Calculus: Formulations and Solutions with Python

Calculus with Python, taught as a working method

Calculus: Formulations and Solutions with Python approaches calculus as something to be explored, tested, and computed—not just memorized. In the material visible here, G. R. Liu frames the subject around differentiation and integration, then builds outward into rules, theorems, implicit and inverse functions, approximation, Newton iteration, and applications.

The emphasis on Python is not decorative. The book uses code throughout, and the contents indicate a practical, example-driven structure that connects symbolic ideas with executable computation. That makes it especially appealing if you want calculus explained in a way that stays close to real calculation, visualization, and problem solving.

What the book covers

• derivatives of one-dimensional functions
• differentiability and continuity
• core derivative rules, including product, quotient, and chain rules
• useful theorems such as Rolle’s theorem and the mean value theorem
• implicit differentiation and inverse functions
• applications such as local linearization, root finding, and extrema

A hands-on calculus resource

The book’s structure suggests a strong teaching and reference purpose: clear mathematical formulations paired with Python code and worked examples. That combination is useful for readers who want to see how calculus behaves in practice, especially when moving between theory, algebraic manipulation, and computational verification.

Who it suits

This title is a natural fit for students of calculus, applied mathematics, computational methods, and engineering, as well as instructors or self-directed readers who prefer a more computational path into the subject. If you like learning mathematics by working through examples and code rather than reading only from formulas, this one is likely to feel immediately familiar.

Series: Series in Computational Methods, Volume 2.