Dremio Python Libraries

Connect Python to Dremix Cloud and Software via Arrow Flight or dataframe workflows using dremio-simple-query and dremioframe libraries.

Updated Mar 6, 2026

Search Tags:#python #dataframe #data-ingestion #dremio #arrow-flight #dremioframe #dremio-simple-query

Ready to run

npx skills add https://github.com/developer-advocacy-dremio/dremio-skills-bundle --skill dremio-python-libraries

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Dremio Python Libraries
Source: https://github.com/developer-advocacy-dremio/dremio-skills-bundle/tree/main/dremio-python-skill
Command: npx skills add https://github.com/developer-advocacy-dremio/dremio-skills-bundle --skill dremio-python-libraries

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides a concise, actionable guide for connecting AI agents and developers to Dremio from Python to run queries, build dataframes, ingest data, and perform administration tasks without needing to memorize library specifics.

Core Features & Use Cases

Lightweight high-performance queries: Use Arrow Flight via dremio-simple-query for fast SQL query execution and zero-copy Arrow results.
Full-featured dataframe workflows: Use DremioFrame for ingestion, CRUD, Iceberg management, modeling, charting, orchestration, and admin tasks.
Flexible authentication and outputs: Supports profiles, environment variables, or direct parameters and returns results as Arrow, Pandas, Polars, or DuckDB relations.
Use Case: Quickly fetch large query results into a Pandas DataFrame for analysis or build repeatable ingestion pipelines that merge API data into Iceberg tables.

Quick Start

Connect using a saved profile or environment variables and instruct the agent to run a SQL query and return the results as a Pandas DataFrame.

Frequently Asked Questions about Dremio Python Libraries

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I connect to Dremio from Python to run SQL queries?▼

Connect to Dremio from Python using the dremio-simple-query library for lightweight Arrow Flight queries or DremioFrame for full dataframe workflows. Authenticate via saved profiles, environment variables, or direct parameters to execute SQL.

Can I return Dremio query results as a Pandas or Polars DataFrame?▼

Yes, Dremio Python libraries support returning query results as Pandas or Polas DataFrames, as well as zero-copy Arrow tables and DuckDB relations. Use dremio-simple-query for fast retrieval or DremioFrame for complex dataframe operations.

What is the best way to ingest data into Iceberg tables using Dremio in Python?▼

Use DremioFrame to build repeatable ingestion pipelines that merge API data into Iceberg tables. DremioFrame handles full-featured dataframe workflows including CRUD operations, Iceberg management, and orchestration within Dremio Cloud or Dremio Software.

Does Dremio support zero-copy Arrow Flight results for high-performance Python queries?▼

Yes, the dremio-simple-query library uses Arrow Flight to provide zero-copy Arrow results for high-performance SQL query execution. This enables fast data retrieval directly into Python for analysis without serialization overhead.

Do I need different Python libraries for Dremio administration tasks versus data ingestion?▼

No, DremioFrame handles both data engineering tasks like ingestion and administration tasks within a single library. Use dremio-simple-query only for lightweight queries, while DremioFrame covers modeling, charting, orchestration, and admin workflows.

Can I use Dremio Python libraries with both Dremio Cloud and Dremio Software?▼

Yes, Dremio Python libraries support both Dremio Cloud and Dremio Software environments. You can authenticate using profiles or environment variables and perform queries, dataframe operations, and Iceberg management across both platforms.