Dockerizing Hatchet Applications

This guide explains how to create Dockerfiles for Hatchet applications, focusing on both Poetry and PIP implementations. Hatchet workers need proper containerization to ensure reliable execution of workflows in production environments.

Entry Point Configuration for Hatchet

Before creating your Dockerfile, understand that Hatchet workers require specific entry point configuration:

The entry point must run code that runs the Hatchet worker. This can be done by calling the worker.start() method. See the Python SDK docs for more information
Proper environment variables must be set for Hatchet SDK
The worker should be configured to handle your workflows using the worker.register method

Example Docker Files

# Use the official Python image as the base
FROM python:3.10-slim
 
# Set environment variables
 
ENV PYTHONUNBUFFERED=1 \
 POETRY_VERSION=1.4.2 \
 HATCHET_ENV=production
 
# Install system dependencies and Poetry
 
RUN apt-get update && \
 apt-get install -y curl && \
 curl -sSL https://install.python-poetry.org | python3 - && \
 ln -s /root/.local/bin/poetry /usr/local/bin/poetry && \
 apt-get clean && \
 rm -rf /var/lib/apt/lists/\*
 
# Set work directory
 
WORKDIR /app
 
# Copy dependency files first
 
COPY pyproject.toml poetry.lock\* /app/
 
# Install dependencies
 
RUN poetry config virtualenvs.create false && \
 poetry install --no-interaction --no-ansi
 
# Copy Hatchet application code
 
COPY . /app
 
# Set the entrypoint to run the Hatchet worker
 
CMD ["poetry", "run", "python", "worker.py"]

If you're using a poetry script to run your worker, you can replace poetry run python worker.py with poetry run <script-name> in the CMD.

Scheduled Workflows Managed Compute