Update README iwth info about ETL Dashboard Docker

README.md

@@ -4,10 +4,6 @@ This repository contains a library for Extract, Transform and Load processes for
 
 You can report issues with current transformations, or suggest sources which should be added to this library using the GitHub issue tracker.
 
-This GitHub repository builds two different docker images:
-* The Dockerfile in the root dir builds https://registry.hub.docker.com/u/bjwebb/resource-projects-etl/
-* The Dockerfile in the `load` dir builds https://registry.hub.docker.com/u/bjwebb/resource-projects-etl-load/
-
 ## Processes
 Each process, located in the **process** folder consists of a collection of files that either (a) document a manual transformation of the data; or (b) perform an automated transformation.
 
@@ -22,67 +18,46 @@ Folders may contain:
 
 The output of each process should be written to the root data/ folder, from where it can be loaded onto the ResourceProjects.org platform.
 
+## Running ETL Dashboard with with docker
 
-## Running locally
-
-### Requirements
-
-* Python 3
-* Bash
+### Running from docker hub
 
-### Run
+You will need [virtuoso container running](https://github.com/NRGI/resourceprojects.org-frontend/#pre-requisites).
 
 ```
-virtualenv .ve --python=/usr/bin/python3
-source .ve/bin/activate
-pip install -r requirements.txt
-./transform_all.sh
+docker rm -f rp-etl
+docker run --name rp-etl --link virtuoso:virtuoso -p 127.0.0.1:8000:80 -e DBA_PASS=dba opendataservices/resource-projects-etl
 ```
 
-You will then have some data in the data/ directory. Currently the load step can only be run with docker (see "Using a data directory on the host system" below).
+Update DBA_PASS as appropriate.
 
-## Running with docker
+Then visit http://locahost:8000/
 
-### Requirements
-
-Docker **1.7** (actual requirement may be >=1.6, but 1.7 is what's been tested. This is required because the docker library python image doesn't work otherwise).
-
-### Running from docker hub
+### Building docker image
 
 ```
-docker rm -f rp-etl rp-load
-docker run --name rp-etl -v /usr/src/app/data -v /usr/src/app/ontology bjwebb/resource-projects-etl
-docker run --name rp-load --link virtuoso:virtuoso --volumes-from virtuoso --volumes-from rp-etl --rm bjwebb/resource-projects-etl-load
+docker build -t opendataservices/resource-projects-etl .
 ```
 
-To run the last command you will need [virtuoso container running](https://github.com/NRGI/resourceprojects.org-frontend/#pre-requisites).
+Then run as described above. (You may want to use a different name for your own image, so as not to get confused with those actually from docker hub).
 
+## Running taglifter locally
 
-### Using a data directory on the host system
-
-To transform the data, and put it in ./data on the host system, run:
-
-```
-docker rm -f rp-etl
-docker run --name rp-etl -v `pwd`/data:/usr/src/app/data bjwebb/resource-projects-etl
-```
-
-To load the data, you can then run:
-
-```
-docker run --name rp-load --link virtuoso:virtuoso --volumes-from virtuoso -v `pwd`/data:/usr/src/app/data -v `pwd`/ontology:/usr/src/app/ontology --rm bjwebb/resource-projects-etl-load
-```
+### Requirements
 
-This load step can also be used to load data not generated using a dockerized step.
+* Python 3
+* Bash
 
-### Building docker images
+### Run
 
 ```
-docker build -t bjwebb/resource-projects-etl .
-docker build -t bjwebb/resource-projects-etl-load load
+virtualenv .ve --python=/usr/bin/python3
+source .ve/bin/activate
+pip install -r requirements.txt
+./transform_all.sh
 ```
 
-Then run as described above. (You may want to use a different name for your own images, so as not to get confused with those actually from docker hub).
+You will then have some data as Turtle in the data/ directory.
 
 # License