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.