My Rxtrace system already creates GS1-identical codes in QR, Bar and Data Matrix formats and exports them to PDF, PNG, ZPL and EPL, carrying the four required fields—MFD, MRP, Expiry and Batch No. The companion scanner app correctly reads those codes and returns Company Name, SKU and the original four parameters. Everything is working, but the generation pipeline still feels sluggish when large batches are requested and the overall setup could be leaner. I want a fresh set of eyes to profile the current Python codebase, pinpoint bottlenecks and refactor whatever is necessary to speed things up without changing functionality. Practical caching strategies, smarter loop logic or faster encoding libraries—whatever delivers measurable performance gains—is fair game. If you have proven experience squeezing extra performance out of code that deals with image generation, label printers (ZPL/EPL) or GS1 compliance, I would love to hear how you would approach the problem and how much improvement you expect to achieve. A short note about similar optimization wins you’ve delivered will help me decide quickly.