performant-code

What problem does it solve?

This skill provides practical guidance to prevent timeouts and memory exhaustion when processing large inputs by encouraging scale-first thinking, efficient I/O, and algorithmic optimization.

Core Features & Use Cases

• Scale-aware planning: Decide whether to load data, stream, or mmap based on dataset size and constraints.
• I/O and buffering strategies: Guidance on buffered reads/writes, mmap, and chunked processing to avoid excessive system calls.
• Algorithmic choices and profiling: Advice on complexity, use of hash maps, numpy for numeric workloads, and when to move hotspots to C.
• Use Case: Processing multi-gigabyte logs, parsing binary data streams, or transforming large datasets without exceeding memory or time limits.

Quick Start

Optimize this code to process a 10GB file using streaming I/O, buffered reads/writes, and memory-efficient algorithms.