GitCop vs Quantifiedcode: What are the differences?
Developers describe GitCop as "Automated Commit Message Validation for GitHub Pull Requests". Free for open source projects;Any time a pull request is raised on your repository, each commit in the pull request is checked against the repository rules. If any commits do not follow the provided rules, a comment is left against the pull request. On the other hand, Quantifiedcode is detailed as "The first platform for automated code review AND repair". QuantifiedCode is an automated, data-driven code review for Python. Our goal is to help developers write better software in less time. Therefore, we make state-of-the-art code analysis available to everyone.
GitCop and Quantifiedcode can be primarily classified as "Code Review" tools.
What is GitCop?
What is Quantifiedcode?
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Why do developers choose GitCop?
What are the cons of using GitCop?
What are the cons of using Quantifiedcode?
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There are few things in python you do not learn till it punches you in the face. Mutable data types. I started using python 6 months back and "assumed" arguments are passed by value. One example where this mutable argument can behave in a way that you do not expect it to be is if you have lets say "" as a default argument of function. Example:
def myfunc( input= ) blah blah
This does something bad and Quantified Code detects this. They point out that this is not what you expect. They suggest better ways to achieve the same. This is good stuff.
One piece of advise is to not to try fix everything that QC suggests. Fix the dangerous ones. Do not become a victim if instantaneous gratification QC provides.