Lakehouse platform
Project description
Modern data lakehouse platform built on Dagster, DLT, Iceberg, Nessie, and dbt.
Features
- Decorator-driven development - Reduce boilerplate by 74% with
@phlo.operations.ingestionand@phlo.quality - Write-Audit-Publish pattern - Git-like branching with automatic quality gates and promotion
- Type-safe data quality - Pandera schemas enforce validation and generate Iceberg tables
- Plugin architecture - Extensible via service, source, quality, and transformation plugins
- Observatory UI - Web-based interface for data exploration, lineage, and monitoring
- Production-ready patterns - Auto-publishing to Postgres, configurable merge strategies, freshness policies
- Modern tooling - Built on Dagster, DLT, Iceberg, Nessie, dbt, and Trino
Quick Start
# Install with default services
uv pip install phlo[defaults]
# Initialize a new project
phlo init my-project
cd my-project
# Start services and run
phlo services start
phlo materialize --select "dlt_glucose_entries+"
Documentation
Full documentation at docs/index.md:
- Installation Guide
- Quickstart Guide
- Core Concepts
- Developer Guide
- Plugin Development
- CLI Reference
- Configuration Reference
- Operations Guide
- Blog Series - 13-part deep dive
Development
# Services
phlo services start # Start all services
phlo services stop # Stop services
phlo services logs -f # View logs
# Development
uv pip install -e . # Install Phlo
ruff check src/ # Lint
ruff format src/ # Format
basedpyright src/ # Type check
phlo test # Run tests
Project details
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