본문으로 건너뛰기
cccskills
무료GitHub에 공개

performance-testing

Measure indicator calculation speed with BenchmarkDotNet, a benchmarking tool for .NET. Compare batch, incremental, and streaming implementations, detect slowdowns against saved results, and evaluate changes intended to reduce processing time and memory allocations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Benchmark indicator performance with BenchmarkDotNet. Use for Series/Buffer/Stream benchmarks, regression detection, and optimization patterns. Target 1.5x Series for StreamHub, 1.2x for BufferList.

foryourhealth111-pixel/Vibe-Skills
설치 방법 보기

이럴 때 유용합니다

  • Comparing batch, incremental, and streaming performance
  • Detecting performance regressions after code changes
  • Adding benchmarks for a new indicator
  • Evaluating memory allocation optimizations

포함된 파일(2)

  • SKILL.md3.1 KB
  • references/benchmark-patterns.md3.6 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Performance testing

Running benchmarks

cd tools/performance

# Run all benchmarks (~15-20 minutes)
dotnet run -c Release

# Run specific category
dotnet run -c Release --filter *StreamIndicators*
dotnet run -c Release --filter *BufferIndicators*
dotnet run -c Release --filter *SeriesIndicators*

# Run specific indicator
dotnet run -c Release --filter *.EmaHub

Adding benchmarks

Series pattern

[Benchmark]
public void ToMyIndicator() => quotes.ToMyIndicator(14);

Stream pattern

[Benchmark]
public object MyIndicatorHub() => quoteHub.ToMyIndicatorHub(14).Results;

Buffer pattern

[Benchmark]
public MyIndicatorList MyIndicatorList() => new(14) { quotes };

Style comparison

[Benchmark]
public IReadOnlyList<MyResult> MyIndicatorSeries() => quotes.ToMyIndicator(14);

[Benchmark]
public IReadOnlyList<MyResult> MyIndicatorBuffer() => quotes.ToMyIndicatorList(14);

[Benchmark]
public IReadOnlyList<MyResult> MyIndicatorStream() => quoteHub.ToMyIndicator(14).Results;

Performance targets

Note: These are optimization goals for future v3.1+ effort. Current implementations vary—see PERFORMANCE_ANALYSIS.md for actual measured performance. Some indicator families (e.g., EMA) have inherent framework overhead due to simple operation costs.

StyleTarget vs SeriesUse Case
SeriesBaselineBatch processing
BufferList≤ 1.2xIncremental data
StreamHub≤ 1.5xReal-time feeds

Expected execution times (502 periods)

Note: These are optimization targets. Actual execution times vary by indicator complexity and current implementation.

ComplexityTimeExamples
Fast< 30μsSMA, EMA, WMA, RSI
Medium30-60μsMACD, Bollinger Bands, ATR
Complex60-100μsHMA, ADX, Stochastic
Advanced100-200μs+Ichimoku, Hurst

Regression detection

# Auto-detect baseline and results
pwsh detect-regressions.ps1

# Custom threshold (default 10%)
pwsh detect-regressions.ps1 -ThresholdPercent 15

Exit codes:

  • 0 - No regressions
  • 1 - Regressions found

Creating baselines

cp BenchmarkDotNet.Artifacts/results/Performance.*-report-full.json \
   baselines/baseline-v3.0.0.json

Required optimization patterns

  • Minimize allocations in hot paths
  • Avoid LINQ in performance-critical loops
  • Use Span<T> for zero-copy operations
  • Cache calculations when possible
  • Test with realistic data sizes (502 periods)

Prohibited patterns

  • Excessive LINQ in hot paths
  • Boxing/unboxing of value types
  • Unnecessary string allocations
  • Redundant calculations in loops
  • Poor cache locality

See references/benchmark-patterns.md for detailed patterns.

Last updated: December 31, 2025

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

adaptyv

무료

Support experimental validation of designed proteins through a cloud laboratory. Prepare and optimize sequences, submit tests for binding, expression, thermal stability, or enzyme activity, track experiment progress, and retrieve results through the API.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Submit designed proteins for binding tests
  • Request expression, thermal stability, or enzyme activity tests
  • Optimize sequences for solubility before experiments
foryourhealth111-pixel/Vibe-Skills3.8천2026년 10월 20일 업데이트

aeon

무료

Analyze time series, observations ordered over time, using aeon in Python. Build classification, prediction, and clustering workflows, detect unusual patterns or changes, and compare methods through an interface compatible with scikit-learn.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Classifying time series by their patterns
  • Forecasting future values from past observations
  • Detecting anomalies and change points
foryourhealth111-pixel/Vibe-Skills3.8천2026년 10월 20일 업데이트

algorithmic-art

무료

Create original generative art with p5.js, using code to produce patterns and motion. Receive a written artistic concept and an interactive HTML viewer with adjustable parameters, reproducible random variations, seed navigation, and PNG downloads.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Create art from particle motion and flow fields
  • Explore patterns by adjusting sliders
  • Reproduce a favorite variation with the same seed
foryourhealth111-pixel/Vibe-Skills3.8천2026년 10월 20일 업데이트

alpha-vantage

무료

Retrieve stock prices, exchange rates, cryptocurrency prices, company financial statements, and economic indicators through the Alpha Vantage API. It also covers historical data, news sentiment, and technical indicators, which summarize price and trading patterns.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Retrieve historical stock prices and trading volumes
  • Collect company financial statements and earnings data
  • Check foreign exchange and cryptocurrency prices
foryourhealth111-pixel/Vibe-Skills3.8천2026년 10월 20일 업데이트

architecture-patterns

무료

Design backend systems with clear boundaries between business rules, databases, and external services. Use Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to organize new applications, refactor existing code, and make core logic easier to test.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Planning the structure of a new backend
  • Refactoring tightly coupled applications
  • Testing business rules independently of external services
foryourhealth111-pixel/Vibe-Skills3.8천2026년 10월 20일 업데이트

astropy

무료

Helps process astronomical data in Python by converting coordinates, units, and time scales, working with FITS observation files, matching object catalogs, and calculating distances using cosmological models.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Converting celestial coordinates
  • Reading and editing FITS observation files
  • Matching objects across astronomical catalogs
foryourhealth111-pixel/Vibe-Skills3.8천2026년 10월 20일 업데이트

foryourhealth111-pixel의 스킬 모두 보기

이 스킬의 문제 신고