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Learn to build a comprehensive data analytics command-line interface tool using only Python's standard libraries, eliminating the need for external dependencies like pandas, numpy, and matplotlib. Master the creation of core data manipulation functionalities including group by operations, aggregations, and tabulation using vanilla Python techniques. Develop CLI-friendly graphing capabilities and implement proper application structure following production best practices for layout and testing methodologies. Explore practical applications through building a TaskWarrior-inspired productivity system, covering terminal-based task management, colorful CLI interfaces, argument parsing, and Python package structure. Gain hands-on experience with code refactoring, modular function design, unit testing, and package publishing while learning advanced techniques like rolling sum calculations grouped by ISO weeks and subprocess module usage. Create a production-ready, well-tested, user-friendly Python tool that saves over 500MB by avoiding external dependencies while maintaining full data science capabilities.
