DATAMIMIC CE v1.2.1

We are pleased to announce the release of DATAMIMIC CE v1.2.1! This update primarily focuses on updating dependencies to enhance compatibility, performance, and security.

Updated Dependencies

• dill: Updated from 0.3.8 to 0.3.9 - Used for pickling.
• faker: Updated from 19.13.0 to 33.3.1 - Used for generating fake data.
• numpy: Updated from 1.26.4 to 2.2.2 - Used for numerical operations.
• oracledb: Updated from 2.1.2 to 2.5.1 - Used for Oracle database connections.
• psycopg2-binary: Updated from 2.9.9 to 2.9.10 - Used for PostgreSQL database connections.
• pydantic: Updated from 2.10.2 to 2.10.5 - Used for data validation.
• pydantic-settings: Updated from 2.6.1 to 2.7.1 - Used for settings management.
• pymongo: Updated from 4.6.3 to 4.10.1 - Used for MongoDB connections.
• pyodbc: Updated from 5.1.0 to 5.2.0 - Used for ODBC connections.
• requests: Updated from 2.32.2 to 2.32.3 - Used for making HTTP requests.
• sqlalchemy: Updated from 2.0.36 to 2.0.37 - Used for creating engine.
• xmltodict: Updated from 0.13.0 to 0.14.2 - Used for parsing XML data to Python dictionaries.

Updated Dev-Dependencies

• pytest: Updated from 8.0.0 to 8.3.4 - Testing framework.
• pytest-xdist: Updated from 3.5.0 to 3.6.1 - Distributed testing (parallel execution).
• ruff: Updated from 0.8 to 0.9.2 - Fast Python linter written in Rust.
• prettytable: Updated from 3.10.0 to 3.12.0 - Used for creating tables.
• mypy: Updated from 1.14.0 to 1.14.1 - Static type checker for Python.

Notes

• This release is dedicated to updating dependencies to ensure improved compatibility, performance, and security.
• Development dependencies have also been updated to ensure that testing and linting workflows are using the latest versions.

Installation

pip install datamimic-ce==1.2.1

Upgrading

When upgrading from v1.2.0, please ensure that your environment is compatible with the updated dependencies. While backward compatibility is maintained, it's always a good practice to test your application after upgrading dependencies.

For any questions or support, please contact [email protected] or visit our GitHub repository.

Full Changelog: GitHub Compare

DATAMIMIC CE v1.2.0

We are excited to announce DATAMIMIC CE v1.2.0! This release brings important improvements to XML handling, enhanced error handling, and several core functionality updates.

Major Changes

XML Processing Improvements

• Added secure XML parsing with lxml library integration for better entity handling and improved security
• Enhanced XML exporter with more robust error handling and entity resolution controls
• Added support for XML attributes in item generation via ElementTask
• Expanded item elements support to include EL_ELEMENT tag

Error Handling & Expression Evaluation

• Improved Python expression evaluation with better handling of colon characters in expressions
• Enhanced error messages for undefined items and invalid structures
• Added special handling for expressions containing colon characters (e.g., XML namespaces)
• Implemented recursive dictionary processing for proper handling of nested structures

Data Processing Updates

• Improved handling of OrderedDict and dict types in XML file loading
• Enhanced item processing logic with better type checking
• Updated context evaluation mechanisms for more reliable data generation

Technical Updates

• Added lxml>=5.3.0 dependency for improved XML processing
• Added type definitions with types-lxml>=5.3.0 for better development experience
• Updated project dependencies and type checking configurations

Installation

pip install datamimic-ce==1.2.0

Upgrading

When upgrading from v1.1.1, please note that while we've maintained backward compatibility, the XML processing changes might affect some edge cases, particularly if you're using custom XML configurations with special characters or namespaces.

For any questions or support, please contact [email protected] or visit our GitHub repository.

Full Changelog: 1.1.1...1.2.0

DATAMIMIC CE v1.1.1

We are excited to announce a new release of DATAMIMIC Community Edition! This release focuses on code quality improvements, enhanced testing, and better developer experience while maintaining our commitment to providing advanced test data generation capabilities under the MIT license.

What's New in This Release

Code Quality & Development Improvements

• Enhanced project configuration with improved type checking using mypy and ruff
• Refactored codebase with better type hints and improved code clarity
• Improved error handling and logging in database clients and exporters
• Enhanced condition handling for more robust data generation
• Updated documentation with clearer README and new RELEASE.md for better release management

Core Features Reminder

Core Capabilities

• Model-Driven Data Generation: Create and manage sophisticated data models using XML-based configuration
• Advanced Data Transformation: Transform various inputs into abstract entities for flexible output formats
• Multi-Format Support: Generate data in JSON, XML, CSV, RDBMS, and MongoDB formats
• High-Performance Engine: Optimized for handling large data volumes efficiently
• Privacy-First Design: Built-in anonymization and pseudonymization capabilities

Development Features

• Python Integration: Seamless integration with Python 3.10+ projects
• Extensible Architecture: Custom generators and scripts support
• Database Connectivity: Direct integration with various database systems
• Validation Framework: Define and enforce custom data validation rules

Installation

pip install datamimic-ce

System Requirements

• Python 3.10 or higher
• Supported OS: Windows, macOS, Linux

Documentation & Resources

• User Guide: https://docs.datamimic.io
• GitHub Repository: https://github.com/rapiddweller/datamimic
• Issue Tracker: Available on GitHub
• Community Discussions: GitHub Discussions
• Email Support: [email protected]

License

DATAMIMIC CE remains available under the MIT License, allowing for both personal and commercial use with the following permissions:

• Commercial use
• Modification
• Distribution
• Private use

Looking Ahead

We continue to focus on improving code quality and developer experience while maintaining our commitment to providing powerful test data generation capabilities. We welcome contributions and feedback from our community.

For enterprise features and support, check out DATAMIMIC Enterprise Edition at https://datamimic.io

DATAMIMIC CE v1.1.0

We are excited to announce the first open source release of DATAMIMIC Community Edition under the MIT license! This release marks a significant milestone in making advanced test data generation accessible to everyone.

Overview

DATAMIMIC CE is an AI-powered, model-driven platform that revolutionizes test data generation. Built with Python 3.10+, it enables developers and testers to create realistic, scalable, and privacy-compliant test data efficiently.

Key Features

Core Capabilities

• Model-Driven Data Generation: Create and manage sophisticated data models using XML-based configuration
• Advanced Data Transformation: Transform various inputs into abstract entities for flexible output formats
• Multi-Format Support: Generate data in JSON, XML, CSV, RDBMS, and MongoDB formats
• High-Performance Engine: Optimized for handling large data volumes efficiently
• Privacy-First Design: Built-in anonymization and pseudonymization capabilities

Development Features

• Python Integration: Seamless integration with Python 3.10+ projects
• Extensible Architecture: Custom generators and scripts support
• Database Connectivity: Direct integration with various database systems
• Validation Framework: Define and enforce custom data validation rules

Installation

pip install datamimic-ce

System Requirements

• Python 3.10 or higher
• Supported OS: Windows, macOS, Linux

Documentation

Comprehensive documentation is available at:

• User Guide: https://docs.datamimic.io
• API Reference: https://github.com/rapiddweller/datamimic

Community and Support

• GitHub Repository: https://github.com/rapiddweller/datamimic
• Issue Tracker: Available on GitHub
• Community Discussions: GitHub Discussions
• Email Support: [email protected]

License

DATAMIMIC CE is now available under the MIT License, allowing for both personal and commercial use with the following permissions:

• Commercial use
• Modification
• Distribution
• Private use

Looking Ahead

This release represents our commitment to the open source community. We encourage contributions and feedback as we continue to enhance DATAMIMIC CE with new features and improvements.

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For enterprise features and support, check out DATAMIMIC Enterprise Edition at https://datamimic.io