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A drop-in replacement for the Haystack Elasticsearch backend which allows multilingual indexes for Django.

Project Description

A multilingual Haystack plugin for Django and Elasticsearch. The module is a drop-in replacement for the Haystack ElasticsearchSearchEngine.

Instead of a single index it creates an index for each language specified in settings.LANGUAGES.

A query is routed to the index of the currently active language.

Currently, support for Django 1.10 is not guaranteed.

Installation

Install with pip:

pip install django-multilingual-search

The major and minor versions of this project correspond to the Haystack version the package was tested against. This version is for Haystack 2.4.

Configuration

The app provides a drop-in replacement for the ElasticsearchEngine of Haystack. To use it, specify this engine in settings.py:

HAYSTACK_CONNECTIONS = {
    'default': {
        'ENGINE': 'multilingual.elasticsearch_backend.ElasticsearchMultilingualSearchEngine',
        'URL': 'http://127.0.0.1:9200/',
        'INDEX_NAME': 'myproject',
    },
}

For automatic indexing of new entries the Haystack signal processors can be used without modification. It is recommended that a custom SignalProcessor be used instead of the RealtimeSignalProcessor because of server timeout issues with the latter.

Contributing

Please read the Contributing guide. Any help is greatly appreciated.

My current company is not using Python, so I won’t be able to maintain and keep this library updated.

Release History

  • 2.4.2: Support Haystack 2.4.1
  • 2.4.1: Add compatibility with Django-parler.
  • 2.4.0: Update code for compatibility with Haystack 2.4
  • 2.3.0: First release
Release History

Release History

History Node

2.4.2.beta1

This version
History Node

2.4.1

History Node

2.4.1.beta2

History Node

2.4.0

History Node

2.4.0.beta

History Node

2.3.0.beta

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
django-multilingual-search-2.4.1.tar.gz (5.9 kB) Copy SHA256 Checksum SHA256 Source Nov 20, 2016

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