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docs/en/docs/tutorial/testing.md
In a real application, you probably would have your tests in a different file. And your **FastAPI** application might also be composed of several files/modules, etc. ### **FastAPI** app file Let's say you have a file structure as described in [Bigger Applications](bigger-applications.md){.internal-link target=_blank}: ``` . ├── app │ ├── __init__.py │ └── main.py ``` In the file `main.py` you have your **FastAPI** app:
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docs/en/docs/tutorial/bigger-applications.md
**FastAPI** provides a convenience tool to structure your application while keeping all the flexibility. !!! info If you come from Flask, this would be the equivalent of Flask's Blueprints. ## An example file structure Let's say you have a file structure like this: ``` . ├── app │ ├── __init__.py │ ├── main.py │ ├── dependencies.py
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docs/en/docs/deployment/manually.md
<font color="#3465A4">INFO </font> Resolved absolute path <font color="#75507B">/home/user/code/awesomeapp/</font><font color="#AD7FA8">main.py</font> <font color="#3465A4">INFO </font> Searching for package file structure from directories with <font color="#3465A4">__init__.py</font> files <font color="#3465A4">INFO </font> Importing from <font color="#75507B">/home/user/code/</font><font color="#AD7FA8">awesomeapp</font>
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docs/en/docs/tutorial/first-steps.md
<font color="#3465A4">INFO </font> Resolved absolute path <font color="#75507B">/home/user/code/awesomeapp/</font><font color="#AD7FA8">main.py</font> <font color="#3465A4">INFO </font> Searching for package file structure from directories with <font color="#3465A4">__init__.py</font> files <font color="#3465A4">INFO </font> Importing from <font color="#75507B">/home/user/code/</font><font color="#AD7FA8">awesomeapp</font>
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docs/en/docs/advanced/dataclasses.md
This way, its schema will show up in the API docs user interface: <img src="/img/tutorial/dataclasses/image01.png"> ## Dataclasses in Nested Data Structures You can also combine `dataclasses` with other type annotations to make nested data structures. In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.
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docs/es/docs/tutorial/cookie-params.md
```Python hl_lines="3" {!> ../../../docs_src/cookie_params/tutorial001.py!} ``` ## Declarar parámetros de `Cookie` Luego declara los parámetros de cookie usando la misma estructura que con `Path` y `Query`. El primer valor es el valor por defecto, puedes pasar todos los parámetros adicionales de validación o anotación: === "Python 3.10+" ```Python hl_lines="9"
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docs/de/docs/features.md
Inklusive externer Bibliotheken, die auf Pydantic basieren, wie <abbr title="Object-Relational Mapper (Abbildung von Objekten auf relationale Strukturen)">ORM</abbr>s, <abbr title="Object-Document Mapper (Abbildung von Objekten auf nicht-relationale Strukturen)">ODM</abbr>s für Datenbanken. Daher können Sie in vielen Fällen das Objekt einer Anfrage **direkt zur Datenbank** schicken, weil alles automatisch validiert wird.
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docs/en/docs/release-notes.md
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docs/en/docs/features.md
* Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data. * Validate **complex structures**: * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
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docs/en/docs/fastapi-cli.md
<font color="#3465A4">INFO </font> Resolved absolute path <font color="#75507B">/home/user/code/awesomeapp/</font><font color="#AD7FA8">main.py</font> <font color="#3465A4">INFO </font> Searching for package file structure from directories with <font color="#3465A4">__init__.py</font> files <font color="#3465A4">INFO </font> Importing from <font color="#75507B">/home/user/code/</font><font color="#AD7FA8">awesomeapp</font>
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