes/pull/106510), [@robscott](https://github.com/robscott))
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  6. okhttp/src/main/kotlin/okhttp3/internal/http1/Http1ExchangeCodec.kt

            statusLine.code == HTTP_CONTINUE -> {
              state = STATE_READ_RESPONSE_HEADERS
              responseBuilder
            }
            statusLine.code in (102 until 200) -> {
              // Processing and Early Hints will mean a second headers are coming.
              // Treat others the same for now
              state = STATE_READ_RESPONSE_HEADERS
              responseBuilder
            }
            else -> {
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  7. docs/en/docs/tutorial/query-params-str-validations.md

    ## Use `Annotated` in the type for the `q` parameter
    
    Remember I told you before that `Annotated` can be used to add metadata to your parameters in the [Python Types Intro](../python-types.md#type-hints-with-metadata-annotations){.internal-link target=_blank}?
    
    Now it's the time to use it with FastAPI. 🚀
    
    We had this type annotation:
    
    === "Python 3.10+"
    
        ```Python
        q: str | None = None
        ```
    
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  8. CHANGELOG/CHANGELOG-1.22.md

    - Remove support for the Service `topologyKeys` field (alpha) and the `kube-proxy` implementation of it. This field was deprecated several cycles ago. This functionality is replaced by the combination of automatic topology hints per-endpoint (alpha) and the Service `internalTrafficPolicy` field (alpha). ([#102412](https://github.com/kubernetes/kubernetes/pull/102412), [@andrewsykim](https://github.com/andrewsykim))
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  9. CHANGELOG/CHANGELOG-1.24.md

    - The `TopologyAwareHints` feature gate is now enabled by default. This will allow users to opt-in to Topology Aware Hints by setting the `service.kubernetes.io/topology-aware-hints` on a Service. This will not affect any Services without that annotation set. ([#108747](https://github.com/kubernetes/kubernetes/pull/108747), [@robscott](https://github.com/robscott))
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  10. RELEASE.md

        *   Fix device placement issues related to datasets with ragged tensors of
            strings (i.e. variant encoded data with types not supported on GPU).
        *   'experimental_follow_type_hints' for tf.function has been deprecated.
            Please use input_signature or reduce_retracing to minimize retracing.
    
    *   `tf.SparseTensor`:
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