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How to query what you loaded without writing SQL with DLT

Reattach to a pipeline by name and compose transformations as Ibis expressions that compile to SQL.

Short answer: Install the library with pip install dlt; then Reconnect with DLT.attach, passing pipeline_name, destination and dataset_name; List tables with dataset.tables and pull one as a lazy relation, then call .df(), .arrow() or .to_ibis(). All steps.

  • Data and analytics
  • Intermediate
  • 45 minutes
  • From the README
  • Claude Code
  • Codex
  • Cursor
  • Gemini CLI

Who it is forAn analyst who wants to work in Python on data already loaded.

The problemSwitching to the warehouse console breaks the workflow.

The outcomeAggregated results computed in the destination, returned to Python.

What you need first

  • Python 3.10 through 3.14, with 3.14 support described as experimental
  • `pip install dlt` plus the extras for your sources and destinations
  • Credentials for your destination in secrets.toml or environment variables

Steps

  1. Install the library with pip install dlt
  2. Reconnect with DLT.attach, passing pipeline_name, destination and dataset_name
  3. List tables with dataset.tables and pull one as a lazy relation, then call .df(), .arrow() or .to_ibis()
  4. Compose group_by and aggregate on the Ibis expression and call .to_pyarrow(), which compiles to SQL and runs on the destination

Prompt for your agent

Using dlt-hub/dlt, attach to <my pipeline>, aggregate <my table> by one column with Ibis and bring the result back as an Arrow table.

Caveat. Nothing runs until you ask for the result, so time the final call, not the expression.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for dlt-hub/dlt and "Query what you loaded without writing SQL"

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claude mcp add --transport http deduped https://dedupedai.com/mcp

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