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Back to plasma-umass/scalene

Projects sharing features with Scalene

30 open-source projects similar to plasma-umass/scalene, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.

  • benfred/py-spybenfred avatar

    benfred/py-spy

    15,272View on GitHub↗

    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

    Rustperformance-analysisprofilerprofiling
    View on GitHub↗15,272
  • nvdv/vprofnvdv avatar

    nvdv/vprof

    3,979View on GitHub↗

    vprof is a visual profiling tool for Python designed to identify execution bottlenecks and monitor memory consumption. It functions as a CPU and memory profiler that transforms performance data into interactive visualizations to analyze processor time and call stacks. The project distinguishes itself through a suite of visual diagnostics, including flame graphs for stack visualization and heatmaps that map execution frequency and duration directly onto source code. It also includes a remote performance monitor capable of capturing function-specific metrics from a running server and streaming

    Pythoncpu-flame-graphd3developer-tools
    View on GitHub↗3,979
  • gperftools/gperftoolsgperftools avatar

    gperftools/gperftools

    8,959View on GitHub↗

    gperftools is a collection of specialized tools for profiling CPU usage, detecting memory errors, and providing high-performance memory allocation. It provides a memory profiling toolkit for C++ applications, including a sampling CPU profiler and a heap profiler for analyzing consumption patterns. The project includes a high-performance memory allocator designed as a multi-threaded replacement for standard allocation to reduce contention and improve execution speed. It further provides a memory debugger to identify illegal memory access and double frees. The toolkit covers broad diagnostic c

    C++
    View on GitHub↗8,959

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  • joerick/pyinstrumentjoerick avatar

    joerick/pyinstrument

    7,638View on GitHub↗

    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

    Pythonasyncdjangoperformance
    View on GitHub↗7,638
  • node-inspector/node-inspectornode-inspector avatar

    node-inspector/node-inspector

    12,646View on GitHub↗

    node-inspector is a web-based debugger for Node.js applications that integrates the Blink developer tools interface. It functions as a runtime profiler and inspection suite, providing a remote debugging interface to connect a local browser to a Node.js process. The project enables live code iteration, allowing source code to be modified while the process is running and persisting those changes back to the physical file system. It also includes a JavaScript runtime profiler to monitor CPU and heap usage for identifying bottlenecks and memory leaks. The tool covers execution flow control throu

    JavaScript
    View on GitHub↗12,646
  • alibaba/arthasalibaba avatar

    alibaba/arthas

    37,367View on GitHub↗

    Arthas is a Java diagnostic tool and runtime debugger designed for real-time troubleshooting of applications. It functions as a remote diagnostics agent that allows users to inspect the runtime state of a Java process, including its heap objects and classloader hierarchies, without requiring a process restart. The project distinguishes itself through advanced bytecode manipulation capabilities, enabling live class hotswapping and the modification of bytecode in running processes. It supports in-memory source compilation and runtime bytecode decompilation to verify and update logic instantly w

    Javaagentalibabaarthas
    View on GitHub↗37,367
  • pythonprofilers/memory_profilerpythonprofilers avatar

    pythonprofilers/memory_profiler

    4,571View on GitHub↗

    This project is a diagnostic utility for monitoring and analyzing memory consumption in Python applications. It provides tools for tracking resource usage at the process level and performing detailed, line-by-line analysis to identify memory leaks and performance bottlenecks. The tool distinguishes itself through its ability to aggregate memory metrics across entire process trees, capturing the total resource impact of both parent and child processes. It supports time-series visualization of memory usage over the duration of a script, allowing for the identification of long-term consumption p

    Python
    View on GitHub↗4,571
  • jvm-profiling-tools/async-profilerjvm-profiling-tools avatar

    jvm-profiling-tools/async-profiler

    9,063View on GitHub↗

    Async-profiler is a suite of performance tools designed for sampling Java runtimes, tracking memory allocations, and monitoring hardware counters. It functions as a low-overhead sampling profiler for Java applications, collecting stack traces and memory allocation data without safepoint bias. The project provides specialized utilities for generating interactive flame graphs to visualize execution hotspots in a web browser. It includes a hardware performance counter monitor to track low-level system events such as cache misses and page faults. The toolset covers several diagnostic domains, in

    C++
    View on GitHub↗9,063
  • microsoft/perfviewmicrosoft avatar

    microsoft/perfview

    4,633View on GitHub↗

    PerfView is a set of integrated profiling and tracing tools built on Windows Event Tracing for Windows (ETW), designed to diagnose CPU, memory, and ETW-based performance issues in .NET applications. It captures ETW events to analyze runtime behavior, CPU usage, and memory allocations, serving as a .NET performance profiler that measures both CPU time and garbage collection events. The tool distinguishes itself with a diff comparison engine that compares two performance traces side-by-side to highlight changes in method costs and event rates. It renders profiled call stacks as flame graphs whe

    C#dotnetdotnet-coreperformance
    View on GitHub↗4,633
  • kdab/hotspotKDAB avatar

    KDAB/hotspot

    5,074View on GitHub↗

    Hotspot is a graphical user interface for analyzing and visualizing performance data captured by the Linux perf tool. It functions as a performance profiling visualizer and assembly-level profiler that maps performance costs to specific instructions synchronized with original source code. The project distinguishes itself through a remote symbol resolver that maps performance data from embedded targets to local host debug symbols and sysroots. It also includes a specialized off-CPU analysis tool designed to identify thread wait times and I/O blocks using kernel scheduler tracepoints. The tool

    C++
    View on GitHub↗5,074
  • iovisor/bcciovisor avatar

    iovisor/bcc

    22,459View on GitHub↗

    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

    C
    View on GitHub↗22,459
  • nswbmw/node-in-debuggingnswbmw avatar

    nswbmw/node-in-debugging

    6,457View on GitHub↗

    This project is a comprehensive technical guide and diagnostic manual for analyzing memory, performance, and asynchronous behavior within Node.js applications. It provides detailed methods for asynchronous tracing, memory diagnostics, and performance analysis to resolve runtime errors and execution bottlenecks. The resource distinguishes itself by covering advanced diagnostic workflows, including the use of flame graphs for CPU profiling, the capture and comparison of heap snapshots for memory leak detection, and the mapping of asynchronous call stacks. It also provides technical guidance on

    debugdebuggingguide
    View on GitHub↗6,457
  • aobingjava/javafamilyAobingJava avatar

    AobingJava/JavaFamily

    36,959View on GitHub↗

    JavaFamily is a curated set of learning paths and reference guides for backend engineering, distributed systems, and virtual machine internals. It provides a structured curriculum covering the Java language, operating system concepts, and network protocols. The project features detailed study guides for the Java virtual machine architecture, including memory management and garbage collection. It also includes a comprehensive reference for distributed systems, covering microservices, remote procedure call frameworks, and scalable system design. The collection covers a broad range of technical

    interviewjavajava8
    View on GitHub↗36,959
  • koute/bytehoundkoute avatar

    koute/bytehound

    4,791View on GitHub↗

    Bytehound is a Linux memory profiler that utilizes a custom global allocator to intercept memory requests and track allocations and deallocations. It records full call-stack traces for every memory operation to map allocations back to their originating source code. The project features a remote memory profiling system that streams capture data via network sockets to a separate machine, minimizing resource overhead on the target system. Analysis is supported by a specialized domain-specific query language used to automate the detection of memory patterns and anomalies. The tool covers heap al

    Cmemory-profilermemory-profilingprofiler
    View on GitHub↗4,791
  • bloomberg/memraybloomberg avatar

    bloomberg/memray

    14,885View on GitHub↗

    Memray is a memory profiler for Python that tracks heap allocations in both Python code and native C or C++ extensions. It captures memory events by hooking into the language runtime and traversing call stacks, providing a comprehensive view of how an application consumes memory. The tool is designed to minimize performance impact on the target application by using thread-local buffering and streaming data to an external process or file. The project distinguishes itself through its ability to monitor complex, multi-threaded systems and child processes in real-time. It provides diagnostic util

    Pythonhacktoberfestmemorymemory-leak
    View on GitHub↗14,885
  • didi/doraemonkitdidi avatar

    didi/DoraemonKit

    20,420View on GitHub↗

    DoraemonKit is a mobile frontend development toolset designed to optimize the lifecycle of web and hybrid mobile applications. It functions as a comprehensive suite of productivity tools, providing specialized utilities for mobile UI inspection, web view debugging, and on-device performance monitoring. The toolset distinguishes itself through several targeted simulation and interception capabilities. It includes a network traffic interceptor for mocking API responses without modifying source code, a device state simulator for overriding GPS coordinates, and a mobile web debugging bridge that

    Java
    View on GitHub↗20,420
  • android/ndk-samplesandroid avatar

    android/ndk-samples

    10,513View on GitHub↗

    The Android NDK samples provide a comprehensive collection of code examples demonstrating how to integrate C and C++ native code into Android applications. This repository serves as a practical guide for developers utilizing the Android Native Development Kit to implement performance-critical application components that require direct hardware access and low-level system interaction. The project highlights the use of the Java Native Interface to bridge managed code with native modules, enabling cross-language function calls and efficient data exchange. It demonstrates how to manage native act

    C++
    View on GitHub↗10,513
  • nodejs/llnodenodejs avatar

    nodejs/llnode

    1,168View on GitHub↗

    An lldb plugin for Node.js and V8, which enables inspection of JavaScript states for insights into Node.js processes and their core dumps.

    C++
    View on GitHub↗1,168
  • gruns/icecreamgruns avatar

    gruns/icecream

    10,063View on GitHub↗

    Icecream is a Python debugging utility designed for inspecting variable values and execution flow during development. It provides a variable inspector that automatically labels values and attaches file and line number metadata to each output. The tool features a builtins injector that adds debugging functions to the global namespace, allowing for universal access across all project files without manual imports. It also includes an inline debugging tool that returns its arguments to the caller, enabling the insertion of inspection calls directly into active expressions without altering program

    Pythondebugdebuggingdebugging-tool
    View on GitHub↗10,063
  • watson/stackmanwatson avatar

    watson/stackman

    257View on GitHub↗

    He is like Batman, but for Node.js stack traces

    JavaScript
    View on GitHub↗257
  • pallets-eco/flask-debugtoolbarpallets-eco avatar

    pallets-eco/flask-debugtoolbar

    979View on GitHub↗

    A toolbar overlay for debugging Flask applications

    JavaScriptdebugflaskflask-debugtoolbar
    View on GitHub↗979
  • ionelmc/python-manholeionelmc avatar

    ionelmc/python-manhole

    402View on GitHub↗

    Debugging manhole for python applications.

    Pythondebuggingpython
    View on GitHub↗402
  • gotcha/ipdbgotcha avatar

    gotcha/ipdb

    1,975View on GitHub↗

    Integration of IPython pdb

    Pythondebuggeripythonpython
    View on GitHub↗1,975
  • inducer/pudbinducer avatar

    inducer/pudb

    3,243View on GitHub↗

    Full-screen console debugger for Python

    Pythonbpythondebugdebugger
    View on GitHub↗3,243
  • barryvdh/laravel-debugbarbarryvdh avatar

    barryvdh/laravel-debugbar

    19,242View on GitHub↗

    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

    PHP
    View on GitHub↗19,242
  • ionelmc/python-hunterionelmc avatar

    ionelmc/python-hunter

    869View on GitHub↗

    Hunter is a flexible code tracing toolkit.

    Pythondebuggerdebuggingpython
    View on GitHub↗869
  • django-commons/django-debug-toolbardjango-commons avatar

    django-commons/django-debug-toolbar

    8,373View on GitHub↗

    django-debug-toolbar is a developer tool that provides a browser-based set of diagnostic panels for inspecting HTTP requests and responses within a Django web application. It serves as a server-side diagnostics tool and web framework development suite, allowing developers to profile and inspect request-response cycles. The tool focuses on Django application troubleshooting, database optimization, and general web development. It enables the analysis of SQL queries and database performance to identify slow calls and reduce the number of requests per page. The software includes capabilities for

    Python
    View on GitHub↗8,373
  • google/gvisorgoogle avatar

    google/gvisor

    17,748View on GitHub↗

    This project is a secure container runtime that provides strong isolation for application workloads by implementing a userspace kernel. By intercepting system calls and executing them within a memory-safe, restricted environment, it minimizes the attack surface exposed to the host kernel. It functions as a drop-in engine for standard container orchestration platforms, ensuring compatibility with industry-standard runtime specifications while maintaining a hardened execution boundary. The runtime distinguishes itself through its ability to virtualize core system resources, including an indepen

    Gocontainersdockerkernel
    View on GitHub↗17,748
  • gaogaotiantian/viztracergaogaotiantian avatar

    gaogaotiantian/viztracer

    7,674View on GitHub↗

    VizTracer is a Python runtime instrumentation system and execution profiler used to trace and visualize code execution. It functions as a multi-process performance analyzer and trace visualizer, providing an interactive timeline and flamegraph interface to identify performance bottlenecks and analyze call sequences. The project distinguishes itself by its ability to aggregate execution data from multiple threads, subprocesses, and asynchronous tasks into a single unified report. It also features live process instrumentation, allowing users to attach to and detach from running Python applicati

    Pythondebuggingflamegraphlogging
    View on GitHub↗7,674
  • what-studio/profilingwhat-studio avatar

    what-studio/profiling

    2,937View on GitHub↗

    This project is a performance analysis suite for Python applications, providing tools for both application-wide profiling and granular code benchmarking. It enables developers to identify execution bottlenecks and measure function call frequency through a combination of deterministic tracing and statistical sampling methods. The tool distinguishes itself by offering a terminal-based interactive interface that allows for real-time navigation and filtering of complex call stacks. It supports non-intrusive data collection through signal-based process interception, enabling performance monitoring

    Pythondebuglive-profilingprofiling
    View on GitHub↗2,937