---
id: modelsearch
version: "1.3.2"
license: BSD-3-Clause
license_treatment: permissive
maintenance: active
---

# modelsearch — A library for indexing Django models with Elasicsearch, OpenSearch or database and searching them with the Django ORM.

License: permissive · Maintenance: active · Downloads: 534.2K/mo

## What it is and what it does

Django ModelSearch is a search indexing layer for Django that lets you index your models into Elasticsearch, OpenSearch, or your existing database (PostgreSQL FTS, MySQL FTS, MariaDB FTS, SQLite FTS5) and then query them through the familiar Django ORM. Instead of writing raw search queries, you call `.search()` on a QuerySet just like you would `.filter()`, and the library translates that into the appropriate backend query.

It was built into Wagtail CMS since 2014 and extracted as a standalone package in March 2025. The library handles index synchronization via Django signals, supports zero-downtime index rebuilds using aliases, and integrates with Django's pagination and filtering ecosystem. You define searchable fields on your models with optional per-field boosting, filter fields for fast faceting, and can pull content from related models into the index.

Use it for:

- Build a product catalog search that works across PostgreSQL, Elasticsearch, or SQLite without rewriting query logic for each backend.
- Add autocomplete and fuzzy search to a Django admin or user-facing search form with faceted results.
- Index large text fields (articles, documentation, logs) and search them with phrase queries and field-specific relevance tuning.
- Migrate search from database FTS to Elasticsearch for performance without changing application code.
- Combine full-text search with Django filters and pagination in a single QuerySet chain.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Indexes Django models into Elasticsearch, OpenSearch, or native database full-text search, then queries them through the Django ORM with support for filtering, faceting, and fuzzy search.

Yes. The package is actively maintained, has low install friction, carries a permissive license, and solves a real problem—letting you write search queries in Django ORM syntax regardless of backend. It's production-ready (marked stable, extracted from Wagtail's proven codebase), has no known vulnerabilities, and supports modern Python versions. Install it if you need flexible, backend-agnostic search on Django models.

## Install

pip install modelsearch
uv add modelsearch
poetry add modelsearch

## Installing modelsearch

Before you install: Low friction: pure Python wheel with only Django and django-tasks as runtime dependencies. Actively maintained since March 2025 with recent commits and no known vulnerabilities.

License in practice: BSD-3-Clause (permissive): you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.

Quickstart:

pip install modelsearch

# settings.py
INSTALLED_APPS = [
    'modelsearch',
    'django.contrib.postgres',  # if using PostgreSQL
]

# models.py
from modelsearch import index
from modelsearch.queryset import SearchableQuerySetMixin

class SongQuerySet(SearchableQuerySetMixin, models.QuerySet):
    pass

class Song(index.Indexed, models.Model):
    name = models.TextField()
    search_fields = [index.SearchField('name', boost=2.0)]
    objects = SongQuerySet.as_manager()

# Then search
Song.objects.search("query")

Requires Python 3.10+; if using PostgreSQL, django.contrib.postgres must be in INSTALLED_APPS; run `django-admin rebuild_modelsearch_index` to initialize indexes.

Verify before relying:

- Whether django-tasks is a hard runtime requirement or optional for background indexing.
- Performance characteristics and scaling limits with large datasets or high query volume.
- Compatibility matrix details for specific Elasticsearch/OpenSearch versions beyond the documented 7.x, 8.x, 9.x and 2.x, 3.x ranges.

## Package facts

- License: BSD-3-Clause (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 534.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

django model search indexing, elasticsearch django orm, full-text search django, django database search, opensearch django integration, django queryset search, fuzzy search django models, search-indexing, orm-integration, elasticsearch

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