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scripts/mkdocs_hooks.py
from functools import lru_cache from pathlib import Path from typing import Any, List, Union import material from mkdocs.config.defaults import MkDocsConfig from mkdocs.structure.files import File, Files from mkdocs.structure.nav import Link, Navigation, Section from mkdocs.structure.pages import Page non_traslated_sections = [ "reference/", "release-notes.md", ] @lru_cache
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docs/en/docs/tutorial/encoder.md
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docs/en/docs/how-to/custom-docs-ui-assets.md
### Project file structure Let's say your project file structure looks like this: ``` . ├── app │ ├── __init__.py │ ├── main.py ``` Now create a directory to store those static files. Your new file structure could look like this: ``` . ├── app │ ├── __init__.py │ ├── main.py └── static/ ```
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docs/en/docs/tutorial/dependencies/dependencies-in-path-operation-decorators.md
```Python hl_lines="9 14" {!> ../../../docs_src/dependencies/tutorial006.py!} ``` ## Dependencies for a group of *path operations*
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docs/fr/docs/advanced/additional-status-codes.md
# Codes HTTP supplémentaires Par défaut, **FastAPI** renverra les réponses à l'aide d'une structure de données `JSONResponse`, en plaçant la réponse de votre *chemin d'accès* à l'intérieur de cette `JSONResponse`. Il utilisera le code HTTP par défaut ou celui que vous avez défini dans votre *chemin d'accès*. ## Codes HTTP supplémentaires
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docs/en/docs/advanced/async-tests.md
The `TestClient` is based on <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a>, and luckily, we can use it directly to test the API. ## Example For a simple example, let's consider a file structure similar to the one described in [Bigger Applications](../tutorial/bigger-applications.md){.internal-link target=_blank} and [Testing](../tutorial/testing.md){.internal-link target=_blank}: ``` . ├── app │ ├── __init__.py
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docs/en/docs/how-to/sql-databases-peewee.md
So, we are going to focus only on the differences. ## File structure Let's say you have a directory named `my_super_project` that contains a sub-directory called `sql_app` with a structure like this: ``` . └── sql_app ├── __init__.py ├── crud.py ├── database.py ├── main.py └── schemas.py ``` This is almost the same structure as we had for the SQLAlchemy tutorial.
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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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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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