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docs/fr/docs/async.md
Pour parler de tâches "synchrones" (en opposition à "asynchrones"), on utilise souvent le terme "séquentiel", car l'ordinateur / le programme va effectuer toutes les étapes d'une tâche séquentiellement avant de passer à une autre tâche, même si ces étapes impliquent de l'attente. ### Concurrence et Burgers
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Sun Aug 31 09:56:21 UTC 2025 - 25.4K bytes - Viewed (0) -
docs/en/docs/tutorial/bigger-applications.md
/// ## Check the automatic API docs { #check-the-automatic-api-docs } Now, run your app: <div class="termy"> ```console $ fastapi dev app/main.py <span style="color: green;">INFO</span>: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit) ``` </div>
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docs/uk/docs/tutorial/first-steps.md
# Перші кроки Найпростіший файл FastAPI може виглядати так: {* ../../docs_src/first_steps/tutorial001.py *} Скопіюйте це до файлу `main.py`. Запустіть сервер: <div class="termy"> ```console $ <font color="#4E9A06">fastapi</font> dev <u style="text-decoration-style:single">main.py</u> <font color="#3465A4">INFO </font> Using path <font color="#3465A4">main.py</font>
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docs/en/docs/async.md
For "synchronous" (contrary to "asynchronous") they commonly also use the term "sequential", because the computer / program follows all the steps in sequence before switching to a different task, even if those steps involve waiting. ### Concurrency and Burgers { #concurrency-and-burgers }
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RELEASE.md
* `tf.lite` * LiteRT announced a [new release](https://developers.googleblog.com/en/litert-maximum-performance-simplified/) at Google IO ‘25 that improves upon TFLite, particularly in terms of NPU and GPU hardware acceleration and performance for on-device ML and AI applications. The APIs are available in Kotlin and C++.
Registered: Tue Sep 09 12:39:10 UTC 2025 - Last Modified: Mon Aug 18 20:54:38 UTC 2025 - 740K bytes - Viewed (2) -
docs/ko/docs/deployment/docker.md
* FastAPI 이미지를 빌드합니다: <div class="termy"> ```console $ docker build -t myimage . ---> 100% ``` </div> /// tip | 팁 맨 끝에 있는 `.` 에 주목합시다. 이는 `./`와 동등하며, 도커에게 컨테이너 이미지를 빌드하기 위한 디렉터리를 알려줍니다. 이 경우에는 현재 디렉터리(`.`)와 같습니다. /// ### 도커 컨테이너 시작하기 * 여러분의 이미지에 기반하여 컨테이너를 실행합니다: <div class="termy"> ```console
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docs/pt/docs/async.md
Para "síncrono" (contrário de "assíncrono") também é utilizado o termo "sequencial", porquê o computador / programa segue todos os passos, em sequência, antes de trocar para uma tarefa diferente, mesmo se alguns passos envolvam esperar. ### Concorrência e hambúrgueres
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docs/ja/docs/tutorial/security/first-steps.md
例えば、`pip install python-multipart`。 これは、**OAuth2**が `ユーザー名` や `パスワード` を送信するために、「フォームデータ」を使うからです。 /// 例を実行します: <div class="termy"> ```console $ uvicorn main:app --reload <span style="color: green;">INFO</span>: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit) ``` </div> ## 確認
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docs/de/docs/tutorial/bigger-applications.md
/// ## Es in der automatischen API-Dokumentation ansehen Führen Sie nun `uvicorn` aus, indem Sie das Modul `app.main` und die Variable `app` verwenden: <div class="termy"> ```console $ uvicorn app.main:app --reload <span style="color: green;">INFO</span>: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit) ``` </div>
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docs/ru/docs/tutorial/bigger-applications.md
/// ## Проверка автоматической документации API Теперь запустите приложение: <div class="termy"> ```console $ fastapi dev app/main.py <span style="color: green;">INFO</span>: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit) ``` </div>
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