feed-ursus 1.2.8

Command line tool to load CSV content into a Solr index for the UCLA Digital Library's frontend, Ursus (https://digital.library.ucla.edu/)

feed_ursus

Command line tools to load CSV content into a Solr index for the UCLA Digital Library's frontend, Ursus (https://digital.library.ucla.edu/) and the Sinai Manuscripts Digital Library

Using feed_ursus

For basic use, you can install feed_ursus as a systemwide command directly from pypi, without having to first clone the repository.

Installation

Installing with UV

We recommend installing with uv. On MacOS, you can install uv with homebrew:

brew install uv

Then:

uv tool install feed_ursus

UV will install feed_ursus in its own virtualenv, but make the command accessible from anywhere so you don't need to active the virtualenv yourself.

Installing with pipx

If you are already using pipx, you can use it instead of uv:

pipx install feed_ursus

Use

Convert a csv into a json document that follows the data model of an Ursus solr index:

feed_ursus [path/to/your.csv]

This repo includes a docker-compose.yml file that will run local instances of solr and ursus for use in testing this script. To use them, first install docker and docker compose. Then run:

docker-compose up --detach
docker-compose run web bundle exec rails db:setup

It might take a minute or so for solr to get up and running, at which point you should be able to see your new site at http://localhost:3000. Ursus will be empty, because you haven't loaded any data yet.

To load data from a csv:

feed_ursus --solr_url=http://localhost:8983/solr/californica --mapping=dlp load [path/to/your.csv]

Mappers

Different metadata mappings are included for general Digital Library use (--mapping=dlp) and for the Sinai Manuscripts Digital Library (--mapping=sinai). The default is "dlp" – "sinai" is not guaranteed to be up to date as the sinai project is using a forked version at https://github.com/uclalibrary/feed_sinai.

Developing feed_ursus

Installing

For development, clone the repository and use uv to set up the virtualenv:

git clone [e-mail]:UCLALibrary/feed_ursus.git
cd feed_ursus
uv install

Then, to activate the virtualenv:

source .venv/bin/activate

The following will assume the virtualenv is active. You could also run e.g. uv run feed_ursus [path/to/your.csv]

Using the development version

feed_ursus --solr_url http://localhost:8983/solr/californica load [path/to/your.csv]

Running the tests

Tests are written for pytest:

pytest

Running the formatter and linters:

ruff (formatter and linter) will run in check mode in ci, so make sure you run it before committing:

ruff format .
ruff check --fix

mypy (static type checker):

mypy

VSCode Debugger Configuration

To debug with VSCode, the python environment has to be created within the project directory.

TODO: update this section for uv. UV seems more predictable overall so it's probablly easier? Just a matter of rm -rf .venv && uv install?

If it exists, remove the existing setup and install in the project directory:

• poetry env list
• poetry env remove <name of environment you want to delete>
• poetry config virtualenvs.in-project true
• poetry install

Add an appropriate .vscode/launch.json, this assumes you have the python debugger extension installed.

{
    // Use IntelliSense to learn about possible attributes.
    // Hover to view descriptions of existing attributes.
    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
    "version": "0.2.0",
    "configurations": [
        {
            "name": "Python: Run the feed_ursus module",
            "type": "debugpy",
            "request": "launch",
            "cwd": "${workspaceFolder}",
            "console": "integratedTerminal",
            "module": "feed_ursus.feed_ursus",
            "justMyCode": true,
        }
    ]
}

Caveats

IIIF Manifests

When importing a work, the script will always assume that a IIIF manifest exists at https://iiif.library.ucla.edu/[ark]/manifest, where [ark] is the URL-encoded Archival Resource Key of the work. This link should work, as long as a manifest has been pushed to that location by importing the work into Fester or Californica. If you haven't done one of those, obviously, the link will fail and the image won't be visible, but metadata will import and be visible. A manifest can then be created and pushed to the expected location without re-running feed_ursus.py.