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Comment: Reorg to split out / clarify test data instructions

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  1. First, install the necessary prerequisites. You will just need to install three things: Docker Desktop (to run Docker), Git (to access our shared Docker compose files) and finally download those shared Docker compose files.
    1. Instructions for Windows 10
    2. Instructions for Mac OS
    3. Instructions for Linux 
  2. Next, using Git, download (clone) the DSpace Angular UI codebase & move into that codebase directory


    Code Block
    # Download the UI codebase
git clone git@github.com:DSpace/dspace-angular.git
# Move into the created codebase directory
cd dspace-angular


  3. Using the Docker instructions in that codebase, start up both the DSpace 7 REST API and Angular UI via Docker

    1. First, pull down the latest version of the Docker images:  

      Code Block
      docker-compose -f docker/docker-compose.yml pull


    2. Optionally, you can choose to locally rebuild the Angular UI (This is only needed, if you want to try out local changes/customizations to that Angular UI. Otherwise, if you just want to run the default Angular UI, you can skip this step entirely.): 

      Code Block
      docker-compose -f docker/docker-compose.yml build


    3. Finally, start up both the Angular UI and REST API via Docker: 

      Code Block
      docker-compose -p d7 -f docker/docker-compose.yml -f docker/docker-compose-rest.yml up -d


      1. If you'd like to monitor the startup process, you can "tail" the logs as follows:  docker-compose -p d7 logs -f
      2. If anything goes wrong, occasionally a simple restart of the images will resolve it.  Just do a "down" followed by an "up -d" again.

      Once started up, you can create a default Administrative user via the "dspace-cli" container:


  4. Next, optionally, you can add test data to your Docker instance. We have two sets of test data available depending on what you want to test out. CHOOSE ONE.

    1. [Option #1: Use AIP test data] We have a set of AIP (Archival Information Package) data which was exported from a DSpace 6.x instance. This test data is good to get a quick feel for the changes in DSpace 7 compared to DSpace 6.  It's also the easiest to quickly import as we have an ingest script written for Docker

      Code Block
      # This example creates an Admin user with email "test@test.edu" and password "admin"
docker-compose -p d7 -f docker/cli.yml run --rm dspace-cli create-administrator -e test@test.edu -f admin -l user -p admin -c en

      Then, you can ingest a sample set of AIPs again using the "dspace-cli" container. Just run: 

      Code Block
      docker-compose -p d7 -f docker/cli.yml -f ./docker/cli.ingest.yml run --rm dspace-cli
    In the previous step, you will be testing in Docker using AIP data that is similar in structure to DSpace 6.x.  If


    2. [Option #2: Use a database dump of Entities test data] Alternatively, if you'd like to instead test the new Configurable Entities
     
    1. features, we have a separate database dump which provides Entity
    Test
    1. test data.  (This test data is not yet available in AIP format).  Here's how you'd switch your Docker instance to using the Configurable Entities test data

      1. First, you unfortunately need to completely shut down any running volumes and remove them. We will be replacing them with a database dump of Entity test data.

        Code Block
        # Shut down the running containers
docker-compose -p d7 -f docker/docker-compose.yml -f docker/docker-compose-rest.yml down

# Remove any existing volumes
docker volume rm $(docker volume ls -q)


      2. Now, let's recreate those containers with the Configurable Entities test data included:

        Code Block
        # NOTE: the `db.entities.yml` here will startup a database image with Entities test data included (from a database dump)
docker-compose -p d7 -f docker/docker-compose.yml -f docker/docker-compose-rest.yml -f docker/db.entities.yml up -d

# Once started, also load up the Entities test "assetstore" (files) & trigger a reindex
docker-compose -p d7 -f docker/cli.yml -f docker/cli.assetstore.yml run --rm dspace-cli
      In


  5. Finally, in order to have

    a

    an initial login, let's create an initial Administrator using the "dspace-cli" container:

    Code Block
    # This example creates an Admin user with email "test@test.edu" and password "admin"
docker-compose -p d7 -f docker/cli.yml run --rm dspace-cli create-administrator -e test@test.edu -f admin -l user -p admin -c en


  6. After a few minutes, you should have a full local installation of DSpace 7 Preview (with test data).
    1. User Interface: http://localhost:3000/
    2. REST API: http://localhost:8080/server/ 
    3. Admin Login: (whatever login you setup via the "dspace-cli" command above)
  7. Objects/Pages of interest (within the test data):
    1. Journal Example represents a journal with journal volumes, issues and articles, as detailed in the Configurable Entities Design.
    2. Publications Example contains publications which contain a combination of plain-text authors and related author entities. It also contains relations to Research Projects and Organizational Units, as detailed in the Configurable Entities design. Navigating to e.g. a Person will reveal their relations to Publications, Research Projects and Organizational Units.
    3. Submission/Workflow functionality can be tested using one of the collections in this community where the workflow is enabled. You can use the accounts mentioned above to perform the submission and workflow steps. The admin account can perform the submission and all workflow steps as well.
    4. Once logged in, MyDSpace functionality is found in the user menu (upper right).  Submissions can be started from that page, or via the "New → Item" admin menu (if logged in as an Admin).

  8. Once you are done testing, you can stop Docker and clean up the data (deleting the volumes). 

    Code Block
    # Shut down the running containers
docker-compose -p d7 -f docker/docker-compose.yml -f docker/docker-compose-rest.yml down

# Remove all volumes, images, etc (This removes all the existing data and images)
docker system prune --volumes


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