Installation

Anaconda provides an enterprise-ready data analytics platform that empowers companies to adopt a modern open data science analytics architecture.

The Mission Support Web Map Service (mss) is available as anaconda package on the channel.

conda-forge

This channel conda-forge has builds for osx-64, linux-64, win-64

The conda-forge github organization uses various automated continuos integration build processes.

We provide an automatic installation and a manual installation.

Automatic Installation

  • For Windows, go here

    1. Right click on the webpage and select “Save as…” to download the file

    2. Double click the downloaded file and follow further instructions

    • For fully automatic installation, open cmd and execute it with /Path/To/Windows.bat -a

  • For Linux/Mac, go here

    1. Right click on the webpage and select “Save as…” to download the file

    2. Make it executable via chmod +x LinuxMac.sh

    3. Execute it and follow further instructions ./LinuxMac.sh

    • For fully automatic installation, run it with the -a parameter ./LinuxMac.sh -a

Manual Installation

To install MSS you need the conda installer or its drop-in replacement the mamba installer. We explain below how you get by the conda installer the mamba installer. Mamba is a fast cross platform installer.

The fastest way to get the conda installer is to start with Miniconda or Miniforge. This is a small subset of the Anaconda package with only the conda installer and its dependencies. If you do prefer to use over 7K open-source packages install Anaconda.

We recommend to install this for the local user. This does not require administrator permissions.

As Beginner start with an installation of Miniconda - Get Miniconda

If you are an Advanced User you know that Anaconda or Miniforge are compatible too.

Add the conda-forge channel

Please add the channel conda-forge to your defaults:

$ conda config --add channels conda-forge

The conda-forge channel must be on top of the list before the anaconda default channel.

Install

You must install mss into a new environment to ensure the most recent versions for dependencies (On the Anaconda Prompt on Windows, you have to leave out the ‘source’ here and below).

$ conda create -n mssenv mamba
$ conda activate mssenv
(mssenv) $ mamba install mss=7.0.8 python
(mssenv) $ msui

Update

Builtin Update

With 5.0 we provide a new feature for updating MSS by the UI or the command line After you started the MSS UI it informs you after a while if there is a new update available. From the command line you can trigger this update feature by

(mssenv) $ msui --update

Other Methods

For updating an existing MSS installation to the current version, it is best to install it into a new environment. If your current version is not far behind the new version you could try the mamba update mss as described.

Important

mamba is under development. All dependencies of MSS and MSS itselfs are under development. Sometimes this update feature of mamba can’t resolve from existing to new dependencies.

search for MSS what you can get

(mssenv) $ mamba search mss
...
mss                            7.0.6  py38h578d9bd_0  conda-forge
mss                            7.0.6  py39hf3d152e_0  conda-forge

compare what you have installed

(mssenv) $ mamba list mss

  mss                            7.0.2     py310hff52083_0    conda-forge

We have reports that often an update suceeds by using the install option and the new version number, in this example 7.0.8 and python as second option

(mssenv) $ mamba install mss=7.0.8 python

All attemmpts show what you get if you continue. Continue only if you get what you want.

The alternative is to use a new environment and install mss.

For further details of configurating mss Configuration of MSUI

Server based installation

For a wms server setup or mscolab setup you may want to have a dedicated user for the apache2 wsgi script. We suggest to create a mss user.

  • create a mss user on your system

  • login as mss user

  • create a src directory in /home/mss

  • cd src

  • get miniconda for Python 3

  • set execute bit on install script

  • execute script, enable environment in .bashrc

  • login again or export PATH=”/home/mss/miniconda3/bin:$PATH”

  • conda create -n mssenv mamba

  • conda activate mssenv

  • mamba install mss=7.0.8 python

For a simple test you could start the builtin standalone mswms and mscolab server:

$ mswms &
$ mscolab start

Point a browser for the verification of both servers installed on

Further details in the components section on http://mss.rtfd.io

Use Docker

You can use images from the docker hub. based on our repository

Build settings are based on the stable branch. Our openmss/mss:latest has any update in the stable branch.

You can start server and client by loading the image

$ xhost +local:docker
$ docker run -ti --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix --network host openmss/mss:latest  /bin/bash
$ /opt/conda/envs/mssenv/bin/msui &
$ /opt/conda/envs/mssenv/bin/mswms --port 80 &
$ /opt/conda/envs/mssenv/bin/mscolab start &
$ curl http://localhost/?service=WMS&request=GetCapabilities&version=1.1.1
$ curl http://localhost:8083/status

The WMS server initialized by demodata, and the mscolab server and the userinterface can be started by

$  xhost +local:docker
$  docker run -d -ti --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix --network host openmss/mss:latest MSS

If you want only to start the msui do this by

$  xhost +local:docker
$  docker run -d -ti --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix --network host openmss/mss:latest msui

Use Singularity

You can use images from the docker hub. based on our repository by converting them to singularity or build from our singularity definition

Build settings are based on the stable branch. Our openmss/mss:latest has any update in the stable branch.

You can start server and client by loading the image

$ host +
$ singularity build -f mss.sif Singularity.def
$ singularity shell mss.sif
$ Singularity > msui # starts the ui
$ Singularity > mswms_demodata --seed  # creates in your $HOME a mss/ folder with testdata
$ Singularity > export PYTHONPATH=$HOME/mss; mswms # starts the development server
$ Singularity > mscolab db --init; mscolab start # starts the mscolab development server