Document the LPTS pipeline converting DuckDB logical plans to CTE-based SQL strings.
npx skills add https://github.com/cwida/lpts --skill explain-lpts
Please help me install this Agent Skill. Skill: explain-lpts Source: https://github.com/cwida/lpts/tree/main/.claude/skills/explain-lpts Command: npx skills add https://github.com/cwida/lpts --skill explain-lpts
This Skill fills the gap for developers, data engineers, and DBAs working with DuckDB's LPTS extension by providing a single, comprehensive reference for the entire pipeline that transforms optimized logical query plans into equivalent CTE-based SQL strings, eliminating the need to parse source code to understand conversion logic, AST structures, and operator handling.
Consult the explain-lpts skill to look up the AST node structure and conversion logic for a LOGICAL_COMPARISON_JOIN operator when implementing custom join handling for a new SQL dialect.
High-intent search queries and answers about installing and using this skill.
The LPTS pipeline converts DuckDB post-optimizer logical plans into equivalent CTE-based SQL strings by transforming logical plans to AST nodes, then to a CTE list, and finally to a formatted SQL string for transpilation and inspection.
You convert DuckDB logical operators to CTE clauses by applying operator-specific extraction logic for scans, filters, projections, aggregates, and unions, mapping each operator to a CTE node structure with resolved column bindings.
Yes, DuckDB LPTS supports Postgres alongside DuckDB, applying dialect-specific SQL formatting rules during the CTE List to SQL string conversion phase to ensure correct transpilation output.
You trace column binding resolution in DuckDB query plans by consulting the LPTS reference for column binding map rules and expression resolution logic that map logical plan bindings to CTE output columns.
The AST node hierarchy for DuckDB logical plan conversion is a structural reference detailing how logical operators are parsed into abstract syntax tree nodes before CTE list generation and final SQL string formatting.
Yes, you can extend LPTS to support a new SQL dialect by referencing its dialect-specific formatting rules and operator conversion logic to implement custom SQL string generation from the CTE list.
cwidaDocuments LPTS DuckDB extension DDL syntax, including pragmas, table functions, dialects, and known limitations.
openyakTranslate natural-language data needs into dialect-specific SQL for Snowflake, BigQuery, and Postgres.
cwidaBuild, run, and debug the LPTS SQL transpilation test suite.
saschadudkin-sketchOptimize SQL queries and design efficient database schemas.
