julia-pro
Master Julia 1.10+ Development
Julia developers need expert guidance on modern Julia features, performance optimization, and production-ready practices. This skill provides comprehensive expertise in Julia 1.10+ development including multiple dispatch, package management, scientific computing, and high-performance numerical code.
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A utilizar "julia-pro". How do I create a custom array type in Julia that supports broadcasting?
Resultado esperado:
To create a custom array type with broadcasting support, you need to define your struct as a subtype of AbstractArray and implement the required interface methods. Here's how:
1. Define your custom array type with eltype and dimensions
2. Implement size() and getindex() methods
3. Optionally implement Broadcast.broadcastable() for optimized broadcasting
The key is maintaining type stability throughout your implementations for optimal performance.
A utilizar "julia-pro". What's the best way to optimize this numerical loop for better performance?
Resultado esperado:
For numerical loop optimization in Julia, consider these approaches:
1. Use @inbounds to skip bounds checking
2. Apply @simd for SIMD vectorization
3. Preallocate arrays to avoid allocations
4. Use view() instead of slicing to avoid copies
5. Check type stability with @code_warntype
Always benchmark with BenchmarkTools.jl before and after optimizations.
Auditoria de Segurança
SeguroPrompt-only skill containing only a SKILL.md file with no executable code. Static analysis scanned 0 files (0 lines) and detected 0 potential security issues. The skill is a pure prompt-based Julia expert that provides guidance and best practices without executing any code. No suspicious patterns or risk factors detected. Safe for publication.
Pontuação de qualidade
O Que Você Pode Construir
Learn Modern Julia Development
Get started with Julia 1.10+ by understanding modern features, best practices, and proper project setup with Pkg.jl
Optimize Performance-Critical Code
Receive expert guidance on profiling, type stability analysis, and optimization techniques for numerical applications
Develop Production Julia Packages
Create publish-ready Julia packages with proper structure, documentation, testing, and CI/CD pipelines
Tente Estes Prompts
How do I [specific task] in Julia 1.10+? Please explain with a simple example.
My Julia function [describe function] is slow. Please analyze and suggest optimizations for better performance.
Design a multiple dispatch type hierarchy for [domain]. Include abstract types, concrete types, and example methods.
Create a complete Julia package structure for [package name]. Include Project.toml setup, src files, test structure, and documentation outline.
Melhores Práticas
- Prioritize type stability in all functions - use @code_warntype to verify
- Use immutable structs by default unless mutation is specifically required
- Format code consistently with JuliaFormatter.jl using BlueStyle
Evitar
- Avoid type piracy - do not define methods for types you do not own
- Avoid using global variables in performance-critical code
- Avoid unnecessary allocations in hot loops