Getting Started

Welcome to ETLantic!

ETLantic catches incompatible data-pipeline wiring before you process data. Define typed datasets, transformations, and pipelines in Python; validate and plan them once; run locally or through optional engine plugins.

Project status: Alpha 0.14.0. See Capabilities for the shipped boundary and Evaluator brief for decision-makers. How to read status labels: Documentation Status.

Five-minute path

1. Current 0.15 guide — task-based map
2. Installation — pip install etlantic==0.15.0
3. Quickstart — copy, run, see Ada Lovelace
4. Break a type on purpose and re-run validate() — that failure is the product
5. Capabilities — only after first success
6. Evaluator brief — if you are deciding whether to adopt

What You'll Learn

• Install ETLantic from PyPI
• Define typed data contracts and transformations
• Wire a pipeline and validate it before execution
• Run locally with in-memory storage
• Use the CLI (validate / plan / run)
• Tell shipped APIs from future design

Prerequisites

• Python 3.11+
• Basic type annotations
• Familiarity with ETL concepts helps; orchestration experience is optional

Documentation Roadmap

1. Installation
2. Quickstart
3. Your First Pipeline
4. Capabilities and Limitations
5. Evaluator Brief
6. Troubleshooting
7. FAQ
8. Project Structure (after a second pipeline)

The ETLantic Mental Model

Typed Python classes
      │
      ▼
Validation (catch bad wiring)
      │
      ▼
PipelinePlan (secret-free, deterministic)
      │
      ▼
Run locally  |  Compile (Airflow)  |  Generate contracts

ETLantic 0.15.0 can execute registered Python implementations with its local runtime and optional Polars/Pandas/SQL/PySpark plugins, compile plans to Airflow DAGs via etlantic-airflow, and execute Polars kernel portable transforms without a native @implementation("polars").

Next Step

Continue with Installation, then Quickstart.