Search (lexigram-search)

Full-text search and indexing for Lexigram Framework — Elasticsearch, Meilisearch, and Algolia

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Overview

lexigram-search provides a unified SearchEngineProtocol interface over Meilisearch, Elasticsearch, Typesense, PostgreSQL full-text, MySQL, MongoDB, and SQLite. It supports typo-tolerant search, faceting, fuzzy matching, result caching, and analytics. All services are wired via SearchProvider, which registers the search engine protocol with the DI container.

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Install

uv add lexigram-search
# Optional extras
uv add "lexigram-search[meilisearch]"     # Meilisearch
uv add "lexigram-search[elasticsearch]"   # Elasticsearch 8.x
uv add "lexigram-search[typesense]"       # Typesense
uv add "lexigram-search[postgres,mysql,sqlite,mongodb]"  # Database backends

Quick Start

from lexigram import Application
from lexigram.di.module import Module, module

# Import the module from the package
from lexigram.search import SearchModule

@module(imports=[SearchModule.configure(...)])
class AppModule(Module):
    pass

app = Application(modules=[AppModule])
if __name__ == "__main__":
    app.run()

Configuration

Zero-config usage: Call SearchModule.configure() with no arguments to use defaults.

Option 1 — YAML file

application.yaml

search:
  backend_type: meilisearch
  meilisearch:
    url: http://localhost:7700
    api_key: "${MEILI_API_KEY}"
  query:
    strategy: fuzzy
    default_limit: 10

Option 2 — Profiles + Environment Variables (recommended)

export LEX_SEARCH__ENABLED=true
# Environment variables for each field

Option 3 — Python

from lexigram.search.config import SearchConfig, BackendType
from lexigram.search import SearchModule

config = SearchConfig(backend_type=BackendType.MEILISEARCH, ...)
SearchModule.configure(config)

Config reference

Field	Default	Env var	Description
backend_type	memory	LEX_SEARCH__BACKEND_TYPE	Active backend (meilisearch, elasticsearch, typesense, postgres, mysql, sqlite, memory)
timeout	30.0	LEX_SEARCH__TIMEOUT	Default request timeout in seconds
query.strategy	fuzzy	LEX_SEARCH__QUERY__STRATEGY	Query strategy (fuzzy, exact, semantic, hybrid)
query.default_limit	10	LEX_SEARCH__QUERY__DEFAULT_LIMIT	Default number of results returned
query.max_limit	100	LEX_SEARCH__QUERY__MAX_LIMIT	Maximum allowed result limit
query.fuzzy_threshold	0.8	LEX_SEARCH__QUERY__FUZZY_THRESHOLD	Fuzzy match threshold (0–1; 1 = exact)
meilisearch.url	http://localhost:7700	LEX_SEARCH__MEILISEARCH__URL	MeiliSearch server URL
meilisearch.api_key	null	LEX_SEARCH__MEILISEARCH__API_KEY	MeiliSearch authentication key
elasticsearch.hosts	[http://localhost:9200]	LEX_SEARCH__ELASTICSEARCH__HOSTS	Elasticsearch cluster hosts
operations.bulk_chunk_size	500	LEX_SEARCH__OPERATIONS__BULK_CHUNK_SIZE	Documents per bulk index request

Module Factory Methods

Method	Description
SearchModule.configure(config, enable_facets)	Configure with explicit SearchConfig
SearchModule.stub()	Minimal config for testing

Key Features

• Protocol abstraction — Swap backends without changing application code
• Meilisearch — Typo-tolerant, instant search with faceting
• Elasticsearch — Full Lucene query DSL; aggregations; multi-index
• Typesense — Fast, schema-enforced search with scoped API keys
• PostgreSQL FTS — tsvector/tsquery via lexigram-sql; no extra infra
• MySQL FTS — FULLTEXT index support for MySQL / MariaDB
• MongoDB Text — Native $text operator with language stemming
• SQLite FTS5 — Local development with zero dependencies
• Cached search — Transparent result caching via CacheBackend
• Analytics — Query recording and hit-rate analytics for ranking improvement

Testing

async with Application.boot(modules=[SearchModule.stub()]) as app:
    # your test code
    ...

Key Source Files

File	What it contains
src/lexigram/search/module.py	SearchModule class with factory methods
src/lexigram/search/di/provider.py	SearchProvider — wires search protocols into DI container
src/lexigram/search/config.py	SearchConfig and sub-config classes
src/lexigram/search/engine/	Search engine implementations for each backend
src/lexigram/search/indexer/	Index management and document indexing