47 مستودعات
Measuring the elapsed time of code execution to identify performance bottlenecks.
Distinct from Time Tracking: Focuses on software profiling and latency tracking rather than business time-tracking or project billing.
Explore 47 awesome GitHub repositories matching software engineering & architecture · Function Execution Timing. Refine with filters or upvote what's useful.
spdlog هي مكتبة تسجيل C++ عالية الأداء مصممة لتسجيل رسائل التشخيص وأحداث التطبيق. تعمل كإطار عمل تسجيل غير متزامن ومكتبة آمنة للخيوط (thread-safe) تنسق الوصول عبر الخيوط المتزامنة للحفاظ على سلامة الرسائل. يعمل المشروع كموجه سجلات متعدد الأهداف، حيث يوزع الأحداث الفردية على وجهات متعددة مثل وحدات التحكم والملفات وخدمات النظام (daemons). يتضمن مدير تدوير السجلات الذي يتعامل مع دورات حياة الملفات من خلال استراتيجيات التدوير الأساسية أو الدورية أو اليومية لمنع استنفاد القرص. تغطي المكتبة مجموعة واسعة من القدرات، بما في ذلك تنسيق السجل المخصص للأنواع المعرفة من قبل المستخدم والبيانات الثنائية، والتقاط موقع المصدر، وتتبع وقت التنفيذ. كما توفر بدائيات المراقبة مثل التقاط تتبع الأحداث عبر التخزين المؤقت لرسائل التصحيح والقدرة على إدارة مستويات السجل من خلال التكوين الخارجي في وقت التشغيل. المكتبة متاحة كتوزيعة تعتمد على ملفات الرأس (header-only) فقط للقضاء على خطوات التجميع المنفصلة.
Measures and logs the elapsed time of code blocks using a built-in stopwatch utility.
Winston is a versatile logging library for Node.js designed to record system events and metadata. It functions as a multi-transport log manager that routes data to various destinations and a structured log formatter that transforms entries into JSON or plain text. The project is distinguished by its pluggable transport architecture, which decouples the logging interface from delivery mechanisms. This allows for the creation of custom transport extensions and the use of hierarchical logger instances to inherit configurations while attaching persistent metadata to downstream messages. The libr
Measures and logs the execution duration of specific operations for performance analysis.
BCC is an eBPF development toolkit and tracing framework used for monitoring and analyzing the Linux kernel. It functions as a performance analysis tool and debugging utility to capture system events, measure kernel latency, and provide network observability. The project distinguishes itself by providing a build system that integrates with LLVM to compile C-like code into BPF bytecode at runtime. It utilizes BPF Type Format data for relocations to maintain cross-kernel compatibility and extracts kernel headers to ensure the generated programs match the specific kernel version. The toolkit co
Measures the time spent in kernel or user-space functions to locate performance regressions.
MicroPython is a lean implementation of Python 3 optimized to run on microcontrollers and other resource-constrained systems. It serves as a cross-platform embedded runtime and hardware abstraction layer, providing a firmware framework that maps high-level software commands to specific microcontroller registers across diverse processor architectures. The project functions as an embedded language interpreter that enables rapid prototyping on hardware through an interactive read-eval-print loop. It supports a wide range of target environments, including ARM, ESP32, STM32, RISC-V, and WebAssembl
Provides functions to track system uptime and execute precise delays using real-time clock hardware.
DoKit is a frontend development debugging toolset designed for web and mobile applications. It provides a suite of utilities for intercepting network traffic, mocking API responses, inspecting UI hierarchies, and monitoring mobile app performance. The project is distinguished by its focus on hybrid app inspection, allowing developers to execute scripts within web views and browse internal application sandboxes. It includes a visual UI audit tool with alignment rulers and color pickers to verify that interfaces match design specifications, as well as a diagnostic system that tracks CPU usage a
Calculates total application startup time and analyzes the duration of specific functions and load methods.
Laravel Debugbar is a web-based debugging toolbar and application profiler for Laravel. It provides a visual interface to inspect database queries, logs, and performance metrics in real time to identify and resolve bugs during development. The tool features a database query monitor to capture SQL statements and timings, as well as a request inspector for analyzing route metadata, loaded views, and HTTP request data. It includes a profiler for measuring execution time and memory usage to identify bottlenecks in the request lifecycle. Its observability capabilities cover exception capture, app
Tracks the start and end times of specific code blocks to resolve performance bottlenecks.
py-spy is a sampling profiler and process debugger for Python. It allows for the analysis of running processes to identify performance bottlenecks and diagnose hanging programs without requiring code changes or restarts. The tool operates by reading the memory of a running process from the outside, which enables non-invasive sampling and state collection without pausing execution. It can resolve binary symbols to capture performance data from native extensions written in compiled languages and generate visual flame graphs for both native extensions and subprocesses. The project provides capa
Displays a real-time view of functions consuming the most time in a running program.
This project is a JavaScript logging utility and namespace-based debugger used for printing formatted, color-coded debug messages to the console in Node.js, web browsers, and Deno. It serves as a console output formatter and execution time profiler to help identify bugs and track program flow. The system manages debug visibility through named namespaces, allowing specific groups of messages to be enabled or disabled via environment variables. It distinguishes different modules in the output stream by assigning specific colors to these namespaces. The utility includes capabilities for measuri
Calculates the millisecond difference between consecutive debug calls to identify bottlenecks.
Quantaxis is a quantitative trading framework designed for building, backtesting, and executing automated strategies across global equities, futures, and cryptocurrencies. It integrates an event-driven backtesting engine, a multi-market execution gateway for order routing, and a quantitative data pipeline for ingesting and storing multi-asset market data. The system features a Rust-accelerated financial library that utilizes Apache Arrow for high-performance technical indicator calculation and zero-copy data processing. It provides a containerized infrastructure model designed for orchestrati
Tracks the elapsed time of functions to identify and resolve performance bottlenecks.
Healthchecks is a heartbeat monitoring service and cron job monitoring tool designed to track the execution and success of scheduled tasks and systemd timers. It functions as a dead man switch, alerting users when expected periodic signals from remote processes fail to arrive. The system accepts health signals via HTTP and SMTP, allowing it to track infrastructure heartbeats from sources ranging from CI/CD workflows to network routers. It distinguishes itself by supporting the capture of diagnostic data, including exit codes and execution logs, and by calculating the duration between start an
Calculates the duration between start and success signals to track how long scheduled tasks take to complete.
Sokol is a C hardware abstraction layer and cross-platform graphics library designed for managing windowing, input, and audio across different operating systems. It functions as a GPU resource manager and multimedia application framework, providing a unified API for rendering 2D and 3D graphics across WebGL, Metal, Direct3D, and OpenGL. The project is distinguished by its single-header implementation, which simplifies integration and portability. It utilizes a stateless render pass definition and a one-update-per-frame model to synchronize CPU data to GPU memory and manage resource lifecycles
Calculates precise execution intervals and lap times using high-resolution timestamps to identify performance bottlenecks.
mini.nvim is a comprehensive library of independent modules designed to extend Neovim with a wide array of navigation, user interface, and text manipulation tools. It serves as a modular plugin collection, a UI toolkit for creating custom statuslines and notifications, and a package manager for installing and pinning external plugins from Git. The project provides a specialized fuzzy picker framework for filtering files and symbols, an LSP completion engine with interactive snippet expansion, and a dedicated plugin test framework that uses headless editor instances and remote procedure calls
Executes functions multiple times to compute summary statistics and measure performance.
Torch7 is a scientific computing environment and tensor computation library used for deep learning research and numerical analysis. It functions as a Lua-based framework for training neural networks and learning agents, providing a toolkit for implementing architectures and training through reinforcement learning algorithms. The project is distinguished by its tight integration with C, utilizing a binding layer to map high-level scripting to low-level C structures for direct memory access. It supports hardware-accelerated computation by offloading linear algebra and convolution operations to
Measures real, user, and system execution time to analyze performance and resource use.
This project is an educational resource and a collection of instructional materials for performing data manipulation and statistical analysis using Python. It provides a comprehensive set of guides and code examples for using the Pandas, NumPy, and Matplotlib libraries to analyze structured data. The resource includes a dedicated guide for reshaping, cleaning, and aggregating tabular data and time series via Pandas, alongside a reference for high-performance vectorized operations and linear algebra using NumPy. It also features tutorials for creating publication-quality charts, distribution p
Provides techniques for profiling the execution time of specific code blocks to resolve bottlenecks.
pysheeet هي مكتبة مرجعية تقنية توفر مجموعة مختارة من مقتطفات التعليمات البرمجية وأنماط التنفيذ لتطوير Python المتقدم، وتكامل النظام، والحوسبة عالية الأداء. تعمل كدليل شامل لتنفيذ برمجة الشبكات منخفضة المستوى، وإضافات C الأصلية، والبرمجة غير المتزامنة والمتزامنة. يوفر المشروع أطر عمل متخصصة لتطوير ونشر نماذج اللغات الكبيرة، بما في ذلك أدوات لاستنتاج GPU الموزع والخدمة عالية الأداء. يتضمن أيضاً أنماطاً مفصلة لتنظيم مجموعات الحوسبة عالية الأداء، وتغطية تخصيص موارد GPU وإدارة عبء العمل متعدد العقد. تغطي المكتبة سطحاً واسعاً من القدرات، بما في ذلك اتصالات الشبكة الآمنة والتشفير، والتعيين الكائني-العلائقي وإدارة قواعد البيانات، وتنفيذ هياكل البيانات والخوارزميات المعقدة. كما توفر أدوات لإدارة الذاكرة، وقابلية التشغيل البيني الأصلية عبر واجهات الوظائف الخارجية، وتكامل نظام التشغيل على مستوى النظام.
Implements precise measurement of elapsed time between function entry and return to identify performance bottlenecks.
TechEmpower FrameworkBenchmarks is an open-source project that provides a standardized, reproducible suite for measuring and comparing the performance of web frameworks across many languages. At its core, it defines a set of common server-side tasks—such as JSON serialization, database queries, and server-side template rendering—and executes them uniformly against hundreds of framework implementations to produce comparable throughput and latency metrics. The project is built around a multi-language benchmark harness that automates the full test lifecycle, from dependency installation and serve
Streams continuously updated performance measurements from automated runs for real-time framework comparison.
This project is a software-defined radio platform designed to capture, analyze, and broadcast radio frequency signals across a wide spectrum. It provides a programmable hardware interface for transmitting and receiving radio signals, enabling spectrum analysis and wireless data monitoring. The system is distinguished by its ability to synchronize multiple devices using a shared external clock and hardware triggers to ensure precise timing and sample accuracy. It supports advanced signal routing, allowing ports to be mapped based on frequency or time to enable specialized operations like pseud
Provides interfaces for integrating external clock signals to ensure precise frequency control.
php-timer is a set of utilities for measuring, tracking, and formatting the execution duration and memory consumption of PHP code segments. It functions as an execution timer and performance profiling utility to analyze resource consumption. The project provides capabilities to track the duration between start and stop triggers in seconds, milliseconds, or nanoseconds. It also includes a resource usage tracker that converts raw execution timestamps and memory bytes into human-readable text strings for reporting. The tool covers performance profiling, resource monitoring, and request duration
Measures the precise elapsed time of PHP code segments to identify performance bottlenecks.
snacks.nvim is a comprehensive collection of quality-of-life plugins and utilities designed to extend the core functionality of Neovim. It serves as a multi-purpose toolkit providing a UI framework, navigation enhancements, and integrations with external services. The project distinguishes itself by combining a wide array of specialized tools into a single suite, including a picker-based file explorer, a deep GitHub integration for managing issues and pull requests, and a set of development utilities for profiling Lua performance and inspecting code execution. Its broader capability surface
Measures the execution time of functions to identify performance bottlenecks.
pyinstrument is a statistical sampling profiler for Python that records the call stack at regular intervals to identify performance bottlenecks with low overhead. It tracks wall-clock time, including I/O and external service calls, and provides specialized profiling for asynchronous programs by attributing time spent awaiting tasks to the calling function. The project converts captured execution data into interactive HTML reports, JSON, and flamecharts. It includes a call stack visualizer to simplify the analysis of execution paths and supports the profiling of individual cells within interac
Records the execution time of functions and modules to identify performance bottlenecks.