这是最适合我的最小配置:

FROM python:3.7

ENV PIP_DISABLE_PIP_VERSION_CHECK=on

RUN pip install poetry

WORKDIR /app
COPY poetry.lock pyproject.toml /app/

RUN poetry config virtualenvs.create false
RUN poetry install --no-interaction

COPY . /app

注意，它不像@sobolevn的配置那样安全。

作为一个小问题，我将补充一下pyproject是否可以进行可编辑安装。Toml项目，可以删除一两行:

FROM python:3.7

ENV PIP_DISABLE_PIP_VERSION_CHECK=on

WORKDIR /app
COPY poetry.lock pyproject.toml /app/

RUN pip install -e .

COPY . /app

在将诗歌与docker一起使用时，有几件事需要记住。

安装

安装诗歌的官方方式是:

curl -sSL https://install.python-poetry.org | python3 -

这种方式允许诗歌及其依赖从你的依赖中分离出来。但是，在我看来，这不是一件很好的事情，有两个原因:

诗歌版本可能会得到更新，它会破坏你的构建。在这种情况下，您可以指定poeetry_version环境变量。安装程序将尊重它 我不喜欢在没有任何保护措施的情况下，将来自互联网的文件传输到我的容器中

所以，我使用pip安装'poetry==$ poeetry_version '。如您所见，我仍然建议固定您的版本。

另外，把这个版本固定在pyproject中。Toml也是:

[build-system]
# Should be the same as `$POETRY_VERSION`:
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

它将保护您避免本地和docker环境之间的版本不匹配。

缓存的依赖关系

我们想要缓存我们的需求，并且只在pyproject时重新安装它们。汤姆或诗歌。锁定文件更改。否则构建会很慢。为了实现工作缓存层，我们应该放:

COPY poetry.lock pyproject.toml /code/

在安装诗词之后，但在添加任何其他文件之前。

Virtualenv

接下来要记住的是virtualenv创建。我们在docker中不需要它。它已经被孤立了。因此，我们使用诗意配置virtualenvs。创建假设置关闭它。

开发vs生产

如果你像我一样使用相同的Dockerfile进行开发和生产，你将需要根据一些环境变量安装不同的依赖集:

poetry install $(test "$YOUR_ENV" == production && echo "--no-dev")

通过这种方式，$YOUR_ENV将控制将安装哪些依赖集:all(默认)或仅生产带有——no-dev标志。

你可能还想添加一些更好的体验选项:

——无互动不要问任何互动问题 ——no-ansi标志，使您的输出更日志友好

结果

你会得到类似的结果:

FROM python:3.6.6-alpine3.7

ARG YOUR_ENV

ENV YOUR_ENV=${YOUR_ENV} \
  PYTHONFAULTHANDLER=1 \
  PYTHONUNBUFFERED=1 \
  PYTHONHASHSEED=random \
  PIP_NO_CACHE_DIR=off \
  PIP_DISABLE_PIP_VERSION_CHECK=on \
  PIP_DEFAULT_TIMEOUT=100 \
  POETRY_VERSION=1.0.0

# System deps:
RUN pip install "poetry==$POETRY_VERSION"

# Copy only requirements to cache them in docker layer
WORKDIR /code
COPY poetry.lock pyproject.toml /code/

# Project initialization:
RUN poetry config virtualenvs.create false \
  && poetry install $(test "$YOUR_ENV" == production && echo "--no-dev") --no-interaction --no-ansi

# Creating folders, and files for a project:
COPY . /code

你可以在这里找到一个真实的例子:weakake -django-template

2019年12月17日更新

将诗歌更新到1.0

2022-11-24更新

更新curl命令使用现代诗歌安装脚本

这是最适合我的最小配置:

FROM python:3.7

ENV PIP_DISABLE_PIP_VERSION_CHECK=on

RUN pip install poetry

WORKDIR /app
COPY poetry.lock pyproject.toml /app/

RUN poetry config virtualenvs.create false
RUN poetry install --no-interaction

COPY . /app

注意，它不像@sobolevn的配置那样安全。

作为一个小问题，我将补充一下pyproject是否可以进行可编辑安装。Toml项目，可以删除一两行:

FROM python:3.7

ENV PIP_DISABLE_PIP_VERSION_CHECK=on

WORKDIR /app
COPY poetry.lock pyproject.toml /app/

RUN pip install -e .

COPY . /app

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/

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。

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"]