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docs/en/docs/tutorial/response-model.md
# Response Model - Return Type You can declare the type used for the response by annotating the *path operation function* **return type**. You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc. === "Python 3.10+" ```Python hl_lines="16 21" {!> ../../../docs_src/response_model/tutorial001_01_py310.py!} ```
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docs/en/docs/tutorial/first-steps.md
### Step 4: define the **path operation function** This is our "**path operation function**": * **path**: is `/`. * **operation**: is `get`. * **function**: is the function below the "decorator" (below `@app.get("/")`). ```Python hl_lines="7" {!../../../docs_src/first_steps/tutorial001.py!} ``` This is a Python function.
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docs/en/docs/reference/background.md
# Background Tasks - `BackgroundTasks` You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent. You can import it directly from `fastapi`: ```python from fastapi import BackgroundTasks ```
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docs/en/docs/advanced/generate-clients.md
### Custom Generate Unique ID Function FastAPI uses a **unique ID** for each *path operation*, it is used for the **operation ID** and also for the names of any needed custom models, for requests or responses. You can customize that function. It takes an `APIRoute` and outputs a string.
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docs/en/docs/reference/request.md
# `Request` class You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc. You can import it directly from `fastapi`: ```python from fastapi import Request ``` !!! tip
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docs/en/docs/advanced/dataclasses.md
8. Notice that this *path operation function* uses regular `def` instead of `async def`. As always, in FastAPI you can combine `def` and `async def` as needed. If you need a refresher about when to use which, check out the section _"In a hurry?"_ in the docs about [`async` and `await`](../async.md#in-a-hurry){.internal-link target=_blank}.
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fastapi/param_functions.py
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docs/en/docs/alternatives.md
It is designed to have functions that receive two parameters, one "request" and one "response". Then you "read" parts from the request, and "write" parts to the response. Because of this design, it is not possible to declare request parameters and bodies with standard Python type hints as function parameters.
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docs/vi/docs/features.md
Bạn viết chuẩn Python với kiểu dữ liệu như sau: ```Python from datetime import date from pydantic import BaseModel # Declare a variable as a str # and get editor support inside the function def main(user_id: str): return user_id # A Pydantic model class User(BaseModel): id: int name: str joined: date ``` Sau đó có thể được sử dụng: ```Python
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docs/en/docs/tutorial/dependencies/index.md
!!! tip You'll see what other "things", apart from functions, can be used as dependencies in the next chapter. Whenever a new request arrives, **FastAPI** will take care of: * Calling your dependency ("dependable") function with the correct parameters. * Get the result from your function. * Assign that result to the parameter in your *path operation function*. ```mermaid graph TB
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