Python is increasingly used for scientific computing, data handling, automation, and reproducible analysis. In pharmaceutical sciences, it can support structured work with laboratory observations, formulation data, quality-control records, pharmacokinetic datasets, ADR reports, inventory information, and research data. Python for Pharmaceutical Sciences introduces programming from the beginning for B.Pharm learners and is aligned with the core coverage of BP101T. It covers Jupyter Notebook, variables, data types, input/output, operators, strings, conditions, loops, functions, data structures, NumPy, file handling, Pandas, data cleaning, and Matplotlib. Each concept is supported with pharmacy-focused examples, algorithms, executable code, outputs, interpretations, exercises, and integrated projects.