Skip to main content
Version: 1.5.0 (latest)

destinations.impl.lancedb.schema

Utilities for creating arrow schemas from table schemas.

NULL_SCHEMA​

Empty pyarrow Schema with no fields.

make_arrow_field_schema​

def make_arrow_field_schema(column_name: str, column: TColumnSchema,
                            type_mapper: DataTypeMapper) -> TArrowField

[view_source]

Creates a PyArrow field from a dlt column schema.

make_arrow_table_schema​

def make_arrow_table_schema(
        table_name: str,
        schema: Schema,
        type_mapper: DataTypeMapper,
        vector_field_name: Optional[str] = None,
        embedding_fields: Optional[List[str]] = None,
        embedding_model_func: Optional[TextEmbeddingFunction] = None,
        embedding_model_dimensions: Optional[int] = None) -> TArrowSchema

[view_source]

Creates a PyArrow schema from a dlt schema.

This demo works on codespaces. Codespaces is a development environment available for free to anyone with a Github account. You'll be asked to fork the demo repository and from there the README guides you with further steps.
The demo uses the Continue VSCode extension.

Off to codespaces!

DHelp

Ask a question

Welcome to "Codex Central", your next-gen help center, driven by OpenAI's GPT-4 model. It's more than just a forum or a FAQ hub – it's a dynamic knowledge base where coders can find AI-assisted solutions to their pressing problems. With GPT-4's powerful comprehension and predictive abilities, Codex Central provides instantaneous issue resolution, insightful debugging, and personalized guidance. Get your code running smoothly with the unparalleled support at Codex Central - coding help reimagined with AI prowess.