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Rust Systems Portfolio — Robert Nio

World-class Rust systems programming: safety, performance, and production-grade architecture.


TTAPI — High-Performance Financial Data Platform

A production-grade Rust application demonstrating mastery of async/await concurrency, zero-copy data processing, and fault-tolerant systems design.

Key Highlights

🚀 23x faster end-to-end pipeline with intelligent caching ⚡ 438,000 rows/second data import throughput 💾 8x more memory efficient than Python/Pandas equivalents 🔄 100 concurrent requests with semaphore-based backpressure 🎯 ≥90% test coverage with zero clippy::pedantic warnings 🛡️ Circuit breakers & resilience for fault-tolerant operation


Performance at a Glance

End-to-End Pipeline

Metric Cold Run Cached Run Speedup
Total Pipeline 3m 2s 7.8s 23x
Symbol Data 52s 88ms 590x
EOD Processing 2m 26s 4s 36x
Core Data 16s 91ms 176x

Throughput Analysis

Operation Scale Throughput
Symbol collection 22,348 symbols 8,608 symbols/s
MetaStock import 27.6M rows 438,000 rows/s
Parquet load 2.69 GB 690 MB/s
Statistical analysis 29.2M rows 7.3M rows/s

Technical Excellence

1. Workspace Architecture (Polars-Inspired)

2. Async/Await Concurrency

3. Zero-Copy Data Processing

4. Intelligent Caching

5. Circuit Breakers & Resilience


Code Quality Standards

Rust Excellence Playbook 2025

≥90% test coverage (llvm-cov) ✅ Zero clippy::pedantic warningsFile headers (copyright, license, description) ✅ Panic-free public APIs (all errors are Result<T, E>) ✅ Benchmark suites (criterion/divan) ✅ Structured logging (tracing with request IDs)


Documentation

Core Technical Documentation

📊 Performance Benchmarks — Detailed metrics, throughput analysis, and real-world performance data 🏗️ Rust Excellence — Architecture deep-dive with code examples and design patterns 🔍 Architecture Deep Dive — System diagrams, data flow, and concurrency model ⚖️ Why Rust? — Technology comparison (Rust vs. Python/C++/Go) with performance data

Quick References

🎯 Architecture One-Pager — Quick technical overview 🎥 Demo Videos — Watch cold run vs. cached run (23x speedup)

Engineering Write-Ups

📝 Panic-Free Rust APIs — Production-grade error handling 📝 Bench-First Rust Development — Performance as a feature


Real-World Performance

Symbol Data Collection (507 Symbols, S&P 500)

Cold Run: 368,380 data points in 52 seconds Cached Run: 368,380 data points in 88 milliseconds Speedup: 590x faster

EOD Data Processing (9,158 Symbols, 29M Rows)

Cold Run: 29.2M rows (2.69 GB) in 2m 26s Cached Run: 2.69 GB loaded in 3.978s Speedup: 36x faster


Key Differentiators

vs. Python/Pandas

Feature TTAPI (Rust) Python/Pandas
Symbol collection (507) 52s 2+ hours
EOD processing (29M rows) 146s 30+ minutes
Memory usage 2.4 GB 20+ GB
Concurrent requests 100 10-20
Type safety Compile-time Runtime

vs. Typical Rust Projects

Workspace architecture (Polars-inspired domain separation) ✅ ≥90% test coverage (most projects: 50-70%) ✅ Zero clippy::pedantic warnings (most projects: allow some) ✅ Benchmark suites (criterion/divan with CI gates) ✅ Production-grade error handling (circuit breakers, retries, backoff) ✅ Intelligent caching (TTL-based with dependency tracking)


Contact

Robert Nio Rust Systems Engineer GitHub | LinkedIn


License

Documentation and demo materials are public. TTAPI source code is private.

Copyright © 2025 SKY, LLC. All rights reserved.

No proprietary code is included. Performance data is from real production runs.