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  1. docs/en/docs/deployment/manually.md

     │                          │
     ╰──────────────────────────╯
    
    <font color="#3465A4">INFO    </font> Using import string <font color="#8AE234"><b>main:app</b></font>
    
     <font color="#4E9A06">╭─────────── FastAPI CLI - Production mode ───────────╮</font>
     <font color="#4E9A06">│                                                     │</font>
     <font color="#4E9A06">│  Serving at: http://0.0.0.0:8000                    │</font>
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  2. docs/en/docs/advanced/behind-a-proxy.md

    By default, **FastAPI** will create a `server` in the OpenAPI schema with the URL for the `root_path`.
    
    But you can also provide other alternative `servers`, for example if you want *the same* docs UI to interact with a staging and production environments.
    
    If you pass a custom list of `servers` and there's a `root_path` (because your API lives behind a proxy), **FastAPI** will insert a "server" with this `root_path` at the beginning of the list.
    
    For example:
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  3. fastapi/__init__.py

    """FastAPI framework, high performance, easy to learn, fast to code, ready for production"""
    
    __version__ = "0.111.0"
    
    from starlette import status as status
    
    from .applications import FastAPI as FastAPI
    from .background import BackgroundTasks as BackgroundTasks
    from .datastructures import UploadFile as UploadFile
    from .exceptions import HTTPException as HTTPException
    from .exceptions import WebSocketException as WebSocketException
    Python
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  4. docs/en/docs/how-to/async-sql-encode-databases.md

    * PostgreSQL
    * MySQL
    * SQLite
    
    In this example, we'll use **SQLite**, because it uses a single file and Python has integrated support. So, you can copy this example and run it as is.
    
    Later, for your production application, you might want to use a database server like **PostgreSQL**.
    
    !!! tip
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  5. docs/hu/docs/index.md

    * **Egyszerű**: Egyszerű tanulásra és használatra tervezve. Kevesebb dokumentáció olvasással töltött idő.
    * **Rövid**: Kód duplikáció minimalizálása. Több funkció minden paraméter deklarálásával. Kevesebb hiba.
    * **Robosztus**: Production ready kód. Automatikus interaktív dokumentáció val.
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  6. docs/en/docs/fastapi-cli.md

    For production you would use `fastapi run` instead. 🚀
    
    Internally, **FastAPI CLI** uses <a href="https://www.uvicorn.org" class="external-link" target="_blank">Uvicorn</a>, a high-performance, production-ready, ASGI server. 😎
    
    ## `fastapi dev`
    
    When you run `fastapi dev`, it will run on development mode.
    
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  7. docs/en/docs/advanced/generate-clients.md

    **build** the client it will error out if you have any **mismatch** in the data used.
    
    So, you would **detect many errors** very early in the development cycle instead of having to wait for the errors to show up to your final users in production and then trying to debug where the problem is. ✨...
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  8. docs/en/docs/advanced/websockets.md

    First you need to install `WebSockets`:
    
    <div class="termy">
    
    ```console
    $ pip install websockets
    
    ---> 100%
    ```
    
    </div>
    
    ## WebSockets client
    
    ### In production
    
    In your production system, you probably have a frontend created with a modern framework like React, Vue.js or Angular.
    
    And to communicate using WebSockets with your backend you would probably use your frontend's utilities.
    
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  9. docs/en/docs/tutorial/first-steps.md

     <span style="background-color:#C4A000"><font color="#2E3436">│                                                     │</font></span>
     <span style="background-color:#C4A000"><font color="#2E3436">│  Running in development mode, for production use:   │</font></span>
     <span style="background-color:#C4A000"><font color="#2E3436">│                                                     │</font></span>
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  10. pyproject.toml

    [build-system]
    requires = ["pdm-backend"]
    build-backend = "pdm.backend"
    
    [project]
    name = "fastapi"
    dynamic = ["version"]
    description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
    readme = "README.md"
    requires-python = ">=3.8"
    authors = [
        { name = "Sebastián Ramírez", email = "******@****.***" },
    ]
    classifiers = [
        "Intended Audience :: Information Technology",
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