open-auto-loader 0.2.0

A lightweight, Databricks-style autoloader using Polars and SQLite.

🚀 OpenAutoLoader

OpenAutoLoader is a high-performance, incremental data ingestion engine. It bridges the gap between raw cloud storage and production-ready Delta Lakes using the lightning-fast Polars Rust engine.

Stop writing complex Spark jobs for simple file ingestion. OpenAutoLoader provides a "Databricks-style" Auto Loader experience in a lightweight Python package.

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💡 Why OpenAutoLoader?

Traditional ingestion often requires heavy JVM clusters (Spark) or manual file tracking. OpenAutoLoader changes that:

• Zero-Spark Overhead: Runs on standard Python environments with Rust-level performance.
• Exactly-Once Processing: Integrated SQLite checkpointing ensures no duplicate data, even if a job restarts.
• Schema First: Automatically infers, saves, and enforces JSON schema contracts to prevent data corruption.
• Cloud Native: A single API for Local, S3, Azure Blob (ABFSS), and GCS.

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🛠️ Installation

# Core (Local files only)
pip install open-auto-loader

# Full Cloud Support (Recommended)
pip install "open-auto-loader[all]"

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🚀 Quick Start: S3 to Delta Lake

from open_auto_loader import OpenAutoLoader

# Define your cloud credentials
storage_options = {
    "aws_access_key_id": "YOUR_ACCESS_KEY",
    "aws_secret_access_key": "YOUR_SECRET_KEY",
    "region": "ap-south-1"
}

# Initialize the loader
loader = OpenAutoLoader(
    source="s3://my-raw-bucket/incoming_logs/",
    target="s3://my-silver-bucket/tables/user_logs",
    check_point="./metadata/checkpoints.db",
    schema_path="./metadata/schemas/",
    storage_options=storage_options
)

# Run the ingestion batch
loader.run(batch_id="daily_run_2026_03_18")

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🏗️ Architecture: How it Works

1. Scanner: Uses fsspec to identify new files since the last successful batch_id.
2. Schema Guard: Checks the file header against the stored JSON contract in schema_path.
3. Polars Engine: Streams the data using sink_delta(), minimizing memory footprint.
4. Metadata Injection: Automatically adds _batch_id, _processed_at, and _source_file to every row for full auditability.
5. Committer: Updates the SQLite checkpoint only after a successful Delta write.

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📋 Compatibility Matrix

Feature	Local	AWS S3	Azure Blob	Google GCS
Incremental Loading	✅	✅	✅	✅
Schema Enforcement	✅	✅	✅	✅
Service Principal Auth	N/A	✅	✅	✅
Streaming Sink	✅	✅	✅	✅

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🤝 Contributing

Contributions are welcome! Whether it's a bug fix, a new cloud provider, or performance tuning, feel free to open a PR.

Created with ❤️ by Nitish Katkade