I’ve been a long-time user of Poetry for my Python projects, and it’s been a welcome change. However, my recent exploration into Hatch has sparked my interest.
Poetry simplifies dependency management with its unified pyproject.toml, but Hatch excels in scenarios requiring complex workflows.
A common personal use-case is Docker multi-stage builds. Hatch, with its conventional requirements.txt and setup.py, offers more granular control, making complex configurations easier.
Hatch also aligns closely with the existing Python ecosystem due to its use of traditional setup files, linking old with new workflows, ensuring a better integration.
For instance, if using a container image manifest such as
# Use a base Python image
FROM python:3.9-slim as base
# Set up a working directory
WORKDIR /app
# Copy requirements and install dependencies
COPY requirements.txt .
RUN pip install -r requirements.txt
# Copy the rest of the application
COPY . .
# Other Docker configurations...
Whereas with Poetry, you might need to install it within the Docker image and use poetry export to generate a requirements.txt equivalent, with Hatch, since it supports the traditional requirements.txt, integration with multi-stage builds can be simpler.