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A few assumptions are that you have a tool that extracts some kind of metadata from a file or dataset and that you have installed Python, Git, and Docker as well as any other specific software needed by your extractor (if any) on your computer.
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Install pyClowder2, which is a Python library that helps to easily communicate with Clowder - the backend services service of Brown Dog which handles extractions. The advantage of using this library is that it manages all communications with Clowder and RabbitMQ (the distributed messaging bus) and the developer doesn't have to take care of such tasks. Needless to say, an extractor can also be written in native Python without the use of pyClowder2, but it would could be more time consuming.
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pip install git+https://opensource.ncsa.illinois.edu/stashbitbucket/scm/cats/pyclowderpyclowder2.git |
2. Get Your Code Together
We have developed a template extractor written in Python. It is a simple wordcount word count extractor that counts lines, words, and characters in a text file. Clone the template extractor and rename the directory to an appropriate name that reflects the purpose of your extractor.
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