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  1. okhttp/src/main/kotlin/okhttp3/internal/idn/IdnaMappingTable.kt

        return when {
          offset >= 0 -> offset * 4 // This section was found by binary search.
          else -> (-offset - 2) * 4 // Not found? Use the preceding element.
        }
      }
    
      /**
       * Binary search [ranges] for [codePoint], looking at its bottom 7 bits.
       *
       * This binary searches over 4-byte entries, and so it needs to adjust binary search indices
       * in (by dividing by 4) and out (by multiplying by 4).
       */
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  2. ReadMe.md

    [![GitHub license](https://img.shields.io/badge/license-Apache%20License%202.0-blue.svg?style=flat)](https://www.apache.org/licenses/LICENSE-2.0)
    [![Revved up by Develocity](https://img.shields.io/badge/Revved%20up%20by-Develocity-06A0CE?logo=Gradle&labelColor=02303A)](https://ge.jetbrains.com/scans?search.rootProjectNames=Kotlin)
    
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  3. docs/de/docs/project-generation.md

    ### Modelle für maschinelles Lernen mit spaCy und FastAPI – Funktionen
    
    * **spaCy** NER-Modellintegration.
    * **Azure Cognitive Search**-Anforderungsformat integriert.
    * **Produktionsbereit** Python-Webserver, verwendet Uvicorn und Gunicorn.
    * **Azure DevOps** Kubernetes (AKS) CI/CD-Deployment integriert.
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  4. docs/fr/docs/history-design-future.md

    ## Futur
    
    À ce stade, il est déjà clair que **FastAPI** et ses idées sont utiles pour de nombreuses personnes.
    
    Elle a été préférée aux solutions précédentes parce qu'elle convient mieux à de nombreux cas d'utilisation.
    
    De nombreux développeurs et équipes dépendent déjà de **FastAPI** pour leurs projets (y compris moi et mon équipe).
    
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  5. docs/en/docs/tutorial/testing.md

    ```Python
    {!> ../../../docs_src/app_testing/app_b/test_main.py!}
    ```
    
    Whenever you need the client to pass information in the request and you don't know how to, you can search (Google) how to do it in `httpx`, or even how to do it with `requests`, as HTTPX's design is based on Requests' design.
    
    Then you just do the same in your tests.
    
    E.g.:
    
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  6. docs/en/docs/alternatives.md

    It is used by many companies including Mozilla, Red Hat and Eventbrite.
    
    It was one of the first examples of **automatic API documentation**, and this was specifically one of the first ideas that inspired "the search for" **FastAPI**.
    
    !!! note
        Django REST Framework was created by Tom Christie. The same creator of Starlette and Uvicorn, on which **FastAPI** is based.
    
    
    !!! check "Inspired **FastAPI** to"
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  7. docs/en/docs/advanced/generate-clients.md

    There are also several other companies offering similar services that you can search and find online. 🤓
    
    ## Generate a TypeScript Frontend Client
    
    Let's start with a simple FastAPI application:
    
    === "Python 3.9+"
    
        ```Python hl_lines="7-9  12-13  16-17  21"
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  8. okhttp/src/main/kotlin/okhttp3/internal/connection/RealConnectionPool.kt

       * given to [connectionUser] who may (for example) assign it to a [RealCall.connection].
       *
       * This confirms the returned connection is healthy before returning it. If this encounters any
       * unhealthy connections in its search, this will clean them up.
       *
       * If [routes] is non-null these are the resolved routes (ie. IP addresses) for the connection.
       * This is used to coalesce related domains to the same HTTP/2 connection, such as `square.com`
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  9. docs/em/docs/tutorial/query-params-str-validations.md

        {!> ../../../docs_src/query_params_str_validations/tutorial003_py310.py!}
        ```
    
    ## 🚮 🥔 🧬
    
    👆 💪 🔬 <abbr title="A regular expression, regex or regexp is a sequence of characters that define a search pattern for strings.">🥔 🧬</abbr> 👈 🔢 🔜 🏏:
    
    === "🐍 3️⃣.6️⃣ &amp; 🔛"
    
        ```Python hl_lines="11"
        {!> ../../../docs_src/query_params_str_validations/tutorial004.py!}
        ```
    
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  10. docs/fr/docs/async.md

    Donc, pendant ce temps, l'ordinateur pourra effectuer d'autres tâches, pendant que "fichier-lent" 📝 se termine.
    
    Ensuite l'ordinateur / le programme 🤖 reviendra à chaque fois qu'il en a la chance que ce soit parce qu'il attend à nouveau, ou car il 🤖 a fini tout le travail qu'il avait à faire. Il 🤖 regardera donc si les tâches qu'il attend ont terminé d'être effectuées.
    
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