Python package management is not straightforward, seeing default package manager (pip) does not behave like node’s npm, in a sense that it doesn’t track dependencies versions.

This is why you should use poetry to manage python packages, since it creates a lock file, so you can be sure that on every re-install, the versions would be the same.

However, this poses a challenge when you want to create a docker image with poetry, because you need to do an extra pip install poetry (unless you bake this into your base python image). Additionally, turns out using poetry to install packages results in larger docker image size.


Below are dockerfiles I use to compare between using poetry and pip:


FROM python:3.12-slim


# 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


FROM python:3.12-slim


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"


And the resulting image size is:

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. Let’s say you deploy 12 times per month, that’s extra 1584 MB.

While I agree that these days storage is cheap, reducing images size here and there won’t hurt 😎.