prind

prind allows you to run the Software for your 3D Printer in Docker containers.
With a single Command, you can start up klipper and choose between multiple Frontends.

Currently supported Frontends:

• Octoprint (via Dockerhub)
• Fluidd (via Dockerhub)
• Mainsail (via GHCR)
• KlipperScreen

Depending on which Frontend you've chosen, moonraker will also be deployed.

Getting started

The following Guide requires docker and docker compose on your machine.
Follow the official Guides on how to get them up and running.

• https://docs.docker.com/engine/install/ubuntu/
• https://docs.docker.com/compose/cli-command/#installing-compose-v2

Build the MCU Code

Before using Klipper, you'll have to build and flash the microcontroller-code for your printers mainboard.
As this can be accomplished via docker, we can create an alias that replaces make with the appropriate docker compose command. After setting this alias, follow the Instructions on finding your printer, building and flashing the microcontroller found in the Klipper Docs.

Adapted from the official Docs, a generic Build would look like this.

alias make="docker compose -f docker-compose.extra.make.yaml run --rm make"

make menuconfig
make
make flash FLASH_DEVICE=/dev/serial/by-id/<my printer>

If your Board can be flashed via SD-Card, you may want to omit make flash and retrieve the klipper.bin from the out directory that is created by make. Follow your boards instructions on how to proceed with flashing via SD-Card.

Add your Configuration to docker-compose.override.yaml

Locate the klipper Service within docker-compose.override.yaml and update the device Section with the Serial Port of your Printer.
In this example, the Printer is using device /dev/ttymxc3.

  klipper:
    devices:
      - /dev/ttymxc3:/dev/ttymxc3

Locate the webcam Service within docker-compose.override.yaml and update the device Section with the Device Name of your Webcam.
In this example, the Webcam is using device /dev/video0. Do not edit any other lines.

  webcam:
    <<: *ustreamer-svc
    devices:
      - /dev/video0:/dev/webcam
    labels:
      - "traefik.enable=true"
      - "traefik.http.services.webcam.loadbalancer.server.port=8080"
      - "traefik.http.routers.webcam.rule=PathPrefix(`/webcam`)"
      - "traefik.http.routers.webcam.entrypoints=web"
      - "traefik.http.middlewares.webcam.stripprefix.prefixes=/webcam"
      - "traefik.http.routers.webcam.middlewares=webcam"

Configuring Klipper/Moonraker

All Runtime Configs are stored within config of this Repo.

• Update config/printer.cfg with your Klipper config, make sure to not remove the existing Macros as they are required by fluidd/mainsail. See Klipper3d Docs for Reference
• Make sure to update cors_domains and trusted_clients within moonraker.cfg to secure your moonraker api from unwanted access. See Moonraker Docs for Reference

Starting the stack

Currently, there are 3 Profiles to choose from, depending on the Web Frontend you'd like to use.

• fluidd
• mainsail
• octoprint

Starting the stack comes down to:

docker compose --profile <profile> up -d

e.g.

docker compose --profile fluidd up -d

Switching between profiles requires the whole stack to be torn down before starting another Frontend.
Running two Frontends at the same time is currently not supported. Switching from fluidd to mainsail would look like this:

docker compose --profile fluidd down
docker compose --profile mainsail up -d

Additional Profiles

KlipperScreen

KlipperScreen by jordanruthe can be enabled via the klipperscreen Profile.

It requires a X11 Server on your machine that the Container can connect to.
Locate the setup Script for X11 within scripts/ and run it from the root directory of this repository as user root. It creates a User, installs and configures X11 and creates a Systemd Service for xinit.

cd prind/
./scripts/setup-X11.sh

The Prind Logo should now be displayed on your screen.
If this is not the case, check the scripts output for errors.
Otherwise, proceed to start/update the Stack.

docker compose --profile fluidd --profile klipperscreen up -d

Moonraker-Telegram-Bot

moonraker-telegram-bot by nlef can be enabled via the moonraker-telegram-bot Profile

Add your bot_token and chat_id to config/telegram.conf.
See the configuration reference for further configuration Options.

docker compose --profile mainsail --profile moonraker-telegram-bot up -d

Updating

Images are built daily and tagged with latest and the first seven chars of the commit-sha of the remote repo. Example:

• mkuf/klipper:latest
• mkuf/klipper:a33d069

The latest Tag will point to a new Image within 24h.
The SHA-Tag a33d069 will remain and refers to Klipper3d/klipper:a33d069

Updating can be handled via docker-compose.
docker-compose.yaml uses latest tags for all Images contained in this Repository.
Compose will download all current Images and replace them when starting the stack again.

docker compose pull
docker compose --profile <profile> up -d

Advanced Topics

Input Shaper Calibration

Note:

Running a host_mcu process on a RaspberryPi to access its GPIO pins is currently not possible when running in Docker. Feel free to contribute if you have a Solution for this.

Using input shaper requires an accelerometer that is directly connected to your printers mainboard. Follow the Docs on Measuring Resonances, to set up your Printer accordingly.

After running TEST_RESONANCES or SHAPER_CALIBRATE, Klipper generates csv output in /tmp. To further analyze this data, it has to be extracted from the running klipper container.

mkdir ./resonances

docker compose exec klipper ls /tmp
  resonances_x_20220708_124515.csv  resonances_y_20220708_125150.csv

docker compose cp klipper:/tmp/resonances_x_20220708_124515.csv ./resonances/
docker compose cp klipper:/tmp/resonances_y_20220708_125150.csv ./resonances/

docker-compose.extra.calibrate-shaper.yaml is set up to run calibrate_shaper.py, so any options supported by the script can also be used with the container. Set an alias to save yourself from typing the the docker compose command multiple times. The generated Images are located besides the csv files in ./resonances

alias calibrate_shaper="docker compose -f docker-compose.extra.calibrate-shaper.yaml run --rm calibrate_shaper"

calibrate_shaper resonances_x_20220708_124515.csv -o cal_x.png
  [...]
  Recommended shaper is ei @ 90.2 Hz

calibrate_shaper resonances_y_20220708_125150.csv -o cal_y.png
  [...]
  Recommended shaper is mzv @ 48.2 Hz

Change Execution Options

The Entrypoint for all Docker Images within this Repo are the actual Applications, which are run at container execution time.
This makes it possible to set command line Arguments for the Apps as Docker Command.
Within docker-compose.yaml commands are already set, you may override them within docker-compose.override.yaml to fit your needs. Example from service Klipper:

  command:
    - "-I"
    - "run/klipper.tty"
    - "-a"
    - "run/klipper.sock"
    - "cfg/printer.cfg"

Multiple Webcams

The Ustreamer Service is already templated to be easily reused for multi-webcam Setups.
To add a new Ustreamer Service, simply add the following snippet to docker-compose.override.yaml.
Notice, that all service names, container names and traefik labels need to be unique while the right side of the passed Device (:/dev/webcam) always stays the same. Hence replace webcam2 with webcam3 and so on for every webcam you add and update the physical device that gets passed to the container.

  webcam2:
    <<: *ustreamer-svc
    devices:
      - /dev/video1:/dev/webcam
    labels:
      org.prind.service: webcam2
      traefik.enable: true
      traefik.http.services.webcam2.loadbalancer.server.port: 8080
      traefik.http.routers.webcam2.rule: PathPrefix(`/webcam2`)
      traefik.http.routers.webcam2.entrypoints: web
      traefik.http.middlewares.webcam2.stripprefix.prefixes: /webcam2
      traefik.http.routers.webcam2.middlewares: webcam2

Building Docker images locally

If you'd like to customize the provided Docker Images, you may edit the Dockerfiles within the docker/<service> Directory.
Images are build in multiple stages, the final stage is called run. Based on this, you can update Service definitions within docker-compose.override.yaml to build Images locally.

Example: Build Moonraker
Update the image: name and add a build config:

  moonraker:
    image: moonraker:latest
    build:
      context: docker/moonraker
      target: run

Enable Mainsail remoteMode

In case Moonraker is not situated on the same Host as Mainsail, you'll have to enable remoteMode in Mainsail to set up a remote Printer. This mirrors the behaviour of https://my.mainsail.xyz.

1. Create config/mainsail.json with the following Contents

{
    "remoteMode":true
}

2. Add the newly created File as a Volume to the mainsail Service

  mainsail:
    volumes:
      - ./config/mainsail.json:/usr/share/nginx/html/config.json

Debugging the Stack

Debugging the Stack without printer hardware is challenging, as klipper requires a mcu to operate.
For this purpose, you can build a service that emulates a mcu with simulavr, as suggested by the Klipper Docs.

The simulavr Image is part of the Dockerfile for Klipper but is not pushed to any registry, so it needs to be built when needed.

Locate the docker-compose.extra.simulavr.yaml in the repository and set the VERSION Build-Arg to any Git Reference from Klipper3d/klipper that you would like the mcu code to be compatible with.

This example builds the mcu code from Klipper3d/klipper:d75154d

    build:
      context: docker/klipper
      target: build-simulavr
      args: 
        VERSION: d75154d695efb1338cbfff061d226c4f384d127b

Then start the Stack

docker compose \
  --profile mainsail \
  -f docker-compose.yaml \
  -f docker-compose.extra.simulavr.yaml \
  up -d