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docs/en/docs/advanced/generate-clients.md
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docs/en/docs/advanced/behind-a-proxy.md
[http.routers] [http.routers.app-http] entryPoints = ["http"] service = "app" rule = "PathPrefix(`/api/v1`)" middlewares = ["api-stripprefix"] [http.services] [http.services.app] [http.services.app.loadBalancer] [[http.services.app.loadBalancer.servers]] url = "http://127.0.0.1:8000" ```
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docs/en/docs/deployment/concepts.md
* **Cloud services** that handle this for you * The cloud service will probably **handle replication for you**. It would possibly let you define **a process to run**, or a **container image** to use, in any case, it would most probably be **a single Uvicorn process**, and the cloud service would be in charge of replicating it. !!! tip
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tests/test_query.py
response = client.get("/query/list/?device_ids=1&device_ids=2") assert response.status_code == 200 assert response.json() == [1, 2] def test_query_list_empty(): response = client.get("/query/list/") assert response.status_code == 422 def test_query_list_default(): response = client.get("/query/list-default/?device_ids=1&device_ids=2") assert response.status_code == 200
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docs/pl/docs/index.md
## Opinie "_[...] I'm using **FastAPI** a ton these days. [...] I'm actually planning to use it for all of my team's **ML services at Microsoft**. Some of them are getting integrated into the core **Windows** product and some **Office** products._"
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docs/it/docs/index.md
## Recensioni "_[...] I'm using **FastAPI** a ton these days. [...] I'm actually planning to use it for all of my team's **ML services at Microsoft**. Some of them are getting integrated into the core **Windows** product and some **Office** products._"
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docs/vi/docs/features.md
### Dependency Injection FastAPI bao gồm một hệ thống <abbr title='cũng biết đến như là "components", "resources", "services", "providers"'><strong>Dependency Injection</strong></abbr> vô cùng dễ sử dụng nhưng vô cùng mạnh mẽ. * Thậm chí, các dependency có thể có các dependency khác, tạo thành một phân cấp hoặc **"một đồ thị" của các dependency**.
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docs/en/docs/alternatives.md
Starlette is a lightweight <abbr title="The new standard for building asynchronous Python web applications">ASGI</abbr> framework/toolkit, which is ideal for building high-performance asyncio services. It is very simple and intuitive. It's designed to be easily extensible, and have modular components. It has: * Seriously impressive performance. * WebSocket support. * In-process background tasks.
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docs/zh/docs/index.md
**剧透警告**: 教程 - 用户指南中的内容有: * 对来自不同地方的参数进行声明,如:**请求头**、**cookies**、**form 表单**以及**上传的文件**。 * 如何设置**校验约束**如 `maximum_length` 或者 `regex`。 * 一个强大并易于使用的 **<abbr title="也被称为 components, resources, providers, services, injectables">依赖注入</abbr>** 系统。 * 安全性和身份验证,包括通过 **JWT 令牌**和 **HTTP 基本身份认证**来支持 **OAuth2**。 * 更进阶(但同样简单)的技巧来声明 **多层嵌套 JSON 模型** (借助 Pydantic)。 * 许多额外功能(归功于 Starlette)比如: * **WebSockets** * **GraphQL**
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docs/de/docs/advanced/behind-a-proxy.md
[http.routers] [http.routers.app-http] entryPoints = ["http"] service = "app" rule = "PathPrefix(`/api/v1`)" middlewares = ["api-stripprefix"] [http.services] [http.services.app] [http.services.app.loadBalancer] [[http.services.app.loadBalancer.servers]] url = "http://127.0.0.1:8000" ```
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