Slim down Python Docker image size with Poetry and Pip

Python package management can be tricky because the default package manager (pip) doesn’t track dependency versions like npm does for Node.js.

That’s why you should use poetry to manage Python packages. It creates a lock file, so you can be sure that the versions will be the same every time you reinstall.

However, this can be a challenge when you want to create a Docker image with poetry. You need to do an extra pip install poetry (unless you include it in your base Python image). Also, using poetry to install packages can result in a larger Docker image size.

Dockerfiles

Here are the Dockerfiles I use to compare using poetry and pip:

Dockerfile.poetry

FROM python:3.12-slim
 
WORKDIR /app
 
# hadolint ignore=DL3013
RUN pip install --no-cache-dir poetry
 
COPY pyproject.toml .
COPY poetry.lock .
 
RUN poetry install --only main --no-root --no-directory

Dockerfile.pip

FROM python:3.12-slim
 
WORKDIR /app
 
COPY requirements.txt .
RUN pip install -r requirements.txt --no-cache-dir

Installed packages

requests = "^2.31.0"
polars = "^0.20.18"
fastapi = "^0.110.1"
pydantic = "^2.6.4"
python-dotenv = "^1.0.1"
langchain = "^0.1.14"
psycopg2-binary = "^2.9.9"

Result

The resulting image sizes are:

benchmark_poetry      latest            23d3105ad0dd   11 seconds ago   520MB
benchmark_pip         latest            b7932a02a8d1   12 hours ago     388MB

As you can see, using poetry makes the image 132 MB larger. If you deploy 12 times per month, that’s an extra 1584 MB.

Even though storage is cheap these days, reducing image sizes can still be helpful! 😎

Reference