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  1. 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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  2. 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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  3. 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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  4. 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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  5. docs/en/docs/python-types.md

    At some point you would have started the definition of the function, you had the parameters ready...
    
    But then you have to call "that method that converts the first letter to upper case".
    
    Was it `upper`? Was it `uppercase`? `first_uppercase`? `capitalize`?
    
    Then, you try with the old programmer's friend, editor autocompletion.
    
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  6. docs/en/docs/tutorial/bigger-applications.md

    !!! tip
        Note that, much like [dependencies in *path operation decorators*](dependencies/dependencies-in-path-operation-decorators.md){.internal-link target=_blank}, no value will be passed to your *path operation function*.
    
    The end result is that the item paths are now:
    
    * `/items/`
    * `/items/{item_id}`
    
    ...as we intended.
    
    * They will be marked with a list of tags that contain a single string `"items"`.
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  7. 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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  8. 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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  9. docs/en/docs/tutorial/security/oauth2-jwt.md

        And be compatible with all of them at the same time.
    
    Create a utility function to hash a password coming from the user.
    
    And another utility to verify if a received password matches the hash stored.
    
    And another one to authenticate and return a user.
    
    === "Python 3.10+"
    
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  10. docs/en/docs/advanced/custom-response.md

    {!../../../docs_src/custom_response/tutorial008.py!}
    ```
    
    1. This is the generator function. It's a "generator function" because it contains `yield` statements inside.
    2. By using a `with` block, we make sure that the file-like object is closed after the generator function is done. So, after it finishes sending the response.
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