numpy-structured

Community

Handle C-like structs in NumPy arrays.

Authorcuba6112
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill enables efficient handling of complex, multi-typed data within NumPy arrays, mimicking C-style structs for better interoperability and memory management.

Core Features & Use Cases

  • Structured Data: Define arrays where each element has named fields of different data types (integers, floats, strings, etc.).
  • Binary Data Interpretation: Directly interpret raw binary data from files or network buffers as structured records.
  • Use Case: When working with sensor data that has a fixed binary format defined by a C header file, use this Skill to load and access fields like 'timestamp', 'temperature', and 'status_code' directly from the byte stream.

Quick Start

Use the numpy-structured skill to create an array of 10 points, each with an integer ID and a 3-element float position.

Dependency Matrix

Required Modules

numpy

Components

scriptsreferences

💻 Claude Code Installation

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Please help me install this Skill:
Name: numpy-structured
Download link: https://github.com/cuba6112/skillfactory/archive/main.zip#numpy-structured

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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