autodw 0.1.1.post3

Database schema serialization with LLM integration

AutoDW: Data Warehouse Intelligent Agent 🚀

Automated schema processing bridge connecting data warehouses with LLMs

AutoDW is an LLM-based intelligent agent that enhances data warehouse development efficiency through automated database schema processing, metadata optimization, and ETL generation.

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✨ Core Features

Schema Parsing Engine

Capability	Description
Multi-format Export	Exports to JSON/Spider-JSON/MSchema formats
Intelligent Sampling	Random value extraction + frequency-based optimization
Precision Filtering	Table/column-level data filtering support
Currently Supported	SQLite • More DB types coming soon

Metadata Serializer

# Complete metadata serialization in 3 steps  
1. Initialize database connection  
2. Select serialization format (mschema/json)  
3. Retrieve structured metadata  

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🚧 Development Roadmap

✅ Implemented Features

• Database schema interaction engine
• DB Schema ↔ JSON bidirectional conversion
• DB Schema → MSchema serialization

🚀 Coming Soon

• SQL → JSON intelligent converter
• LLM-powered query optimization engine
• Automated ETL script generator
• Schema diff visualization tool
• Cloud service support: BigQuery • Snowflake • Redshift
• REST API remote access interface

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⚙️ Quick Installation

pip install autodw  

🎯 Usage Examples

Schema Parsing

from autodw.connectors.sqlite import SQLiteConnector  

db = SQLiteConnector("your_db.sqlite")  
with db:  
    schema = db.get_database_schema(  
        format="json",  
        sample_type="random",  
        max_samples=3  
    )  
    print(schema)  # Get structured schema data  

Metadata Serialization

from autodw.serializers import DatabaseSchemaSerializer  

db = SQLiteConnector("your_db.sqlite")  
with db:  
    serializer = DatabaseSchemaSerializer(  
        connector=db,  
        serializer_type="mschema",  
        exclude_tables=["temp_*"]  
    )  
    print(serializer.generate())  # Output MSchema format  

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📚 Advanced Documentation

Visit docs/ directory for:

• Detailed API reference
• Schema parsing configuration guide
• LLM integration best practices

Technical Support: Questions? Submit a GitHub Issue
Project Lead: [e-mail]
Project Status: v0.1.1 (Actively Developed)