pywayne-maths

utility for efficient integer multiplication and factorization with a focus on speed and scalability.

8|Updated Feb 2, 2026
One-click install
npx skills add https://github.com/wangyendt/wayne-skills --skill pywayne-maths
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pywayne-maths
Source: https://github.com/wangyendt/wayne-skills/tree/main/pywayne/maths
Command: npx skills add https://github.com/wangyendt/wayne-skills --skill pywayne-maths

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Mathematical utilities for fast factorization, digit counting, and large-integer multiplication to streamline number-theory tasks and high-performance arithmetic.

Core Features & Use Cases

  • Factorization: enumerate all factors of a positive integer.
  • Digit Analysis: count occurrences of digits within ranges.
  • Karatsuba Multiplication: multiply large integers efficiently using the Karatsuba algorithm.

Quick Start

Compute all factors of a number with get_all_factors, count digit occurrences with digitCount, or multiply large numbers with karatsuba_multiplication.

Frequently Asked Questions about pywayne-maths

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find all factors of a positive integer in Python?

To find all factors of a positive integer in Python, you can use the get_all_factors function. It provides a fast, deterministic way to enumerate every factor for number-theory tasks and digit analysis.

What is the best way to multiply large integers efficiently in Python?

The best way to multiply large integers efficiently is using the Karatsuba multiplication algorithm. The karatsuba_multiplication function implements this approach to streamline high-performance arithmetic operations in Python.

How do I count digit occurrences within a number range in Python?

To count digit occurrences within a number range in Python, use the digitCount function. It performs fast digit analysis to count specific digit occurrences across defined numerical ranges.

Does this mathematical utility require any external dependencies?

No, this mathematical utility does not require any external dependencies. It provides standalone Python implementations for factorization, digit counting, and Karatsuba multiplication with clear, well-documented behavior.

When should I use Karatsuba multiplication over standard Python multiplication?

You should use Karatsuba multiplication over standard Python multiplication when working with very large integers in algorithm design. It offers better performance for high-performance arithmetic tasks compared to standard methods.