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Awesome GitHub RepositoriesInteractive Debuggers

Tools for tracing code execution line-by-line and inspecting variable states during runtime.

Distinct from Python Profilers: Covers the active debugging process and state inspection, whereas Python Profilers focus on performance measurement

Explore 2 awesome GitHub repositories matching development tools & productivity · Interactive Debuggers. Refine with filters or upvote what's useful.

Awesome Interactive Debuggers GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • spyder-ide/spyderspyder-ide का अवतार

    spyder-ide/spyder

    9,240GitHub पर देखें↗

    Spyder is a scientific integrated development environment designed for scientific computing and interactive Python programming. It functions as a static analysis code editor and an interactive Python console, providing a specialized environment for writing and analyzing code for science and engineering. The platform distinguishes itself as an extensible development tool, utilizing a modular plugin architecture that allows for the addition of custom features or the embedding of core components into other software. It features a dedicated debugger and profiler for tracing code execution and mea

    Includes a set of tools for tracing code execution and measuring performance to identify application bottlenecks.

    Python
    GitHub पर देखें↗9,240
  • iamseancheney/python_for_data_analysis_2nd_chinese_versioniamseancheney का अवतार

    iamseancheney/python_for_data_analysis_2nd_chinese_version

    8,937GitHub पर देखें↗

    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

    Guides the use of interactive debuggers to inspect objects and navigate stack frames after exceptions.

    matplotlibnumpypandas
    GitHub पर देखें↗8,937
  1. Home
  2. Development Tools & Productivity
  3. Debugging, Profiling & Testing
  4. Debugging and Diagnostics
  5. Performance and Resource Profilers
  6. CPU Profilers
  7. Interactive Debuggers