muscles-data-elasticsearch

Elasticsearch adapter package for muscles-data.

This package is intentionally separate from muscles-data: the core package owns typed ports, resource runtime and diagnostics, while this package owns the Elasticsearch-backed SearchIndexPort implementation.

Related packages

• Core runtime and port contracts: muscles-data
• OpenSearch search adapter: muscles-data-opensearch
• Redis key-value/lock/stream adapter: muscles-data-redis
• Qdrant vector adapter: muscles-data-qdrant
• MongoDB document-store adapter: muscles-data-mongodb
• S3 object-store adapter: muscles-data-s3
• SQLAlchemy direct SQL resource adapter: muscles-data-sqlalchemy
• Executable example: example_data_elasticsearch_1

Usage

For application, register this adapter once when App builds its shared DataAdapterCatalog, alongside NativeSqlFactory and any other configured adapters:

catalog.register(ElasticsearchSearchFactory())

The search.elastic resource itself is declared in the application's central data.resources configuration shown below. A package resolves the port from the existing runtime; it does not build another catalog or DataRuntime:

from muscles.data.ports import SearchIndexPort

search = app.resource.connect("search.elastic", SearchIndexPort)

Resource config stays in the project:

data:
  resources:
    search.elastic:
      type: elasticsearch
      url_env: ELASTICSEARCH_URL
      api_key: !environ ELASTICSEARCH_API_KEY
      index: docs
      timeout: 3
      verify_certs: true

The adapter creates the Elasticsearch client and index lazily on search, index/delete, explicit native access or data.doctor. Application code should use SearchIndexPort; direct client access is only an advanced escape hatch with native_client: true.

Missing indexes are created with a default mapping for text, title and metadata; mapping and settings resource options can customize it. upsert_documents() uses Elasticsearch bulk operations.

See muscular-example/example_data_elasticsearch_1 for an executable example.