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docs/pl/docs/index.md
--- "_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_" <div style="text-align: right; margin-right: 10%;">Piero Molino, Yaroslav Dudin, and Sai Sumanth Miryala - <strong>Uber</strong> <a href="https://eng.uber.com/ludwig-v0-2/" target="_blank"><small>(ref)</small></a></div> ---
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docs/ru/docs/index.md
--- ## **Typer**, интерфейс командной строки для FastAPI
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docs/it/docs/index.md
--- "_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_" <div style="text-align: right; margin-right: 10%;">Piero Molino, Yaroslav Dudin, e Sai Sumanth Miryala - <strong>Uber</strong> <a href="https://eng.uber.com/ludwig-v0-2/" target="_blank"><small>(ref)</small></a></div> ---
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docs/zh/docs/index.md
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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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.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/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/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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