#Performance-metrics
Showing 22 of 22 repositories tagged #performance-metrics, ranked by stars
Automated auditing, performance metrics, and best practices for the web.
๐ฎ The only Front-End Performance Checklist that runs faster than the others
This repository contains the development code for sparkMeasure, an Apache Spark performance analysis and troubleshooting library. It simplifies collecting, aggregating, and exporting Spark task/stage metrics, and is designed for practical use by developers and data engineers in interactive analysis, testing, and production monitoring workflows.
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DEPRECATED StackImpact Python Profiler - Production-Grade Performance Profiler: CPU, memory allocations, blocking calls, exceptions, metrics, and more
Swift benchmark runner with many performance metrics and great CI support
Possibly the fastest DataFrame-agnostic quality check library in town.
Run Lighthouse analysis over multiple sites in a single command
DEPRECATED - See Elastic APM instead: https://github.com/elastic/apm-agent-nodejs
Exports metrics about a Docker installation
An open source utility library for measuring React component render times.
An android library to measure code execution time. No need to remove the measurement code, automatically becomes no-op in the release variants. Does not compromise with the code readability and comes with features that enhance the developer experience.
Go profiling CLI: collect CPU/memory profiles, compare benchmarks, and catch regressions in CI.
NodeJS Monitoring Agent
Google Lighthouse + Puppeteer / NPM Package
NextLevel is a performance metrics dashboard tailored to Next.js applications that visualizes critical data, such as build time and key web vitals, enabling developers to pinpoint inefficiencies and improve development productivity and end-user experience.
Confusion matrix metrics directly from your pandas DataFrame
Analyze employee performance and productivity using SQL and Python. Build HR dashboards to evaluate departmental KPIs, efficiency trends, and workload balance. Generates actionable insights through data visualization and KPI aggregation for business decision-making.
A high-performance R :package: for supervised and unsupervised machine learning evaluation metrics witten in 'C++'.
This is one of the first and main programs i made for 99