quicketl 1.3.0

QuickETL - Fast & Flexible Python ETL Framework with 20+ backend support via Ibis

QuickETL

Fast & Flexible Python ETL Framework with 20+ backend support via Ibis

QuickETL is a configuration-driven ETL framework that provides a simple, unified API for data processing across multiple compute backends including DuckDB, Polars, Spark, and pandas.

Documentation | GitHub

Features

• 20+ Backends: DuckDB, Polars, Spark, pandas, Snowflake, BigQuery, and more via Ibis
• Configuration-driven: Define pipelines in YAML with variable substitution
• Quality Checks: Built-in validation (not_null, unique, row_count, accepted_values)
• 12 Transforms: filter, aggregate, join, derive_column, and more
• CLI & Python API: Use quicketl run or the Pipeline builder
• Cloud Storage: S3, GCS, Azure via fsspec

Installation

pip install quicketl

See installation docs for backend-specific extras.

Quick Start

# Create a new project
quicketl init my_project
cd my_project

# Run the sample pipeline
quicketl run pipelines/sample.yml

Or use Python:

from quicketl import Pipeline

pipeline = Pipeline.from_yaml("pipeline.yml")
result = pipeline.run()

Example Pipeline

name: sales_etl
engine: duckdb

source:
  type: file
  path: data/sales.parquet

transforms:
  - op: filter
    predicate: amount > 0
  - op: aggregate
    group_by: [region]
    aggs:
      total: sum(amount)

sink:
  type: file
  path: output.parquet

Documentation

Full documentation, tutorials, and API reference at quicketl.com

• Getting Started
• Pipeline Configuration
• Supported Backends
• CLI Reference

License

MIT License - see LICENSE for details.