Knowledgebase
Help articles for accounts, billing, licences, and common compiler questions.
Performance Tips
Performance improvements from Pyvorin depend on native coverage and workload. Check your native coveragepyvorin compile app.py --report Quick winsUse build mode performance after validating correctness.Increase compilation threads for large projects.Type hot functions to reduce dynamic-type fallbacks. When performance gains are smallI/O-bound programs, scripts dominated by external API calls, and programs with many fallback constructs may not see large speedups. Dashboard widgetThe Compiler Performance widget in the Portal summarizes your compile stats, native percentage, and estimated speedup over time.
Updated 1 month ago
Low Native Coverage
Low native coverage means much of your program fell back to CPython. Review the fallback report for the most common reasons. Add type hints, avoid dynamic imports, and whitelist supported extensions to improve coverage. Not all programs can achieve high native coverage. Correctness is prioritized over coverage.
Updated 1 month ago
Slow Compile
Large projects or many fallback constructs can increase compile time. Try increasing build.threads, excluding tests and documentation from compilation, and using balanced mode instead of performance during development.
Updated 1 month ago
Memory Usage
Compilation can use significant memory for large projects. Close unnecessary applications, reduce parallel threads, or compile on a machine with more RAM. The Portal shows compile resource usage if telemetry is enabled.
Updated 1 month ago
Speedup Less Than Expected
If the measured speedup is smaller than expected, check the native coverage report. Programs that are I/O-bound or have many fallback constructs often see limited gains. Ensure you are measuring representative workloads and warm caches.
Updated 1 month ago