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CKAN extension for data
by Natural History Museum

ckanext-nhm

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A CKAN extension for the Natural History Museum’s Data Portal.

Overview

This extension provides theming and specific functionality for the Natural History Museum’s Data Portal.

The codebase shows how to implement various plugins created by the Museum’s developers; notably our new ElasticSearch datastore with versioned records.

Installation

Installation is not going to be useful for anyone not working on the Data Portal, but the steps are left here for reference.

Path variables used below:

  • $INSTALL_FOLDER (i.e. where CKAN is installed), e.g. /usr/lib/ckan/default
  • $CONFIG_FILE, e.g. /etc/ckan/default/development.ini
  1. Clone the repository into the src folder:
cd $INSTALL_FOLDER/src
git clone https://github.com/NaturalHistoryMuseum/ckanext-nhm.git
  1. Activate the virtual env:
. $INSTALL_FOLDER/bin/activate
  1. Install the requirements from requirements.txt:
cd $INSTALL_FOLDER/src/ckanext-nhm
pip install -r requirements.txt
  1. Run setup.py:
cd $INSTALL_FOLDER/src/ckanext-nhm
python setup.py develop
  1. Add ‘nhm’ to the list of plugins in your $CONFIG_FILE:
ckan.plugins = ... nhm

Configuration

These are the options that can be specified in to configure this extension.

[REQUIRED]

Name Description Options
ckanext.nhm.specimen_resource_id ID for the specimens dataset  
ckanext.nhm.indexlot_resource_id ID for the index lots dataset  
ckanext.nhm.artefact_resource_id ID for the artefacts dataset  
ckanext.nhm.abyssline_resource_id ID for the abyssline dataset  
ckanext.nhm.mam.username Username for the Museum’s image server  
ckanext.nhm.mam.password Password for the Museum’s image server  

Usage

Actions

record_show

Retrieve an individual record.

from ckan.plugins import toolkit

data_dict = {
                'resource_id': RESOURCE_ID,
                'record_id': RECORD_ID,
                'version': OPTIONAL_RECORD_VERSION
            }

toolkit.get_action('record_show')(
    context,
    data_dict
)

download_original_image

Request original image from the Museum’s image server.

from ckan.plugins import toolkit

data_dict = {
                'resource_id': RESOURCE_ID,
                'record_id': RECORD_ID,
                'asset_id': IMAGE_ID,
                'email': REQUESTER_EMAIL
            }

toolkit.get_action('download_original_image')(
    context,
    data_dict
)

object_rdf

Get record RDF from its occurrence ID.

from ckan.plugins import toolkit

data_dict = {
                'uuid': OCCURRENCE_ID,
                'version': OPTIONAL_RECORD_VERSION
            }

toolkit.get_action('object_rdf')(
    context,
    data_dict
)

Commands

create-dataset-vocabulary

Ensures the default dataset vocabulary and categories exists.

ckan -c $CONFIG_FILE nhm create-dataset-vocabulary

add-dataset-category

Adds the given category to the dataset category vocabulary.

ckan -c $CONFIG_FILE nhm delete-dataset-category $NAME

delete-dataset-category

Deletes the given dataset category from the vocabulary.

ckan -c $CONFIG_FILE nhm create-dataset-vocabulary $NAME

replace-resource-file

Replaces the file associated with $RESOURCE_ID with $PATH, e.g. to replace a small dummy file with a large one that was too big to upload initially.

ckan -c $CONFIG_FILE nhm replace-resource-file $RESOURCE_ID $PATH

Testing

Test coverage is currently super duper extremely limited.

To run the tests in this extension, there is a Docker compose configuration available in this repository to make it easy.

To run the tests against ckan 2.9.x on Python3:

  1. Build the required images
docker-compose build
  1. Then run the tests. The root of the repository is mounted into the ckan container as a volume by the Docker compose configuration, so you should only need to rebuild the ckan image if you change the extension’s dependencies.
docker-compose run ckan

The ckan image uses the Dockerfile in the docker/ folder which is based on openknowledge/ckan-dev:2.9.

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