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1. Create a local project from the template:

   Code Block
   language bash
   git clone http://bitbucket.ncsa.illinois.edu/path/to/extractor-template.git myextractor

   Note: If the user downloads the docker-extractor bare image, it is not required to git clone the template project. The docker-extractor image should have that extractor template project.

2. Developer creates and activates a python virtual environment for their new project.

   1. Code Block
      language bash
      virtualenv myextractor source myextractor/bin/activate pip install docker-compose

3. Developer runs "docker-compose up" to start runtime environment of docker containers (TODO: docker-compose.yml for extractor runtime environment) (TODO: docker-compose.yml for converter runtime environment) (TODO: Create any missing Docker containers)

   1. Code Block
      language bash
      cd myextractor docker-compose up ./run-tests.py (or something like that)

   2. Runtime containers for extractors: Clowder instance
   3. Runtime containers for converters: Polyglot instance
      
      
4. Alternatively, to Step (3-4), Developer looks for docker-extractor or docker-converter to start with  and for writing interface script for new tools.  
   1. Example docker extractors and converters are there in  (https://opensource.ncsa.illinois.edu/bitbucket/projects/BD/repos/dockerfiles/browse) 
   2. TODO: use those as reference to create an image for basic Create an repository for a template docker-extractor and a template docker-converter. 
   3. While  While creating basic docker image for extractor, the template project should consists of  interface scripts with comments where to modify the code ( Follow Step 3-4, within a docker container). 
   4. upload the image to dockerhub and create dockerfile and README and upload to the repository. 
   5. Include these template docker-images in the docker-compose.yml file for setting up the runtime-environment for developer to enable start writing custom scripts.

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