{"id":49186064,"url":"https://github.com/chevyphillip/python-data-structures-practice","last_synced_at":"2026-04-23T04:02:49.363Z","repository":{"id":303622642,"uuid":"1016131847","full_name":"chevyphillip/python-data-structures-practice","owner":"chevyphillip","description":"Educational Python repository for WGU MSSWEAIE program. 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WGU MSSWEAIE\n\n[![GitHub Pages](https://img.shields.io/badge/docs-GitHub%20Pages-blue)](https://chevyphillip.github.io/python-data-structures-practice/)\n[![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/)\n[![uv](https://img.shields.io/badge/package%20manager-uv-orange)](https://github.com/astral-sh/uv)\n[![License: Educational](https://img.shields.io/badge/license-Educational-green.svg)](LICENSE)\n\n## 🌐 Live Documentation\n\n**📖 Visit the interactive documentation website:** [https://chevyphillip.github.io/python-data-structures-practice/](https://chevyphillip.github.io/python-data-structures-practice/)\n\n## Overview\n\nThis repository contains comprehensive Python data structures and standard library exercises designed specifically for WGU's Master of Science in Software Engineering - AI Engineering program.\n\n**What You'll Learn:**\n\n- **Core Data Structures**: Master lists, dictionaries, and sets with practical applications\n- **Advanced Python Modules**: Deep dive into `itertools`, `collections`, and `functools`\n- **Functional Programming**: Learn modern Python patterns and optimization techniques\n- **Real-world Applications**: Practice with scenarios relevant to AI/ML and software engineering\n\n## Learning Objectives\n\n### 🎯 Core Data Structures\n\n- Master Python data structure fundamentals (lists, dictionaries, sets)\n- Practice real-world data manipulation scenarios\n- Build confidence with slicing, indexing, and operations\n\n### 🚀 Advanced Python Modules\n\n- Master built-in functions for data transformation (`map`, `filter`, `zip`, `enumerate`)\n- Learn advanced iteration patterns with `itertools` module\n- Utilize specialized data structures from `collections` module\n- Apply functional programming concepts with `functools` module\n\n### 💡 Practical Applications\n\n- Prepare for advanced AI/ML data handling\n- Develop algorithmic thinking and problem-solving skills\n- Build efficient, Pythonic code using standard library tools\n\n## Structure\n\n### 📁 Basics (`basics/`)\n\n🟢 **Beginner Level** - Foundation concepts and operations\n\n- `01_lists_basics.ipynb` - Foundation list operations and methods\n- `02_dictionaries_basics.ipynb` - Dictionary fundamentals and key-value operations\n- `03_sets_basics.ipynb` - Set operations, logic, and mathematical operations\n- `04_combined_basics.ipynb` - Integration practice with multiple data structures\n\n### 📁 Intermediate (`intermediate/`)\n\n🟡 **Intermediate Level** - Advanced Python modules and functional programming\n\n- `01_builtin_functions.ipynb` - Master `map()`, `filter()`, `zip()`, `enumerate()`, `sorted()`\n- `02_itertools_mastery.ipynb` - Advanced iteration with `chain()`, `combinations()`, `groupby()`, infinite iterators\n- `03_collections_mastery.ipynb` - Specialized data structures: `Counter`, `defaultdict`, `deque`, `namedtuple`\n- `04_functools_mastery.ipynb` - Functional programming: `partial`, `reduce`, `lru_cache`, `singledispatch`\n\n### 📁 Advanced (`advanced/`)\n\n🔴 **Advanced Level** - Real-world applications and complex scenarios\n\n- `01_combined_practice.ipynb` - Complex multi-structure problems\n- `02_ai_scenarios.ipynb` - AI/ML relevant applications and data processing\n\n### 📁 Assessments (`assessments/`)\n\n📝 **Testing and Evaluation**\n\n- `ds_while_loops_assessment.ipynb` - Comprehensive assessment combining data structures with control flow\n\n### 📁 Data Files (`data/`)\n\n- `sample_data.json` - Sample data for practice exercises\n\n### 📁 Solutions (`solutions/`)\n\n- Complete solutions with explanations organized by difficulty level\n- Alternative approaches and optimization strategies for each problem\n\n## 🚀 Quick Start\n\n### Option 1: Using uv (Recommended)\n\n```bash\n# Clone the repository\ngit clone https://github.com/chevyphillip/python-data-structures-practice.git\ncd python-data-structures-practice\n\n# Install dependencies with uv\nuv sync\n\n# Start Jupyter Notebook\njupyter notebook\n```\n\n### Option 2: Using pip\n\n```bash\n# Clone the repository\ngit clone https://github.com/chevyphillip/python-data-structures-practice.git\ncd python-data-structures-practice\n\n# Create virtual environment\npython -m venv .venv\nsource .venv/bin/activate  # On Windows: .venv\\Scripts\\activate\n\n# Install dependencies\npip install -r requirements.txt\n\n# Start Jupyter Notebook\njupyter notebook\n```\n\n**📖 For detailed setup instructions, visit:** [Installation Guide](https://chevyphillip.github.io/python-data-structures-practice/INSTALLATION)\n\n## Difficulty Progression\n\n🟢 **Beginner (Basics)**:\n\n- Basic operations, simple indexing\n- Core data structure methods\n- Foundation concepts (~30-45 minutes each)\n\n🟡 **Intermediate (Modules)**:\n\n- Advanced Python standard library modules\n- Functional programming concepts\n- Performance optimization techniques (~45-50 minutes each)\n\n🔴 **Advanced (Applications)**:\n\n- Real-world scenarios and complex problems\n- Integration of multiple concepts\n- AI/ML data processing patterns (~45+ minutes each)\n\n## Study Approach for ADHD Learners\n\n✅ **Progressive Learning** - Start with basics, advance systematically\n✅ **Hands-on Practice** - Every concept includes practical exercises\n✅ **Immediate Feedback** - Run each code block as you write it\n✅ **Comprehensive Examples** - Real-world scenarios in every notebook\n✅ **Manageable Chunks** - Each notebook is designed for focused learning sessions\n✅ **Visual Learning** - Rich examples with clear output demonstrations\n\n## 📚 Additional Resources\n\n- **[Study Guide](https://chevyphillip.github.io/python-data-structures-practice/STUDY_GUIDE)** - Structured learning approach and memory aids\n- **[Solutions](solutions/)** - Complete solutions with multiple approaches\n- **[Installation Guide](https://chevyphillip.github.io/python-data-structures-practice/INSTALLATION)** - Detailed setup for both uv and pip\n\n## 🔧 Features\n\n### 📚 Comprehensive Content\n\n- ✅ **Progressive Curriculum** - 10+ notebooks from beginner to advanced\n- ✅ **Standard Library Mastery** - Complete coverage of `itertools`, `collections`, `functools`\n- ✅ **Real-world Applications** - Practical exercises with business scenarios\n- ✅ **Performance Focus** - Caching, optimization, and efficiency techniques\n\n### 🛠️ Technical Excellence\n\n- ✅ **Modern Dependency Management** - Full support for both `uv` and `pip`\n- ✅ **Comprehensive Testing** - Verification tools included (`verify_requirements.py`)\n- ✅ **Professional Documentation** - Live website with installation guides\n- ✅ **Interactive Learning** - Jupyter notebooks with immediate feedback\n\n### 🎯 Learning Support\n\n- ✅ **Multiple Learning Styles** - Visual, hands-on, and theoretical approaches\n- ✅ **ADHD-Friendly Design** - Structured, manageable learning chunks\n- ✅ **Complete Solutions** - Detailed explanations and alternative approaches\n- ✅ **Assessment Tools** - Comprehensive testing and evaluation notebooks\n\n## Support\n\nEach exercise includes:\n\n- Clear step-by-step instructions\n- Helpful hints\n- Common mistake warnings\n- Multiple solution approaches\n\n## 🤝 Contributing\n\nThis is an educational resource. If you find issues or have suggestions for improvements, please open an issue or submit a pull request.\n\n## 📄 License\n\nThis educational content is available for academic and learning purposes.\n\n---\n\n**🌐 Live Documentation:** [https://chevyphillip.github.io/python-data-structures-practice/](https://chevyphillip.github.io/python-data-structures-practice/)\n\n**📂 Repository:** [https://github.com/chevyphillip/python-data-structures-practice](https://github.com/chevyphillip/python-data-structures-practice)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchevyphillip%2Fpython-data-structures-practice","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchevyphillip%2Fpython-data-structures-practice","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchevyphillip%2Fpython-data-structures-practice/lists"}