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  1. docs/en/docs/advanced/behind-a-proxy.md

    The docs UI would also need the OpenAPI schema to declare that this API `server` is located at `/api/v1` (behind the proxy). For example:
    
    ```JSON hl_lines="4-8"
    {
        "openapi": "3.1.0",
        // More stuff here
        "servers": [
            {
                "url": "/api/v1"
            }
        ],
        "paths": {
                // More stuff here
        }
    }
    ```
    
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  2. docs/en/docs/tutorial/first-steps.md

    #### API "schema"
    
    In this case, <a href="https://github.com/OAI/OpenAPI-Specification" class="external-link" target="_blank">OpenAPI</a> is a specification that dictates how to define a schema of your API.
    
    This schema definition includes your API paths, the possible parameters they take, etc.
    
    #### Data "schema"
    
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  3. docs/en/docs/tutorial/path-params.md

    ```Python hl_lines="7"
    {!../../../docs_src/path_params/tutorial002.py!}
    ```
    
    In this case, `item_id` is declared to be an `int`.
    
    !!! check
        This will give you editor support inside of your function, with error checks, completion, etc.
    
    ## Data <abbr title="also known as: serialization, parsing, marshalling">conversion</abbr>
    
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  4. docs/en/docs/benchmarks.md

        * But it provides you the tools to build simple web applications, with routing based on paths, etc.
        * If you are comparing Starlette, compare it against Sanic, Flask, Django, etc. Web frameworks (or microframeworks).
    * **FastAPI**:
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  5. docs/en/docs/alternatives.md

    !!! check "Inspired **FastAPI** to"
        Define extra validations for data types using the "default" value of model attributes. This improves editor support, and it was not available in Pydantic before.
    
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  6. docs_src/generate_clients/tutorial004.js

    async function modifyOpenAPIFile(filePath) {
      try {
        const data = await fs.promises.readFile(filePath)
        const openapiContent = JSON.parse(data)
    
        const paths = openapiContent.paths
        for (const pathKey of Object.keys(paths)) {
          const pathData = paths[pathKey]
          for (const method of Object.keys(pathData)) {
            const operation = pathData[method]
            if (operation.tags && operation.tags.length > 0) {
    JavaScript
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  7. fastapi/param_functions.py

                This doesn't affect `Path` parameters as the value is always required.
                The parameter is available only for compatibility.
                """
            ),
        ] = _Unset,
        alias: Annotated[
            Optional[str],
            Doc(
                """
                An alternative name for the parameter field.
    
                This will be used to extract the data and for the generated OpenAPI.
    Python
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  8. docs/en/docs/tutorial/response-model.md

        {!> ../../../docs_src/response_model/tutorial003_01.py!}
        ```
    
    With this, we get tooling support, from editors and mypy as this code is correct in terms of types, but we also get the data filtering from FastAPI.
    
    How does this work? Let's check that out. 🤓
    
    ### Type Annotations and Tooling
    
    First let's see how editors, mypy and other tools would see this.
    
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  9. docs/en/docs/advanced/dataclasses.md

    * 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.
    
    !!! info
        Keep in mind that dataclasses can't do everything Pydantic models can do.
    
        So, you might still need to use Pydantic models.
    
        But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓
    
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  10. fastapi/security/oauth2.py

            return param
    
    
    class SecurityScopes:
        """
        This is a special class that you can define in a parameter in a dependency to
        obtain the OAuth2 scopes required by all the dependencies in the same chain.
    
        This way, multiple dependencies can have different scopes, even when used in the
        same *path operation*. And with this, you can access all the scopes required in
        all those dependencies in a single place.
    Python
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