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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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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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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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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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docs/en/docs/release-notes.md
### Internal * 🔧 Update sponsors, remove Flint. PR [#10349](https://github.com/tiangolo/fastapi/pull/10349) by [@tiangolo](https://github.com/tiangolo). * 🔧 Rename label "awaiting review" to "awaiting-review" to simplify search queries. PR [#10343](https://github.com/tiangolo/fastapi/pull/10343) by [@tiangolo](https://github.com/tiangolo).
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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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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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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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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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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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