## batch processing with python-client There are some client libraries for OpenRefine that communicate with the [OpenRefine API](https://github.com/OpenRefine/OpenRefine/wiki/OpenRefine-API). I have prepared a docker container on top of the [Python Library from PaulMakepeace](https://github.com/PaulMakepeace/refine-client-py/) and extended the CLI with some options to create new OpenRefine projects from files. ### basic usage **1) start server:** > docker run -d --name=openrefine-server felixlohmeier/openrefine **2) run client with one of the following commands:** list projects: > docker run --rm --link openrefine-server felixlohmeier/openrefine-client --list create project from file: > docker run --rm --link openrefine-server felixlohmeier/openrefine-client --create [FILE] [PROJECTID] apply rules from json file: > docker run --rm --link openrefine-server felixlohmeier/openrefine-client --apply [FILE.json] [PROJECTID] export project to file: > docker run --rm --link openrefine-server felixlohmeier/openrefine-client --export [PROJECTID] --output=FILE.tsv check help screen for more options: > docker run --rm --link openrefine-server felixlohmeier/openrefine-client --help **3) cleanup:** > docker stop openrefine-server && docker rm openrefine-server ### example for customized run commands in interactive mode (e.g. for usage in terminals) **1) start server in terminal A:** ```docker run --rm --name=openrefine-server -p 80:3333 -v /home/felix/refine:/data:z felixlohmeier/openrefine -i 0.0.0.0 -m 4G -d /data``` * automatically remove docker container when it exits * set name "openrefine" for docker container * publish internal port 3333 to host port 80 * mount host directory /home/felix/refine as working directory * make openrefine available in the network * increase java heap size to 4 GB * set refine workspace to /data * OpenRefine should be available at http://localhost **2) start client in terminal B (prints help screen):** ```docker run --rm --link openrefine-server -v /home/felix/refine:/data:z felixlohmeier/openrefine-client``` * automatically remove docker container when it exits * build up network connection with docker container "openrefine" * mount host directory /home/felix/refine as working directory * apply history in file /home/felix/refine/history.json to project with id 1234567890123 ### example for customized run commands in detached mode (e.g. for usage in shell scripts) **1) define variables (bring your own example data)** > workingdir=/home/felix/refine > inputfile=example.csv > jsonfile=test.json **2) start server** ```docker run -d --name=openrefine-server -v ${workingdir}:/data:z felixlohmeier/openrefine -i 0.0.0.0 -m 4G -d /data``` **3) create project (import file)** ```docker run --rm --link openrefine-server -v ${workingdir}:/data:z felixlohmeier/openrefine-client --create $inputfile``` **4) get project id** ```project=($(docker run --rm --link openrefine-server -v ${workingdir}:/data felixlohmeier/openrefine-client --list | cut -c 2-14))``` **5) apply transformations from json file** ```docker run --rm --link openrefine-server -v ${workingdir}:/data felixlohmeier/openrefine-client --apply ${jsonfile} ${project}``` **6) export project to file** ```docker run --rm --link openrefine-server -v ${workingdir}:/data felixlohmeier/openrefine-client --export --output=${project}.tsv ${project}``` **7) cleanup** ```docker stop -t=500 openrefine-server && docker rm openrefine-server```