Run and analyze coodie versus cqlengine performance benchmarks with pytest-benchmark.
npx skills add https://github.com/fruch/coodie --skill benchmarks
Please help me install this Agent Skill. Skill: benchmarks Source: https://github.com/fruch/coodie/tree/main/.github/skills/benchmarks Command: npx skills add https://github.com/fruch/coodie --skill benchmarks
This Skill provides a standardized environment and tooling to measure and compare the performance of coodie against cqlengine for various database operations.
Run all benchmarks comparing coodie and cqlengine using pytest.
High-intent search queries and answers about installing and using this skill.
You can benchmark coodie against cqlengine by running predefined side-by-side tests for insert, read, update, delete, and batch operations using pytest-benchmark and Dockerized ScyllaDB instances to measure performance differences.
Yes, pytest-benchmark facilitates comparing ODM performance by running side-by-side benchmarks for coodie and cqlengine against Dockerized ScyllaDB instances to measure insert, read, update, and delete operation speeds.
Investigating a coodie performance regression involves running the insert benchmarks and comparing the results against a previous baseline to identify bottlenecks using the provided profiling and comparison tools.
Adding new performance tests for specific coodie features is facilitated by the benchmarking skill, allowing you to develop and execute new tests alongside existing insert, read, update, delete, and batch benchmarks.
Dockerized ScyllaDB instances are used to provide a standardized environment for measuring and comparing the performance of coodie and cqlengine across various database operations during benchmark execution.
A standardized benchmarking environment ensures accurate performance tuning and regression detection by providing consistent tooling to measure and compare coodie against cqlengine for various database operations.
cofinProvide pytest fixtures for Dockerized database instances in integration tests.
albumentations-teamAnalyze benchmark result JSON to detect slow transforms, warmup instability, and regressions.
Vinix24Profile memory, CPU, I/O, and network usage to detect bottlenecks.
softsparkProfile Python, Node.js, SQL, and frontend code to identify performance bottlenecks.
