有两个项目，你可以看到如何正确地做到这一点，或者你可以使用这些项目来构建你自己的图像，因为它们只是基础图像:

https://github.com/max-pfeiffer/uvicorn-poetry https://github.com/max-pfeiffer/uvicorn-gunicorn-poetry

base image的Dockerfile: https://github.com/max-pfeiffer/uvicorn-poetry/blob/main/build/Dockerfile

ARG OFFICIAL_PYTHON_IMAGE
FROM ${OFFICIAL_PYTHON_IMAGE}

ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1 \
    PIP_NO_CACHE_DIR=off \
    PIP_DISABLE_PIP_VERSION_CHECK=on \
    PIP_DEFAULT_TIMEOUT=100 \
    POETRY_VERSION=1.1.11 \
    POETRY_HOME="/opt/poetry" \
    POETRY_VIRTUALENVS_IN_PROJECT=true \
    PYTHONPATH=/application_root \
    VIRTUAL_ENVIRONMENT_PATH="/application_root/.venv"

ENV PATH="$POETRY_HOME/bin:$VIRTUAL_ENVIRONMENT_PATH/bin:$PATH"

# https://python-poetry.org/docs/#osx--linux--bashonwindows-install-instructions
RUN apt-get update \
    && apt-get install --no-install-recommends -y \
        build-essential \
        curl \
    && curl -sSL https://raw.githubusercontent.com/sdispater/poetry/master/get-poetry.py | python - \
    && apt-get purge --auto-remove -y \
      build-essential \
      curl

COPY ./scripts/start_uvicorn.sh /application_server/
RUN chmod +x /application_server/start_uvicorn.sh

COPY ./scripts/pytest_entrypoint.sh ./scripts/black_entrypoint.sh /entrypoints/
RUN chmod +x /entrypoints/pytest_entrypoint.sh
RUN chmod +x /entrypoints/black_entrypoint.sh

EXPOSE 80

CMD ["/application_server/start_uvicorn.sh"]

样例工程图片的Dockerfile: https://github.com/max-pfeiffer/uvicorn-poetry/blob/main/examples/fast_api_multistage_build/Dockerfile

ARG BASE_IMAGE_NAME_AND_TAG=pfeiffermax/uvicorn-poetry:1.0.1-python3.9.8-slim-bullseye
FROM ${BASE_IMAGE_NAME_AND_TAG} as base-image

WORKDIR /application_root

# install [tool.poetry.dependencies]
# this will install virtual environment into /.venv because of POETRY_VIRTUALENVS_IN_PROJECT=true
# see: https://python-poetry.org/docs/configuration/#virtualenvsin-project
COPY ./poetry.lock ./pyproject.toml /application_root/
RUN poetry install --no-interaction --no-root --no-dev

FROM base-image as test-base-image
ENV LOG_LEVEL="debug"

COPY --from=base-image $VIRTUAL_ENVIRONMENT_PATH $VIRTUAL_ENVIRONMENT_PATH

# install [tool.poetry.dev-dependencies]
RUN poetry install --no-interaction --no-root

COPY /app /application_root/app/
COPY /tests /application_root/tests/

# image for running pep8 checks
FROM test-base-image as black-test-image

ENTRYPOINT /entrypoints/black_entrypoint.sh $0 $@

CMD ["--target-version py39", "--check", " --line-length 80", "app"]

# image for running unit tests
FROM test-base-image as unit-test-image

ENTRYPOINT /entrypoints/pytest_entrypoint.sh $0 $@

# You need to use pytest-cov as pytest plugin. Makes life very simple.
# tests directory is configured in pyproject.toml
# https://github.com/pytest-dev/pytest-cov
CMD ["--cov=app", "--cov-report=xml:/test_coverage_reports/unit_tests_coverage.xml"]

FROM base-image as development-image
ENV RELOAD="true" \
    LOG_LEVEL="debug"

COPY --from=base-image $VIRTUAL_ENVIRONMENT_PATH $VIRTUAL_ENVIRONMENT_PATH

# install [tool.poetry.dev-dependencies]
RUN poetry install --no-interaction --no-root

COPY . /application_root/

FROM base-image as production-image

COPY --from=base-image $VIRTUAL_ENVIRONMENT_PATH $VIRTUAL_ENVIRONMENT_PATH

# This RUN statement fixes an issue while running the tests with GitHub Actions.
# Tests work reliable locally on my machine or running GitHub Actions using act.
# There is a bug with multistage builds in GitHub Actions which I can also reliable reproduce
# see: https://github.com/moby/moby/issues/37965
# Will also check if I can fix that annoying issue with some tweaks to docker build args
# see: https://gist.github.com/UrsaDK/f90c9632997a70cfe2a6df2797731ac8
RUN true

COPY /app /application_root/app/

我使用一个锁包(包依赖于锁文件中的所有版本)创建了一个解决方案。这将导致没有需求文件的纯pip安装。

步骤是:构建包，构建锁包，将两个轮子复制到容器中，使用pip安装两个轮子。

安装是:诗词add——dev诗词锁包

docker构建之外的步骤是:

poetry build
poetry run poetry-lock-package --build

然后你的Dockerfile应该包含:

FROM python:3-slim

COPY dist/*.whl /

RUN pip install --no-cache-dir /*.whl \
    && rm -rf /*.whl

CMD ["python", "-m", "entry_module"]

博士TL;

我已经能够使用postgres为Django项目创建诗歌。在做了一些研究后，我最终得到了以下Dockerfile:

FROM python:slim

# Keeps Python from generating .pyc files in the container
ENV PYTHONDONTWRITEBYTECODE 1
# Turns off buffering for easier container logging
ENV PYTHONUNBUFFERED 1

# Install and setup poetry
RUN pip install -U pip \
    && apt-get update \
    && apt install -y curl netcat \
    && curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
ENV PATH="${PATH}:/root/.poetry/bin"

WORKDIR /usr/src/app
COPY . .
RUN poetry config virtualenvs.create false \
  && poetry install --no-interaction --no-ansi

# run entrypoint.sh
ENTRYPOINT ["/usr/src/app/entrypoint.sh"]

这是entrypoint.sh的内容:

#!/bin/sh

if [ "$DATABASE" = "postgres" ]
then
    echo "Waiting for postgres..."

    while ! nc -z $SQL_HOST $SQL_PORT; do
      sleep 0.1
    done

    echo "PostgreSQL started"
fi

python manage.py migrate

exec "$@"

详细解释

需要注意以下几点:

I have decide to use slim instead of alpine as tag for the python image because even though alpine images are supposed to reduce the size of Docker images and speed up the build, with Python, you can actually end up with a bit larger image and that takes a while to build (read this article for more info). Using this configuration builds containers faster than using the alpine image because I do not need to add some extra packages to install Python packages properly. I am installing poetry directly from the URL provided in the documentation. I am aware of the warnings provided by sobolevn. However, I consider that it is better in the long term to use the lates version of poetry by default than relying on an environment variable that I should update periodically. Updating the environment variable PATH is crucial. Otherwise, you will get an error saying that poetry was not found. Dependencies are installed directly in the python interpreter of the container. It does not create poetry to create a virtual environment before installing the dependencies.

如果你需要这个Dockerfile的alpine版本:

FROM python:alpine

# Keeps Python from generating .pyc files in the container
ENV PYTHONDONTWRITEBYTECODE 1
# Turns off buffering for easier container logging
ENV PYTHONUNBUFFERED 1

# Install dev dependencies
RUN apk update \
    && apk add curl postgresql-dev gcc python3-dev musl-dev openssl-dev libffi-dev

# Install poetry
RUN pip install -U pip \
    && curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
ENV PATH="${PATH}:/root/.poetry/bin"

WORKDIR /usr/src/app
COPY . .
RUN poetry config virtualenvs.create false \
  && poetry install --no-interaction --no-ansi

# run entrypoint.sh
ENTRYPOINT ["/usr/src/app/entrypoint.sh"]

注意，alpine版本需要一些依赖关系postgresql-dev gcc python3-dev musl-dev openssl-dev libffi-dev才能正常工作。

使用docker多阶段构建和python slim image，将诗词锁导出到requirements.txt，然后在virtualenv中通过pip安装。

它有最小的尺寸，不需要诗在运行时的形象，钉的版本一切。

FROM python:3.9.7 as base
ENV PIP_DISABLE_PIP_VERSION_CHECK=1
WORKDIR /app

FROM base as poetry
RUN pip install poetry==1.1.12
COPY poetry.lock pyproject.toml /app/
RUN poetry export -o requirements.txt

FROM base as build
COPY --from=poetry /app/requirements.txt /tmp/requirements.txt
RUN python -m venv .venv && \
    .venv/bin/pip install 'wheel==0.36.2' && \
    .venv/bin/pip install -r /tmp/requirements.txt

FROM python:3.9.7-slim as runtime
ENV PIP_DISABLE_PIP_VERSION_CHECK=1
WORKDIR /app
ENV PATH=/app/.venv/bin:$PATH
COPY --from=build /app/.venv /app/.venv
COPY . /app

下面是一个剥离的例子，其中首先是一个带有依赖关系的层(仅在这些依赖关系发生变化时构建)，然后将一个带有完整源代码的层添加到图像中。将poetry设置为安装到全局站点包中会留下一个配置工件，该配置工件也可以被删除。

FROM python:alpine

WORKDIR /app

COPY poetry.lock pyproject.toml ./
RUN pip install --no-cache-dir --upgrade pip \
 && pip install --no-cache-dir poetry \
 \
 && poetry config settings.virtualenvs.create false \
 && poetry install --no-dev \
 \
 && pip uninstall --yes poetry \

COPY . ./

我看到这里所有的答案都是用pip的方式安装诗词，以避免版本问题。 如果定义为安装最合适的版本，则安装诗歌的官方方法是读取poeetry_version env变量。

在github上有一个问题，我认为这张票的解决方案非常有趣:

# `python-base` sets up all our shared environment variables
FROM python:3.8.1-slim as python-base

    # python
ENV PYTHONUNBUFFERED=1 \
    # prevents python creating .pyc files
    PYTHONDONTWRITEBYTECODE=1 \
    \
    # pip
    PIP_NO_CACHE_DIR=off \
    PIP_DISABLE_PIP_VERSION_CHECK=on \
    PIP_DEFAULT_TIMEOUT=100 \
    \
    # poetry
    # https://python-poetry.org/docs/configuration/#using-environment-variables
    POETRY_VERSION=1.0.3 \
    # make poetry install to this location
    POETRY_HOME="/opt/poetry" \
    # make poetry create the virtual environment in the project's root
    # it gets named `.venv`
    POETRY_VIRTUALENVS_IN_PROJECT=true \
    # do not ask any interactive question
    POETRY_NO_INTERACTION=1 \
    \
    # paths
    # this is where our requirements + virtual environment will live
    PYSETUP_PATH="/opt/pysetup" \
    VENV_PATH="/opt/pysetup/.venv"


# prepend poetry and venv to path
ENV PATH="$POETRY_HOME/bin:$VENV_PATH/bin:$PATH"


# `builder-base` stage is used to build deps + create our virtual environment
FROM python-base as builder-base
RUN apt-get update \
    && apt-get install --no-install-recommends -y \
        # deps for installing poetry
        curl \
        # deps for building python deps
        build-essential

# install poetry - respects $POETRY_VERSION & $POETRY_HOME
RUN curl -sSL https://raw.githubusercontent.com/sdispater/poetry/master/get-poetry.py | python

# copy project requirement files here to ensure they will be cached.
WORKDIR $PYSETUP_PATH
COPY poetry.lock pyproject.toml ./

# install runtime deps - uses $POETRY_VIRTUALENVS_IN_PROJECT internally
RUN poetry install --no-dev


# `development` image is used during development / testing
FROM python-base as development
ENV FASTAPI_ENV=development
WORKDIR $PYSETUP_PATH

# copy in our built poetry + venv
COPY --from=builder-base $POETRY_HOME $POETRY_HOME
COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH

# quicker install as runtime deps are already installed
RUN poetry install

# will become mountpoint of our code
WORKDIR /app

EXPOSE 8000
CMD ["uvicorn", "--reload", "main:app"]


# `production` image used for runtime
FROM python-base as production
ENV FASTAPI_ENV=production
COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH
COPY ./app /app/
WORKDIR /app
CMD ["gunicorn", "-k", "uvicorn.workers.UvicornWorker", "main:app"]