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Problem solving with Python programming involves applying logical thinking and computational methods to find efficient solutions. The process starts with understanding the problem, breaking it into smaller steps, and creating algorithms. Python’s simple syntax, built-in functions, and powerful data structures like lists and dictionaries make implementation easier. Control structures such as loops and conditionals help manage program flow, while functions improve modularity and code reuse. Libraries like NumPy, Pandas, and Matplotlib expand capabilities for data handling and visualization. Through debugging and testing, solutions become reliable. Overall, Python empowers learners to solve problems effectively across multiple domains, from automation to data science.