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A Python package for supporting migration from on-prem to cloud

Project description

🚀 Snowforge - Powerful Data Integration

Snowforge is a Python package designed to streamline data integration and transfer between AWS, Snowflake, and various on-premise database systems. It provides efficient data extraction, logging, configuration management, and AWS utilities to support robust data engineering workflows.


✨ Features

  • AWS Integration: Manage AWS S3 and Secrets Manager operations.
  • Snowflake Connection: Establish and manage Snowflake connections with key-pair authentication.
  • Advanced Logging: Centralized logging system with colored output for better visibility.
  • Configuration Management: Load and manage credentials from a TOML configuration file.
  • Data Mover Engine: Parallel data processing and extraction strategies for efficiency.
  • Extensible Database Extraction: Uses a strategy pattern to support multiple on-prem database systems (e.g., Netezza, Oracle, PostgreSQL, etc.).

📥 Installation

Install Snowforge using pip:

pip install snowforge-package

⚙️ Configuration

Snowforge uses a snowforge_config.toml file to manage profiles and credentials for AWS and Snowflake. The package searches for this file in the following order:

  1. Path specified in the SNOWFORGE_CONFIG_PATH environment variable.
  2. Current working directory.
  3. ~/.config/snowforge_config.toml
  4. Package directory.

✅ Example snowforge_config.toml

[AWS.default]
AWS_ACCESS_KEY = "your-access-key"
AWS_SECRET_KEY = "your-secret-key"
REGION = "us-east-1"

[SNOWFLAKE.default]
USERNAME = "your-username"
ACCOUNT = "your-account"
ROLE = "optional-role"

[SNOWFLAKE.svc_key_based_profile]
USERNAME = "svc_user"
ACCOUNT = "your-account"
KEY_FILE_PATH = "/absolute/path/to/your/private_key.p8"
KEY_FILE_PASSWORD = "your_key_password"

🚀 Quick Start

🔹 Initialize AWS

from Snowforge.AWSIntegration import AWSIntegration

AWSIntegration.initialize(profile="default", verbose=True)

🔹 Connect to Snowflake

from Snowforge.SnowflakeIntegration import SnowflakeIntegration

# Connect using TOML profile:
conn = SnowflakeIntegration.connect(profile="svc_key_based_profile", verbose=True)

# Or fall back to username + account only:
conn = SnowflakeIntegration.connect(user_name="your-user", account="your-account")

🔹 Use Logging

from Snowforge.Logging import Debug

Debug.log("This is an info message", level='INFO')
Debug.log("This is an error message", level='ERROR')

🔹 Extract Data Using Strategy Pattern

from Snowforge.DataMover import Engine
from Snowforge.Extractors.NetezzaExtractor import NetezzaExtractor

extractor = NetezzaExtractor()

header, output_file = Engine.export_to_file(
    extractor=extractor,
    output_path="/tmp/exported_data",
    fully_qualified_table_name="MY_DB.MY_SCHEMA.MY_TABLE",
    filter_column="date_column",
    filter_value="01.01.2023",
    verbose=True
)

🧩 Extending the System

Implement a new database extractor by inheriting from ExtractorStrategy and implementing:

  • extract_table_query(...)
  • list_all_tables(...)
  • export_external_table(...)

📜 License

This project is licensed under the MIT License.


👤 Author

Developed by andreasheggelund@gmail.com. Feel free to reach out for support, suggestions, or collaboration!

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