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docs/em/docs/python-types.md
👉 🆎 👈 ✔️ 🔗 🆎 🤙 "**💊**" 🆎. & ⚫️ 💪 📣 👫, ⏮️ 👫 🔗 🆎. 📣 👈 🆎 & 🔗 🆎, 👆 💪 ⚙️ 🐩 🐍 🕹 `typing`. ⚫️ 🔀 🎯 🐕🦺 👫 🆎 🔑. #### 🆕 ⏬ 🐍 ❕ ⚙️ `typing` **🔗** ⏮️ 🌐 ⏬, ⚪️➡️ 🐍 3️⃣.6️⃣ ⏪ 🕐, ✅ 🐍 3️⃣.9️⃣, 🐍 3️⃣.1️⃣0️⃣, ♒️. 🐍 🏧, **🆕 ⏬** 👟 ⏮️ 📉 🐕🦺 👉 🆎 ✍ & 📚 💼 👆 🏆 🚫 💪 🗄 & ⚙️ `typing` 🕹 📣 🆎 ✍. 🚥 👆 💪 ⚒ 🌖 ⏮️ ⏬ 🐍 👆 🏗, 👆 🔜 💪 ✊ 📈 👈 ➕ 🦁. 👀 🖼 🔛. #### 📇
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docs/en/docs/deployment/docker.md
```Dockerfile COPY ./requirements.txt /code/requirements.txt ``` Docker and other tools **build** these container images **incrementally**, adding **one layer on top of the other**, starting from the top of the `Dockerfile` and adding any files created by each of the instructions of the `Dockerfile`.
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docs/vi/docs/python-types.md
Để khai báo những kiểu dữ liệu và những kiểu dữ liệu nội bộ đó, bạn có thể sử dụng mô đun chuẩn của Python là `typing`. Nó có hỗ trợ những gợi ý kiểu dữ liệu này. #### Những phiên bản mới hơn của Python Cú pháp sử dụng `typing` **tương thích** với tất cả các phiên bản, từ Python 3.6 tới những phiên bản cuối cùng, bao gồm Python 3.9, Python 3.10,...
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docs/em/docs/tutorial/extra-models.md
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docs_src/extra_data_types/tutorial001_an.py
from datetime import datetime, time, timedelta from typing import Union from uuid import UUID from fastapi import Body, FastAPI from typing_extensions import Annotated app = FastAPI() @app.put("/items/{item_id}") async def read_items( item_id: UUID, start_datetime: Annotated[datetime, Body()], end_datetime: Annotated[datetime, Body()], process_after: Annotated[timedelta, Body()],
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pyproject.toml
"Topic :: Software Development :: Libraries :: Python Modules", "Topic :: Software Development :: Libraries", "Topic :: Software Development", "Typing :: Typed", "Development Status :: 4 - Beta", "Environment :: Web Environment", "Framework :: AsyncIO", "Framework :: FastAPI", "Framework :: Pydantic", "Framework :: Pydantic :: 1",
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pdm_build.py
import os from typing import Any, Dict, List from pdm.backend.hooks import Context TIANGOLO_BUILD_PACKAGE = os.getenv("TIANGOLO_BUILD_PACKAGE", "fastapi") def pdm_build_initialize(context: Context) -> None: metadata = context.config.metadata # Get custom config for the current package, from the env var config: Dict[str, Any] = context.config.data["tool"]["tiangolo"][ "_internal-slim-build"
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fastapi/openapi/models.py
from enum import Enum from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Type, Union from fastapi._compat import ( PYDANTIC_V2, CoreSchema, GetJsonSchemaHandler, JsonSchemaValue, _model_rebuild, with_info_plain_validator_function, ) from fastapi.logger import logger from pydantic import AnyUrl, BaseModel, Field from typing_extensions import Annotated, Literal, TypedDict
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docs/pt/docs/tutorial/body-nested-models.md
### Importe `List` do typing Primeiramente, importe `List` do módulo `typing` que já vem por padrão no Python: ```Python hl_lines="1" {!../../../docs_src/body_nested_models/tutorial002.py!} ``` ### Declare a `List` com um parâmetro de tipo Para declarar tipos que têm parâmetros de tipo(tipos internos), como `list`, `dict`, `tuple`: * Importe os do modulo `typing`
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docs_src/extra_data_types/tutorial001_an_py39.py
from datetime import datetime, time, timedelta from typing import Annotated, Union from uuid import UUID from fastapi import Body, FastAPI app = FastAPI() @app.put("/items/{item_id}") async def read_items( item_id: UUID, start_datetime: Annotated[datetime, Body()], end_datetime: Annotated[datetime, Body()], process_after: Annotated[timedelta, Body()], repeat_at: Annotated[Union[time, None], Body()] = None, ):
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