pypangolin 0.5.1

Python client for Pangolin Data Catalog

PyPangolin

Python Client for the Pangolin Data Catalog.

Installation

pip install pypangolin

For Delta Lake support:

pip install "pypangolin[delta]"

Quick Start

Core Client

from pypangolin import PangolinClient

# Connect to Pangolin
client = PangolinClient(uri="http://localhost:8080")
client.login("username", "password")

# Work with catalogs
catalogs = client.catalogs.list()

### Warehouse Management

```python
# Create an S3 warehouse with custom configuration (e.g. MinIO)
warehouse = client.warehouses.create_s3(
    name="minio_warehouse",
    bucket="my-bucket",
    endpoint="http://minio:9000",
    access_key="minio",
    secret_key="minio123",
    # Pass extra S3 properties via kwargs
    **{"s3.path-style-access": "true"}
)

### PyIceberg Integration

```python
from pypangolin import get_iceberg_catalog

catalog = get_iceberg_catalog("analytics", uri="http://localhost:8080", token="...")
table = catalog.load_table("sales.transactions")

Generic Assets (Delta Lake)

from pypangolin.assets import DeltaAsset

# Write data and register in Pangolin automatically
DeltaAsset.write(
    client, 
    "analytics", "staging", "my_delta_table", 
    dataframe, 
    location="s3://bucket/path"
)

Documentation

Getting Started

• Authenticated Mode Guide - Standard operational mode with user authentication
• No Auth Mode Guide - For local development and testing
• Publishing Guide - Build and release instructions

Core Features

• PyIceberg Integration - Apache Iceberg tables with PyIceberg
• Advanced Git Operations - Branching, merging, tagging, and conflict resolution

Table Formats & Assets

• Apache Iceberg: PyIceberg Integration
• Delta Lake: Delta Guide
• Apache Hudi: Hudi Guide
• Apache Paimon: Paimon Guide
• File Formats: Parquet | CSV | JSON
• Specialized Formats: Lance | Vortex
• Other Assets: ML Models, Video, Images, etc.

Advanced Features

• Governance & Security - RBAC, permissions, service users, metadata
• Admin & System - Audit logging, search, tokens, system config
• Federated Catalogs & Views - Remote catalogs and SQL views
• Database Connections - Secure credential management for databases
  • PostgreSQL ✅ | MySQL ✅ | MongoDB ✅
  • Snowflake ⚠️ | Redshift ⚠️ | BigQuery ⚠️ | Synapse ⚠️
  • Dremio ✅

Features

✅ Full API Coverage - Complete support for all Pangolin REST API endpoints
✅ PyIceberg Integration - Seamless Apache Iceberg table operations
✅ Multi-Format Support - Delta, Hudi, Paimon, Parquet, CSV, JSON, and more
✅ Git-like Operations - Branching, merging, tagging with conflict resolution
✅ Governance - Role-based access control and business metadata
✅ Federated Catalogs - Connect to remote Iceberg catalogs
✅ Type-Safe - Pydantic models for all API responses
✅ Audit Logging - Comprehensive audit logs with user attribution

Verification

To run the end-to-end verification suite against a local Pangolin + MinIO stack:

# Ensure MinIO is running and buckets exist
python3 scripts/ensure_buckets.py

# Run verification script
python3 scripts/verify_pypangolin_live.py

License

MIT