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  1. docs/en/docs/advanced/dataclasses.md

    So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.
    
    And of course, it supports the same:
    
    * data validation
    * data serialization
    * data documentation, etc.
    
    This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.
    
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  2. docs/en/docs/advanced/generate-clients.md

    For example, you might want to try <a href="https://speakeasyapi.dev/?utm_source=fastapi+repo&utm_medium=github+sponsorship" class="external-link" target="_blank">Speakeasy</a>.
    
    There are also several other companies offering similar services that you can search and find online. 🤓
    
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  3. docs/en/docs/advanced/behind-a-proxy.md

    We get the same response:
    
    ```JSON
    {
        "message": "Hello World",
        "root_path": "/api/v1"
    }
    ```
    
    but this time at the URL with the prefix path provided by the proxy: `/api/v1`.
    
    Of course, the idea here is that everyone would access the app through the proxy, so the version with the path prefix `/api/v1` is the "correct" one.
    
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  4. docs/pl/docs/index.md

    ---
    
    "_**Netflix** is pleased to announce the open-source release of our **crisis management** orchestration framework: **Dispatch**! [built with **FastAPI**]_"
    
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  5. docs/it/docs/index.md

    ---
    
    "_**Netflix** is pleased to announce the open-source release of our **crisis management** orchestration framework: **Dispatch**! [built with **FastAPI**]_"
    
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  6. .github/workflows/test-redistribute.yml

            with:
              python-version: "3.10"
          - name: Install build dependencies
            run: pip install build
          - name: Build source distribution
            env:
              TIANGOLO_BUILD_PACKAGE: ${{ matrix.package }}
            run: python -m build --sdist
          - name: Decompress source distribution
            run: |
              cd dist
              tar xvf fastapi*.tar.gz
          - name: Install test dependencies
            run: |
    Others
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  7. docs/de/docs/deployment/cloud.md

    * <a href="https://docs.platform.sh/languages/python.html?utm_source=fastapi-signup&utm_medium=banner&utm_campaign=FastAPI-signup-June-2023" class="external-link" target="_blank">Platform.sh</a>
    * <a href="https://docs.porter.run/language-specific-guides/fastapi" class="external-link" target="_blank">Porter</a>
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  8. pyproject.toml

        # Settings management
        "pydantic-settings >=2.0.0",
        # Extra Pydantic data types
        "pydantic-extra-types >=2.0.0",
    ]
    
    [tool.pdm]
    version = { source = "file", path = "fastapi/__init__.py" }
    distribution = true
    
    [tool.pdm.build]
    source-includes = [
        "tests/",
        "docs_src/",
        "requirements*.txt",
        "scripts/",
        # For a test
        "docs/en/docs/img/favicon.png",
        ]
    
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  9. docs/en/docs/deployment/concepts.md

    ## Running on Startup
    
    In most cases, when you create a web API, you want it to be **always running**, uninterrupted, so that your clients can always access it. This is of course, unless you have a specific reason why you want it to run only in certain situations, but most of the time you want it constantly running and **available**.
    
    ### In a Remote Server
    
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  10. docs/en/docs/fastapi-people.md

    Here are the **Top Contributors**. 👷
    
    These users have [created the most Pull Requests](help-fastapi.md#create-a-pull-request){.internal-link target=_blank} that have been *merged*.
    
    They have contributed source code, documentation, translations, etc. 📦
    
    {% if people %}
    <div class="user-list user-list-center">
    {% for user in people.top_contributors[:50] %}
    
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