l-mds
local-data-stack
Python

Slow & local data allows you to move fast and deliver business value for the 99.9% of the data challenges.

Last updated Jul 7, 2026
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README

local data stack template

This template brings together some of the best open-source tools in data engineering and Rust-based tooling for ensuring code quality:

  • dagster, dbt, duckdb
  • pixi
  • docker
  • ruff, pyright, taplo, pytest
  • cruft
While the stack runs locally, it's designed with scale in mind. Data and state accumulate over time (as data engineers say in partitions). Slow data - similar to slow food, is healthy and allows the fast delivery of business value efficiently.

The idea of slow data refers to:

  • focusing on the reduction of complexity
- allows to reduce complex data pipelines down to a single developers notebook - making complex data pipeliens testable
  • shipping real busines value fast
  • scaling as needed via partitions and a scalable resource provider
Featured

The template directly can be deployed via docker-compose. With only minimal adaptations you can instead deploy to kubernetes in any cloud provider.

Additionally included for secure handling of secrets:

  • sops
  • age

usage

Prerequisites:

  • git
  • an installation of cruft pip install cruft jinja2-ospath
  • an installation of pixi https://pixi.sh/latest/#installation curl -fsSL https://pixi.sh/install.sh | bash
  • text editor of choice such as vscode
  • docker
curl -fsSL https://pixi.sh/install.sh | bash
git clone https://github.com/l-mds/local-data-stack.git
cd local-data-stack
pixi run tpl-init-cruft

alternatively:

pip install cruft jinja2-ospath cruft create https://github.com/l-mds/local-data-stack.git

cd <<your project name>> git init git add . git commit -m "initial commit"

pixi update git commit -m "set dependencies"

git commit -m "reformatting" pixi run fmt

set dagster home to some directory

your logs and run results will be persistet there

mkdir /path/to/mydagsterhome export DAGSTERHOME=/path/to/mydagster_home

start the data stack

pixi run start-dev

Post install:

  • update the secrets in the .env files by executing: openssl rand -base64 32 and setting a suitable secret
  • ensure the .env.enc can be created by following the instructions in [documentation/secops]

Developing the template

To render an instance of the project:

pixi run render-dev

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