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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 main features of bloomberg/memray are: Memory Profiling, Memory Profilers, Flame Graph Visualizers, Memory Regression, Memory Leak Detection, Native Stack Unwinders, Memory Allocation Tracers, Temporal Memory Profilers.
Projects with overlapping indexed features include: brendangregg/flamegraph — FlameGraph is a performance profiling and visualization toolkit designed to identify bottlenecks in software… kde/heaptrack — Heaptrack is a heap memory profiler and diagnostic tool for applications running on Linux. It functions as a memory… android/ndk-samples — The Android NDK samples provide a comprehensive collection of code examples demonstrating how to integrate C and C++… gperftools/gperftools — gperftools is a collection of specialized tools for profiling CPU usage, detecting memory errors, and providing… samsaffron/memory_profiler — Memory Profiler is a diagnostic library for Ruby applications designed to monitor runtime memory consumption and… dotnet/benchmarkdotnet — BenchmarkDotNet is a library and tool suite for measuring the execution time and memory allocation of .NET code. It…
FlameGraph is a performance profiling and visualization toolkit designed to identify bottlenecks in software execution. It functions as a processing engine that transforms raw stack trace samples into interactive, hierarchical diagrams. By representing aggregated execution frequency as nested rectangles, the tool allows developers to visualize hot code paths and analyze system behavior across both kernel and user-space environments. The project distinguishes itself through its ability to perform differential profile analysis, which highlights performance regressions or improvements by compari
Heaptrack is a heap memory profiler and diagnostic tool for applications running on Linux. It functions as a memory leak detector and performance analysis system that records heap allocations and stack traces to identify memory hotspots and consumption patterns. The project provides a graphical heap allocation visualizer for exploring memory usage through tree views and peak memory reports. It utilizes flame graphs and allocation charts to visualize memory hotspots and assist in the detection of leaks. The toolset includes capabilities for heap memory allocation tracing and the generation of
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
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