scverse
Official@scverse
Foundational tools for omics data in the life sciences
Agent Skills by scverse
Showing 3 vetted skills indexed across 1 GitHub repositories.
memray
Profile Python memory allocations and generate temporal flamegraph HTML reports.
profimp
Profile Python import times and generate an HTML waterfall report.
pyspy
Profile Python script CPU time with py-spy and output speedscope JSON.
Frequently Asked Questions About scverse
FAQPage SchemaWhat specific performance metrics can be captured using these profiling utilities?▼
These utilities capture granular memory allocation events, module import duration, and CPU sampling data. Users can generate temporal flamegraphs for memory usage, waterfall charts for import overhead, and speedscope-compatible JSON for CPU time analysis to pinpoint exact performance regressions in complex computational environments.
Which engineering personas benefit most from these profiling capabilities?▼
Bioinformaticians, computational biologists, and software engineers working on high-throughput data processing benefit most. These utilities are designed for developers managing resource-intensive life science applications who require precise visibility into memory consumption and execution speed to optimize large-scale data analysis tasks.
What are the primary prerequisites for deploying these profiling utilities?▼
Deployment requires a standard Unix-like environment with access to the target runtime. Users must have sufficient permissions to attach to running processes or execute child processes for sampling. No complex infrastructure is required, as these utilities function as standalone diagnostic components within existing development environments.