uData content recommendations bridge
Project description
udata-recommendations
This plugin acts as a bridge between uData and a recommendation system.
In our case (data.gouv.fr), it's a set of scripts living here https://github.com/etalab/piwik-covisits.
Recommendations are stored on datasets. Recommendations can come from various sources and are stored in a descending order, according to the provided score (from 1 to 100). The top recommendations are displayed at the bottom on the dataset page.
Compatibility
udata-recommendations requires Python 3.7+ and uData.
Installation
Install uData.
Remain in the same virtual environment (for Python).
Install udata-recommendations:
pip install udata-recommendations
Modify your local configuration file of udata (typically, udata.cfg) as following:
PLUGINS = ['recommendations']
RECOMMENDATIONS_SOURCES = {
'source-name': 'https://path/to/recommendations.json',
'other-source': 'https://path/to/other/recommendations.json',
}
RECOMMENDATIONS_NB_RECOMMENDATIONS = 4
RECOMMENDATIONS_SOURCES: A key-value dictionary of recommendation sources and URLs to fetch. Default:{}RECOMMENDATIONS_NB_RECOMMENDATIONS: The maximum number of recommendations to display on the dataset page. Default:4
Usage
Adding recommendations
You can fetch and store recommendations as a task, using your configuration in RECOMMENDATIONS_SOURCES, on a schedule if needed. By default, previous recommendations are cleaned before the importing new ones, but you're in control.
udata job run recommendations-add
# Don't clean each source before importing new recommendations
udata job run recommendations-add should_clean=false
Deleting recommendations
To clean all recommendations, you can run the following task.
udata job run recommendations-clean
Expectations
This plugin expects the following format to provide datasets recommendations:
[
{
"id": "dataset-id",
"recommendations": [
{
"id": "dataset-slug-1",
"score": 100
},
{
"id": "5ef1fe80f50446b8f41ba691",
"score": 1
}
]
},
{
"id": "dataset-id2",
"recommendations": [
{
"id": "5ef1fe80f50446b8f41ba691",
"score": 50
}
]
}
]
Dataset IDs can be IDs or slugs. Scores should be between 1 and 100, inclusive. You can validate your JSON using a JSON Schema.
Changelog
Current (in progress)
- Update Matomo content tracking data-attributes #263
3.1.4 (2023-03-07)
3.1.3 (2023-03-02)
- Recommendations for new dataset page #256
3.1.2 (2022-12-15)
- Update dataset and reuse recommendations to match new udata-front layout 207
3.1.1 (2022-09-01)
3.1.0 (2021-09-16)
- Change udata-gouvfr dependency to udata-front following renaming #188
3.0.0 (2021-08-12)
- Ensure compatibility with udata3 by changing imports and style #183
2.2.0 (2020-11-30)
- Add reuses support #153
2.1.1 (2020-10-16)
- Ignore recommendation of dataset itself #147
2.1.0 (2020-08-25)
- Add score to recommendations and support multiple recommendation sources #142
2.0.0 (2020-03-11)
1.0.1 (2018-08-03)
- Nothing yet
1.0.0 (2018-06-06)
- Allow slug instead of id for datasets #8
- Initial release
Release history Release notifications | RSS feed
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