2 repositorios
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
Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
- spyder-ide/spyder
spyder-ide/spyder
9,240Ver en GitHubSpyder 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 - iamseancheney/python_for_data_analysis_2nd_chinese_version
iamseancheney/python_for_data_analysis_2nd_chinese_version
8,937Ver en GitHubThis 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
