Example of integrating Poetry with Docker leveraging multi-stage builds.

Michael Oliver

Last update: Dec 27, 2022

Overview

Poetry managed Python FastAPI application with Docker multi-stage builds

This repo serves as a minimal reference on setting up docker multi-stage builds with poetry

Requirements

NOTE - Run all commands from the project root

Local development

Poetry

Create the virtual environment and install dependencies with:

    poetry install

See the poetry docs for information on how to add/update dependencies.

Run commands inside the virtual environment with:

    poetry run <your_command>

Spawn a shell inside the virtual environment with

    poetry shell

Start a development server locally

    poetry run uvicorn app.main:app --reload --host localhost --port 8000

API will be available at localhost:8000/

Swagger docs at localhost:8000/docs

To run testing/linting locally you would execute lint/test in the scripts directory.

Docker

Build images with:

    docker build --tag poetry-project --file docker/Dockerfile .

The Dockerfile uses multi-stage builds to run lint and test stages before building the production stage. If linting or testing fails the build will fail.

You can stop the build at specific stages with the --target option:

    docker build --name poetry-project --file docker/Dockerfile . --target <stage>

For example we wanted to stop at the test stage:

    docker build --tag poetry-project --file docker/Dockerfile --target test .

We could then get a shell inside the container with:

    docker run -it poetry-project:latest bash

If you do not specify a target the resulting image will be the last image defined which in our case is the 'production' image.

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Comments

Broken Dockerfile example

Sample code

# Dockerfile
# Uses multi-stage builds requiring Docker 17.05 or higher
# See https://docs.docker.com/develop/develop-images/multistage-build/

# Creating a python base with shared environment variables
FROM python:3.10-slim as python-base
ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1 \
    PIP_NO_CACHE_DIR=off \
    PIP_DISABLE_PIP_VERSION_CHECK=on \
    PIP_DEFAULT_TIMEOUT=100 \
    POETRY_HOME="/opt/poetry" \
    POETRY_VIRTUALENVS_IN_PROJECT=true \
    POETRY_NO_INTERACTION=1 \
    PYSETUP_PATH="/opt/pysetup" \
    VENV_PATH="/opt/pysetup/.venv"

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


# builder-base is used to build dependencies
FROM python-base as builder-base
RUN apt-get update \
    && apt-get install --no-install-recommends -y \
        curl \
        build-essential

# Install Poetry - respects $POETRY_VERSION & $POETRY_HOME
ENV POETRY_VERSION=1.2
RUN curl -sSL https://raw.githubusercontent.com/sdispater/poetry/master/get-poetry.py | python

# We copy our Python requirements here to cache them
# and install only runtime deps using poetry
WORKDIR $PYSETUP_PATH
COPY ./poetry.lock ./pyproject.toml ./
RUN poetry install --no-dev  # respects


# 'development' stage installs all dev deps and can be used to develop code.
# For example using docker-compose to mount local volume under /app
FROM python-base as development
COPY --from=builder-base $POETRY_HOME $POETRY_HOME
COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH

# venv already has runtime deps installed we get a quicker install
WORKDIR $PYSETUP_PATH
RUN poetry install

WORKDIR /app
COPY . .


FROM python-base as production
COPY --from=builder-base $VENV_PATH $VENV_PATH
COPY ./app /app
WORKDIR /app

Result

 > [builder-base 5/5] RUN poetry install --no-dev  # respects:
#10 0.383 /bin/sh: 1: poetry: not found

opened by AIGeneratedUsername 1