lancedb/docs/src/python/python.md

Python API Reference

This section contains the API reference for the Python API of LanceDB. Both synchronous and asynchronous APIs are available.

The general flow of using the API is:

1. Use [lancedb.connect][] or [lancedb.connect_async][] to connect to a database.
2. Use the returned [lancedb.DBConnection][] or [lancedb.AsyncConnection][] to create or open tables.
3. Use the returned [lancedb.table.Table][] or [lancedb.AsyncTable][] to query or modify tables.

Installation

pip install lancedb

The following methods describe the synchronous API client. There is also an asynchronous API client.

Connections (Synchronous)

::: lancedb.connect

::: lancedb.db.DBConnection

Tables (Synchronous)

::: lancedb.table.Table

::: lancedb.table.FragmentStatistics

::: lancedb.table.FragmentSummaryStats

::: lancedb.table.Tags

Expressions

Type-safe expression builder for filters and projections. Use these instead of raw SQL strings with [where][lancedb.query.LanceQueryBuilder.where] and [select][lancedb.query.LanceQueryBuilder.select].

::: lancedb.expr.Expr

::: lancedb.expr.col

::: lancedb.expr.lit

::: lancedb.expr.func

Querying (Synchronous)

::: lancedb.query.Query

::: lancedb.query.LanceQueryBuilder

::: lancedb.query.LanceVectorQueryBuilder

::: lancedb.query.LanceFtsQueryBuilder

::: lancedb.query.LanceHybridQueryBuilder

Embeddings

::: lancedb.embeddings.registry.EmbeddingFunctionRegistry

::: lancedb.embeddings.base.EmbeddingFunctionConfig

::: lancedb.embeddings.base.EmbeddingFunction

::: lancedb.embeddings.base.TextEmbeddingFunction

::: lancedb.embeddings.sentence_transformers.SentenceTransformerEmbeddings

::: lancedb.embeddings.openai.OpenAIEmbeddings

::: lancedb.embeddings.open_clip.OpenClipEmbeddings

Remote configuration

::: lancedb.remote.ClientConfig

::: lancedb.remote.TimeoutConfig

::: lancedb.remote.RetryConfig

Context

::: lancedb.context.contextualize

::: lancedb.context.Contextualizer

Utilities

::: lancedb.schema.vector

::: lancedb.merge.LanceMergeInsertBuilder

Integrations

Pydantic

::: lancedb.pydantic.pydantic_to_schema

::: lancedb.pydantic.vector

::: lancedb.pydantic.LanceModel

Reranking

::: lancedb.rerankers.linear_combination.LinearCombinationReranker

::: lancedb.rerankers.cohere.CohereReranker

::: lancedb.rerankers.colbert.ColbertReranker

::: lancedb.rerankers.cross_encoder.CrossEncoderReranker

::: lancedb.rerankers.openai.OpenaiReranker

Connections (Asynchronous)

Connections represent a connection to a LanceDb database and can be used to create, list, or open tables.

::: lancedb.connect_async

::: lancedb.db.AsyncConnection

Tables (Asynchronous)

Table hold your actual data as a collection of records / rows.

::: lancedb.table.AsyncTable

::: lancedb.table.AsyncTags

Indices (Asynchronous)

Indices can be created on a table to speed up queries. This section lists the indices that LanceDb supports.

::: lancedb.index.BTree

::: lancedb.index.Bitmap

::: lancedb.index.LabelList

::: lancedb.index.FTS

::: lancedb.index.IvfPq

::: lancedb.index.HnswPq

::: lancedb.index.HnswSq

::: lancedb.index.IvfFlat

::: lancedb.table.IndexStatistics

Querying (Asynchronous)

Queries allow you to return data from your database. Basic queries can be created with the [AsyncTable.query][lancedb.table.AsyncTable.query] method to return the entire (typically filtered) table. Vector searches return the rows nearest to a query vector and can be created with the [AsyncTable.vector_search][lancedb.table.AsyncTable.vector_search] method.

::: lancedb.query.AsyncQuery options: inherited_members: true

::: lancedb.query.AsyncVectorQuery options: inherited_members: true

::: lancedb.query.AsyncFTSQuery options: inherited_members: true

::: lancedb.query.AsyncHybridQuery options: inherited_members: true