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  1. docs/en/layouts/custom.yml

          align: start
          color: *color
          line:
            amount: 3
            height: 1.25
          font:
            family: *font_family
            style: Bold
    
      # Page description
      - size: { width: 832, height: 64 }
        offset: { x: 64, y: 512 }
        typography:
          content: *page_description
          align: start
          color: *color
          line:
            amount: 2
            height: 1.5
          font:
    Others
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  2. docs/en/docs/tutorial/first-steps.md

    <font color="#4E9A06">INFO</font>:     Application startup complete.
    ```
    
    </div>
    
    In the output, there's a line with something like:
    
    ```hl_lines="4"
    INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
    ```
    
    That line shows the URL where your app is being served, in your local machine.
    
    ### Check it
    
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  3. docs/en/docs/contributing.md

    ## Docs
    
    First, make sure you set up your environment as described above, that will install all the requirements.
    
    ### Docs live
    
    During local development, there is a script that builds the site and checks for any changes, live-reloading:
    
    <div class="termy">
    
    ```console
    $ python ./scripts/docs.py live
    
    <span style="color: green;">[INFO]</span> Serving on http://127.0.0.1:8008
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  4. docs/en/docs/advanced/behind-a-proxy.md

                // More stuff here
        }
    }
    ```
    
    In this example, the "Proxy" could be something like **Traefik**. And the server would be something like FastAPI CLI with **Uvicorn**, running your FastAPI application.
    
    ### Providing the `root_path`
    
    To achieve this, you can use the command line option `--root-path` like:
    
    <div class="termy">
    
    ```console
    $ fastapi run main.py --root-path /api/v1
    
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  5. docs/en/docs/advanced/testing-database.md

    ```Python
    Base.metadata.create_all(bind=engine)
    ```
    
    That is normally called in `main.py`, but the line in `main.py` uses the database file `sql_app.db`, and we need to make sure we create `test.db` for the tests.
    
    So we add that line here, with the new file.
    
    ```Python hl_lines="16"
    {!../../../docs_src/sql_databases/sql_app/tests/test_sql_app.py!}
    ```
    
    ## Dependency override
    
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  6. docs/en/docs/deployment/manually.md

    The main thing you need to run a **FastAPI** application (or any other ASGI application) in a remote server machine is an ASGI server program like **Uvicorn**, this is the one that comes by default in the `fastapi` command.
    
    There are several alternatives, including:
    
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  7. docs/en/docs/advanced/generate-clients.md

    ```
    
    </div>
    
    #### Generate Client Code
    
    To generate the client code you can use the command line application `openapi-ts` that would now be installed.
    
    Because it is installed in the local project, you probably wouldn't be able to call that command directly, but you would put it on your `package.json` file.
    
    It could look like this:
    
    ```JSON  hl_lines="7"
    {
      "name": "frontend-app",
      "version": "1.0.0",
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  8. docs/en/docs/tutorial/testing.md

    ```
    
    In the file `main.py` you have your **FastAPI** app:
    
    
    ```Python
    {!../../../docs_src/app_testing/main.py!}
    ```
    
    ### Testing file
    
    Then you could have a file `test_main.py` with your tests. It could live on the same Python package (the same directory with a `__init__.py` file):
    
    ``` hl_lines="5"
    .
    ├── app
    │   ├── __init__.py
    │   ├── main.py
    │   └── test_main.py
    ```
    
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  9. docs/en/docs/alternatives.md

    It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.
    
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  10. docs/en/docs/benchmarks.md

        * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself....
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