The Brown Dog DTS is a highly extensible/distributed service providing a uniform means of managing and accessing transformation capabilities within the web. Utilized tools can come in the form of command line applications, GUI driven applications, libraries, and/or other services. Here we go over the process of preparing a new transformation tool for usage with the DTS.
Deploying an Extractor from a Single Call Method
Here is described the entire process for taking a working piece of code and deploying it as a Brown Dog Extractor. It is assumed that the method can be invoked from a single call. In this example, we are using the python extractor wrapper and will invoke a python function. In a very similar fashion, a method developed in a language other than python can be invoked using subprocess.
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- Dockerize the extractor
- Deploy the extractor
- Add the extractor to the tool catalog
Creating an Extractor from Working Python Code
In this section, we will describe the process of creating of an extractor from a working Python code. A few assumptions are that you have a working Python code that extracts some kind of metadata from a data file and that you have installed Python, Git, Python virtual environment, and Docker and other specific software needed by your extractor (if any) in your computer.
Install pyClowder, which is a Python library that helps to easily communicate with Clowder - one of the backend services of Brown Dog. The advantage of using this library is that it manages all communications with Clowder and RabbitMQ (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 pyClowder, but it would be more time consuming.
Code Block theme Confluence pip install git+https://opensource.ncsa.illinois.edu/stash/scm/cats/pyclowder.git
Get your code together
We have developed a template or example extractor written in Python. It is a simple wordcount 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 extractorCode Block theme Confluence git clone https://opensource.ncsa.illinois.edu/bitbucket/scm/bd/extractors-template.git mv extractors-template/ <your_extractor_name> cd <your_extractor_name>
Bring in your working python code. Make changes to extractors.py (main program). Consider process_file method as the main method of an extractor and accordingly it needs to contain the main logic. You can call other methods in your python code from this method after importing necessary modules into this file.Edit extractor configuration file config.py:
Change the rabbitmq queue name - in this case replace "wordCount" with an appropriate name for your extractor
- Change the messageType field to reflect the MIME type(s) of the file for which you are writing the extractor
- Update other fields like rabbitmqURL, rabbitmqExchange, sslVerify, to include
- If your extractor needs other custom parameters, they need to be added to config.py
- Edit extractor.info.json
This file contains metadata about the extractor in JSON-LD format. Update all relevant fields as needed. Update Dockerfile
To install your software dependencies, provide necessary instructions in Dockerfile using the RUN command. You will need to add a line in Dockerfile to switch to the root user (USER root
) for getting proper permissions. For e.g., to install ImageMagick package using apt-get, add the following commands to Dockerfile:Code Block theme Confluence USER root RUN apt-get update && apt-get install -y imagemagick
Test Docker
Code Block theme Confluence docker-compose up -d docker build -t <your_extractor_name> . docker run --rm -i -t --link <your_extractor_name_with_only_alphabets>_rabbitmq_1:rabbitmq <your_extractor_name>
You should see the following in the terminal. This means that the extractor is running and waiting for messages:
Code Block theme Confluence INFO : pyclowder.extractors - Waiting for messages. To exit press CTRL+C
Creating a Converter
In this section, we describe the creation of a converter using the image converter written using ImageMagick.
Get the template converter code.
We have developed a template or example converter. It is a simple image converter that images between different formats using ImageMagick tool. Clone the template converter and rename the directory to an appropriate name that reflects the purpose of your converterCode Block theme Confluence git clone https://opensource.ncsa.illinois.edu/bitbucket/scm/bd/convertors-template.git mv convertors-template/ <your_converter_name> cd <your_converter_name>
- Rename and edit ImageMagick_convert.sh script to wrap your converter logic. This script file should be named in the format <alias>_convert.<script_type>. Here <alias> needs to be replaced by the name of the conversion tool with which the converter registers with Polyglot and <script_type> needs to be replaced by the extension of the script (e.g. py, sh, etc.). For the sake of ease of explanation, we will rename the script file as MyTool_convert.sh. This script accepts three parameters:
- Full path to input file
- Full path to output file (including filename)
Full local path to available scratch space (optional)
- First line is the shebang line
- Second line contains the name of the converter followed by version if any
- Third line refers to the type of the data that it can convert
- Fourth line contains a comma-separated list of input file formats accepted by this converter
- Fifth line contains a comma-separated list of output file formats that this converter can generate
- This is followed by the actual code that does conversion.
Modify Dockerfile in the converter directory to replace ImageMagick with MyTool. Specifically change line numbers 11, 15, 16 and 17. You need to also change other fields like maintainer and may need to add instructions to install any specific software required by your converter. For example, you can see instruction to install ImageMagick software in the example Dockerfile:
Code Block language text theme Confluence title Dockerfile linenumbers true # Create softwareserver for polyglot. FROM ncsapolyglot/polyglot:develop MAINTAINER Rob Kooper <kooper@illinois.edu> USER root # - install requirements # - enable shellscripts to be scanned # - enable imagemagick conversion by adding to .aliases.txt RUN apt-get update && apt-get -y install vim nano imagemagick && \ /bin/sed -i -e 's/^\([^#]*Scripts=\)/#\1/' -e 's/^#\(ShellScripts=\)/\1/' /home/polyglot/polyglot/SoftwareServer.conf && \ echo "ImageMagick" > /home/polyglot/polyglot/scripts/sh/.aliases.txt # copy convert file to scripts/sh folder in container # this is done to keep cache so you can debug script easily COPY ImageMagick_convert.sh /home/polyglot/polyglot/scripts/sh/ RUN chown polyglot /home/polyglot/polyglot/scripts/sh/ImageMagick_convert.sh && \ chmod +x /home/polyglot/polyglot/scripts/sh/ImageMagick_convert.sh # back to polyglot CMD ["softwareserver"]
Modify:
Code Block theme Confluence echo "ImageMagick" > /home/polyglot/polyglot/scripts/sh/.aliases.txt
To:
Code Block theme Confluence echo "MyTool" > /home/polyglot/polyglot/scripts/sh/.aliases.txt
Modify:
Code Block theme Confluence COPY ImageMagick_convert.sh /home/polyglot/polyglot/scripts/sh/
To:
Code Block theme Confluence COPY MyTool_convert.sh /home/polyglot/polyglot/scripts/sh/
Modify:
Code Block theme Confluence RUN chown polyglot /home/polyglot/polyglot/scripts/sh/ImageMagick_convert.sh && \ chmod +x /home/polyglot/polyglot/scripts/sh/ImageMagick_convert.sh
To:
Code Block theme Confluence RUN chown polyglot /home/polyglot/polyglot/scripts/sh/MyTool_convert.sh && \ chmod +x /home/polyglot/polyglot/scripts/sh/MyTool_convert.sh
Build the Dockerfile and start the converter
Code Block theme Confluence docker-compose stop docker build –t mytool . docker-compose up
Usage of BD-tmux
BD-tmux runs the necessary dockerized Brown Dog Data Transformation Services (Polyglot, Clowder, Fence, ImageMagick converter and OCR extractor) and combines them into one integrated program.
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