Open Source Unix Shell Source Code Analysis Tools

This repository is for the GitHub Action to run a Super-Linter. It is a simple combination of various linters, written in bash, to help validate your source code. The super-linter finds issues and reports them to the console output. Fixes are suggested in the console output but not automatically fixed, and a status check will show up as failed on the pull request. The design of the Super-Linter is currently to allow linting to occur in GitHub Actions as a part of continuous integration occurring on pull requests as the commits get pushed. It works best when commits are being pushed early and often to a branch with an open or draft pull request. There is some desire to move this closer to local development for faster feedback on linting errors but this is not yet supported. There is no need to set the GitHub Secret as it is automatically set by GitHub, it only needs to be passed to the action.

It's a web application which provides a unify solution to stat. CVS/SVN repository modules code change information and generate html reports. User can browse line of change, file of change, code diff, check-in comment and so on, it can stat. more repository modules one time. After repository modules configured, stat. is simple like a search. It's the mirror project of CodeChangeViewer: http://sourceforge.net/projects/ccv/.

It's a web application which provides a unify solution to stat. CVS/SVN repository modules code change information and generate html reports. User can browse line of change, file of change, code diff, check-in comment and so on, it can stat. more repository modules one time. After repository modules configured, stat. is simple like a search.

The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and Windows - Python2, Python3 - CPython, PyPy Object addresses within modules - Object Identifier OID - and the display of the runtime call flow are supported by 'PyStackInfo'. Online documents: https://pysourceinfo.sourceforge.io/