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+# MDStudio workflow
+
+[![Build Status](https://travis-ci.com/MD-Studio/MDStudio_workflow.svg?branch=master)](https://travis-ci.com/MD-Studio/MDStudio_workflow)
+[![Codacy Badge](https://api.codacy.com/project/badge/Grade/d66db06e8cb041f4b1cd90ace5d6ce69)](https://www.codacy.com/manual/marcvdijk/MDStudio_workflow?utm_source=github.com&utm_medium=referral&utm_content=MD-Studio/MDStudio_workflow&utm_campaign=Badge_Grade)
+[![codecov](https://codecov.io/gh/MD-Studio/MDStudio_workflow/branch/master/graph/badge.svg)](https://codecov.io/gh/MD-Studio/MDStudio_workflow)
+
+![Configuration settings](mdstudio-logo.png)
+
+MDStudio workflow is a Python based workflow engine developed for the MDStudio microservice environment. MDtudio 
+workfow makes it easy to construct complex workflows as DAGs (Directed Acyclic Graphs) combining calls to MDStudio
+microservices with Python scripts or even commandline tools.
+Examples on how to construct and use these workflows is provided in the [MDStudio_examples](https://github.com/MD-Studio/MDStudio_examples)
+repository on GitHub.
+
+## Installation Quickstart
+MDStudio workflow can be used in the MDStudio environment as (Docker) service or as stand-alone Python library.
+
+### Install option 1 Pre-compiled Docker container
+MDStudio propka can be installed quickly from a pre-compiled docker image hosted on DockerHub by:
+
+    docker pull mdstudio/mdstudio_workflow
+    docker run (-d) mdstudio/mdstudio_workflow
+
+In this mode you will first need to launch the MDStudio environment itself in order for the MDStudio workflow service to 
+connect to it. You can unify this behaviour by adding the MDStudio workflow service to the MDStudio service environment as:
+
+    MDStudio/docker-compose.yml:
+        
+        services:
+           mdstudio_workflow:
+              image: mdstudio/mdstudio_workflow
+              links:
+                - crossbar
+              environment:
+                - CROSSBAR_HOST=crossbar
+              volumes:
+                - ${WORKDIR}/mdstudio_workflow:/tmp/mdstudio/mdstudio_workflow
+
+And optionally add `mdstudio_workflow` to MDStudio/core/auth/settings.dev.yml for automatic authentication and 
+authorization at startup.
+
+### Install option 2 custom build Docker container
+You can custom build the MDStudio workflow Docker container by cloning the MDStudio_workflow GitHub repository and run:
+
+    docker build MDStudio_workflow/ -t mdstudio/mdstudio_workflow
+
+After successful build of the container follow the steps starting from `docker run` in install option 1.
+
+### Install option 3 standalone deployment of the service
+If you prefer a custom installation over a (pre-)build docker container you can clone the MDStudio_workflow GitHub
+repository and install `mdstudio_workflow` locally as:
+
+    pip install (-e) mdstudio_workflow/
+
+Followed by:
+
+    ./entry_point_mdstudio_workflow.sh
+
+or
+
+    export MD_CONFIG_ENVIRONMENTS=dev,docker
+    python -u -m mdstudio_workflow
+
+## Install option 4 use mdstudio_workflow as Python library
+Install the project as standalone library as described in option 3. Build workflows as Python scripts explained in the
+[MDStudio_examples](https://github.com/MD-Studio/MDStudio_examples) repository on GitHub.