lionfuncs 1.3.2

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lionfuncs: Empowering Python Development 🦁

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🌟 Key Features

• 🔢 Efficient Data Handling: Robust functions for complex data structures
• 🔍 Advanced Parsing: Tools for JSON, Markdown, and text parsing
• 🧮 Algorithmic Operations: Similarity and distance algorithms
• 🐼 Enhanced Pandas Integration: Extended DataFrame functionality
• 🔄 Flexible Type Conversions: Seamless data type conversions
• 📦 Package Management: Import and package operation utilities

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🏗️ Library Structure and Capabilities

lionfuncs
├── algo        # Algorithmic operations
├── data        # Data handling and manipulation
├── parse       # Parsing utilities
├── func        # Function handling and decorators
├── package     # Package and import management
└── integrations# Integrations (e.g., pandas)

• algo: Implements various similarity and distance algorithms (e.g., cosine, Levenshtein, Jaro-Winkler).
• data: Provides tools for efficient manipulation of complex data structures, including nested dictionaries and lists.
• parse: Offers advanced parsing capabilities for JSON, Markdown, and other text formats, with robust error handling.
• func: Includes decorators and utilities for function manipulation, async operations, and error handling.
• package: Manages package imports and provides tools for dynamic module loading and version checking.
• integrations: Extends functionality of popular libraries like pandas, offering optimized operations on DataFrames.

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🚀 Quick Start

Installation

Choose the method that best suits your needs:

# For stable release
pip install lionfuncs

# For latest development version
pip install git+https://github.com/lion-agi/lionfuncs.git

# If you're using poetry
poetry add lionfuncs

Compatibility: lionfuncs supports Python 3.7+

Basic Usage

from lionfuncs.data import to_dict
from lionfuncs.parse import md_to_json
from lionfuncs.algo import cosine_similarity

# Convert string to dict
data = to_dict('{"name": "John", "age": 30}')
print(data)  # Output: {'name': 'John', 'age': 30}

# Parse Markdown to JSON
md_text = "# Title\n- Item 1\n- Item 2"
json_data = md_to_json(md_text)
print(json_data)  # Output: {'title': 'Title', 'items': ['Item 1', 'Item 2']}

# Calculate similarity
similarity = cosine_similarity("hello world", "hello there")
print(similarity)  # Output: 0.7071067811865475

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📊 Performance and Optimization

lionfuncs is designed with performance in mind:

• Efficient algorithms optimized for Python
• Minimal dependencies to reduce overhead
• Utilizes Python's built-in functions and libraries where possible

In benchmark tests, lionfuncs has shown significant performance improvements in data parsing and manipulation tasks compared to conventional methods.

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🌍 Use Cases

lionfuncs has been successfully used in various domains:

1. Data Science: Preprocessing and cleaning large datasets
2. Web Development: Parsing and manipulating JSON data from APIs
3. Text Analysis: Implementing advanced search and similarity algorithms
4. DevOps: Automating package management and deployment processes

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📚 Documentation

For detailed documentation, including API references and advanced usage examples, visit our documentation site.

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🔄 Staying Updated

To stay updated with the latest changes and releases:

1. Watch the GitHub repository
2. Check the CHANGELOG.md for version history
3. Follow us on Twitter @lionfuncs for announcements

We follow Semantic Versioning. For upgrade guides between major versions, refer to our documentation.

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🤝 Contributing

We welcome contributions! See our Contributing Guide for details on how to get started.

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📄 License

lionfuncs is released under the Apache 2.0 License. See the LICENSE file for details.

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🆘 Support

If you encounter any issues or have questions, please file an issue on our GitHub issue tracker.

For security-related issues, please refer to our Security Policy.

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🙏 Acknowledgments

Thank you to all our contributors who've helped make lionfuncs roar! 🦁💖

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Happy coding with lionfuncs! 🎉👨‍💻👩‍💻