你能给我一个Dockerfile的例子吗?我可以在其中安装所有我需要的软件包。锁定和pyproject。toml到我的镜像/容器从Docker?
当前回答
多阶段Docker构建与诗歌和venv
不要禁用virtualenv创建功能。virtualenv在Docker构建中发挥了作用，因为它们提供了一种优雅的方式来利用多阶段构建。简而言之，构建阶段将所有内容安装到virtualenv中，而最后阶段只是将virtualenv复制到一个小映像中。
在复制代码之前，先使用诗歌导出并安装固定的需求。这将允许您使用Docker构建缓存，并且永远不会因为更改代码中的一行而重新安装依赖项。
不要使用诗意安装来安装代码，因为它将执行可编辑的安装。相反，使用诗歌构建来构建一个轮子，然后将其安装到您的virtualenv中。(感谢PEP 517，这整个过程也可以通过简单的pip install .来执行，但由于构建隔离，您最终将安装另一个Poetry副本。)
下面是一个Dockerfile安装Flask应用到Alpine镜像的例子，它依赖于Postgres。本例使用入口点脚本激活virtualenv。但一般来说，没有入口点脚本也没问题，因为您可以在CMD指令中简单地引用/venv/bin/ Python的Python二进制文件。
Dockerfile
FROM python:3.7.6-alpine3.11 as base
ENV PYTHONFAULTHANDLER=1 \
PYTHONHASHSEED=random \
PYTHONUNBUFFERED=1
WORKDIR /app
FROM base as builder
ENV PIP_DEFAULT_TIMEOUT=100 \
PIP_DISABLE_PIP_VERSION_CHECK=1 \
PIP_NO_CACHE_DIR=1 \
POETRY_VERSION=1.0.5
RUN apk add --no-cache gcc libffi-dev musl-dev postgresql-dev
RUN pip install "poetry==$POETRY_VERSION"
RUN python -m venv /venv
COPY pyproject.toml poetry.lock ./
RUN poetry export -f requirements.txt | /venv/bin/pip install -r /dev/stdin
COPY . .
RUN poetry build && /venv/bin/pip install dist/*.whl
FROM base as final
RUN apk add --no-cache libffi libpq
COPY --from=builder /venv /venv
COPY docker-entrypoint.sh wsgi.py ./
CMD ["./docker-entrypoint.sh"]
docker-entrypoint.sh
#!/bin/sh
set -e
. /venv/bin/activate
while ! flask db upgrade
do
echo "Retry..."
sleep 1
done
exec gunicorn --bind 0.0.0.0:5000 --forwarded-allow-ips='*' wsgi:app
wsgi.py
import your_app
app = your_app.create_app()
其他回答
这是最适合我的最小配置:
FROM python:3.7
ENV PIP_DISABLE_PIP_VERSION_CHECK=on
RUN pip install poetry
WORKDIR /app
COPY poetry.lock pyproject.toml /app/
RUN poetry config virtualenvs.create false
RUN poetry install --no-interaction
COPY . /app
注意，它不像@sobolevn的配置那样安全。
作为一个小问题，我将补充一下pyproject是否可以进行可编辑安装。Toml项目，可以删除一两行:
FROM python:3.7
ENV PIP_DISABLE_PIP_VERSION_CHECK=on
WORKDIR /app
COPY poetry.lock pyproject.toml /app/
RUN pip install -e .
COPY . /app
多阶段Docker构建与诗歌和venv
不要禁用virtualenv创建功能。virtualenv在Docker构建中发挥了作用，因为它们提供了一种优雅的方式来利用多阶段构建。简而言之，构建阶段将所有内容安装到virtualenv中，而最后阶段只是将virtualenv复制到一个小映像中。
在复制代码之前，先使用诗歌导出并安装固定的需求。这将允许您使用Docker构建缓存，并且永远不会因为更改代码中的一行而重新安装依赖项。
不要使用诗意安装来安装代码，因为它将执行可编辑的安装。相反，使用诗歌构建来构建一个轮子，然后将其安装到您的virtualenv中。(感谢PEP 517，这整个过程也可以通过简单的pip install .来执行，但由于构建隔离，您最终将安装另一个Poetry副本。)
下面是一个Dockerfile安装Flask应用到Alpine镜像的例子，它依赖于Postgres。本例使用入口点脚本激活virtualenv。但一般来说，没有入口点脚本也没问题，因为您可以在CMD指令中简单地引用/venv/bin/ Python的Python二进制文件。
Dockerfile
FROM python:3.7.6-alpine3.11 as base
ENV PYTHONFAULTHANDLER=1 \
PYTHONHASHSEED=random \
PYTHONUNBUFFERED=1
WORKDIR /app
FROM base as builder
ENV PIP_DEFAULT_TIMEOUT=100 \
PIP_DISABLE_PIP_VERSION_CHECK=1 \
PIP_NO_CACHE_DIR=1 \
POETRY_VERSION=1.0.5
RUN apk add --no-cache gcc libffi-dev musl-dev postgresql-dev
RUN pip install "poetry==$POETRY_VERSION"
RUN python -m venv /venv
COPY pyproject.toml poetry.lock ./
RUN poetry export -f requirements.txt | /venv/bin/pip install -r /dev/stdin
COPY . .
RUN poetry build && /venv/bin/pip install dist/*.whl
FROM base as final
RUN apk add --no-cache libffi libpq
COPY --from=builder /venv /venv
COPY docker-entrypoint.sh wsgi.py ./
CMD ["./docker-entrypoint.sh"]
docker-entrypoint.sh
#!/bin/sh
set -e
. /venv/bin/activate
while ! flask db upgrade
do
echo "Retry..."
sleep 1
done
exec gunicorn --bind 0.0.0.0:5000 --forwarded-allow-ips='*' wsgi:app
wsgi.py
import your_app
app = your_app.create_app()
我的python应用程序的Dockerfile看起来像这样-
FROM python:3.10-alpine
RUN apk update && apk upgrade
RUN pip install -U pip poetry==1.1.13
WORKDIR /app
COPY . .
RUN poetry export --without-hashes --format=requirements.txt > requirements.txt
RUN pip install -r requirements.txt
EXPOSE 8000
ENTRYPOINT [ "python" ]
CMD ["main.py"]
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"]
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