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1. Install prerequisite software. The install methods will depend on your operating system:
   
   1. VirtualBox (or an equivalent Docker-compatible virtualization environment)
   2. Docker
   3. Python and PIP
      

2. Clone this extractor template project from the repository, substituting your extractor project name:

   Code Block
   language bash
   git clone https://opensource.ncsa.illinois.edu/bitbucket/scm/bd/bd-templates.git <extractor project name>

3. Create and activate a Python virtual environment for their new project:
   

   1. Code Block
      language bash
      cd <extractor project name>/bd-extractor-templates virtualenv . source bin/activate pip install docker-compose

      NOTE: To activate this Python virtual environment in the future, repeat the "source bin/activate" step.

4. Start up the Extractor runtime environment using Docker Compose:
   

   1. TODO: docker-compose.yml for extractor runtime environment

      Code Block
      language bash
      docker-compose up ./tests.py

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[
  {
    "@context": {
      "bd": "http://browndogdts.ncsa.illinois.edu:9000/metadata/#",
      "@vocab" : "http://browndogdts.ncsa.illinois.edu:9000/extractors/ncsa.cv.caltech101"
    },
    "bd:created_at": "Mon Mar 07 09:30:14 CST 2016",
    "bd:agent": {
      "@type": "cat:extractor",
      "bd:name": "ncsa.cv.caltech101",
      "bd:extractor_id@id": "http://browndogdts.ncsa.illinois.edu:9000/api/extractors/ncsa.cv.caltech101"
    },
    "bd:content": {
		"@id": "https://dts-dev.ncsa.illinois.edu/files/938373748293",
		"basic_caltech101_score": [
        "-0.813741"
      ],
      "basic_caltech101_category": [
        "BACKGROUND_Google"
      ]
    }
  }
]

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