Скачать или смотреть Where next for Wagtail Search?

“This is the average length of the first two lines of YouTube description which is super important to fill correctly.”

From the outset, the Wagtail search module has sought to tackle a problem that's largely independent of Wagtail as a CMS: providing full text search for Django models that is easy to configure and works seamlessly across a variety of backends, both in-database and through external services such as Elasticsearch. It's a goal we're still working towards, and in this talk I'll introduce some of the challenges we face:

Building on Django's familiar APIs for filtering and querysets, even when queries aren't using the database
Keeping external data stores in sync with the database, to handle details such as user permissions
Managing backends with widely differing capabilities, that have a habit of being moving targets between releases, and effectively testing across many different configurations
Getting the subtle UX details right to ensure that search works in the way that users expect

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Wagtail future proofs your CMS system, as it’s open source, continuously updated and built on Python, one of the most popular global programming languages, used widely in machine learning and big data. So you’re always ahead of the curve when it comes to CMS platforms.

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