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.github/workflows/test.yml
- name: Install Dependencies if: steps.cache.outputs.cache-hit != 'true' run: pip install -r requirements-tests.txt - name: Install Pydantic v1 if: matrix.pydantic-version == 'pydantic-v1' run: pip install "pydantic>=1.10.0,<2.0.0" - name: Install Pydantic v2 if: matrix.pydantic-version == 'pydantic-v2'
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docs/en/docs/deployment/manually.md
## Install the Server Program When you install FastAPI, it comes with a production server, Uvicorn, and you can start it with the `fastapi run` command. But you can also install an ASGI server manually: === "Uvicorn"
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docs/en/docs/contributing.md
### Install requirements using pip After activating the environment as described above: <div class="termy"> ```console $ pip install -r requirements.txt ---> 100% ``` </div> It will install all the dependencies and your local FastAPI in your local environment. ### Using your local FastAPI
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docs/uk/docs/tutorial/index.md
Це те, що ви, ймовірно, зробили б, коли захочете розгорнути свою програму у виробничому середовищі: ``` pip install fastapi ``` Також встановіть `uvicorn`, щоб він працював як сервер: ``` pip install "uvicorn[standard]" ``` І те саме для кожної з опціональних залежностей, які ви хочете використовувати. ## Розширений посібник користувача
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docs/pt/docs/tutorial/index.md
<div class="termy"> ```console $ pip install "fastapi[all]" ---> 100% ``` </div> ...isso também inclui o `uvicorn`, que você pode usar como o servidor que rodará seu código. !!! note "Nota" Você também pode instalar parte por parte. Isso é provavelmente o que você faria quando você quisesse lançar sua aplicação em produção: ``` pip install fastapi ```
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.github/workflows/publish.yml
python-version: "3.10" # Issue ref: https://github.com/actions/setup-python/issues/436 # cache: "pip" # cache-dependency-path: pyproject.toml - name: Install build dependencies run: pip install build - name: Build distribution env: TIANGOLO_BUILD_PACKAGE: ${{ matrix.package }} run: python -m build - name: Publish
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docs/ko/docs/tutorial/index.md
<div class="termy"> ```console $ pip install "fastapi[all]" ---> 100% ``` </div> ...이는 코드를 실행하는 서버로 사용할 수 있는 `uvicorn` 또한 포함하고 있습니다. !!! note "참고" 부분적으로 설치할 수도 있습니다. 애플리케이션을 운영 환경에 배포하려는 경우 다음과 같이 합니다: ``` pip install fastapi ``` 추가로 서버 역할을 하는 `uvicorn`을 설치합니다: ``` pip install uvicorn ``` 사용하려는 각 선택적인 의존성에 대해서도 동일합니다.
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docs/en/docs/tutorial/testing.md
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docs/ru/docs/deployment/docker.md
# (2) WORKDIR /tmp # (3) RUN pip install poetry # (4) COPY ./pyproject.toml ./poetry.lock* /tmp/ # (5) RUN poetry export -f requirements.txt --output requirements.txt --without-hashes # (6) FROM python:3.9 # (7) WORKDIR /code # (8) COPY --from=requirements-stage /tmp/requirements.txt /code/requirements.txt # (9) RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
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docs/en/docs/advanced/generate-clients.md
### Generate a TypeScript Client Now that we have the app with the models, we can generate the client code for the frontend. #### Install `openapi-ts` You can install `openapi-ts` in your frontend code with: <div class="termy"> ```console $ npm install @hey-api/openapi-ts --save-dev ---> 100% ``` </div> #### Generate Client Code
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