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Lakehouse platform

Project description

Phlo

Modern data lakehouse platform built on Dagster, DLT, Iceberg, Nessie, and dbt.

CI PyPI Python 3.11+

Features

  • Decorator-driven development - Reduce boilerplate by 74% with @phlo.operations.ingestion and @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:

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

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