codebeat vs Quantifiedcode

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codebeat

16
78
+ 1
0
Quantifiedcode

8
17
+ 1
5
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codebeat vs Quantifiedcode: What are the differences?

codebeat: Automated code review for Swift. codebeat helps you prioritize issues and identify quick wins. It provides immediate and continuous feedback on complexity and duplication; Quantifiedcode: 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.

codebeat and Quantifiedcode belong to "Code Review" category of the tech stack.

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Pros of codebeat
Pros of Quantifiedcode
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      Github integration
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    What is codebeat?

    codebeat helps you prioritize issues and identify quick wins. It provides immediate and continuous feedback on complexity and duplication

    What is Quantifiedcode?

    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.

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    What tools integrate with codebeat?
    What tools integrate with Quantifiedcode?
    What are some alternatives to codebeat and Quantifiedcode?
    SonarQube
    SonarQube provides an overview of the overall health of your source code and even more importantly, it highlights issues found on new code. With a Quality Gate set on your project, you will simply fix the Leak and start mechanically improving.
    Codacy
    Codacy automates code reviews to improve and standardize code quality across large enterprises. It identifies issues through static code analysis. Integrates with GitLab, GitHub & Bitbucket.
    ESLint
    A pluggable and configurable linter tool for identifying and reporting on patterns in JavaScript. Maintain your code quality with ease.
    Prettier
    Prettier is an opinionated code formatter. It enforces a consistent style by parsing your code and re-printing it with its own rules that take the maximum line length into account, wrapping code when necessary.
    Snyk
    Automatically find & fix vulnerabilities in your code, containers, Kubernetes, and Terraform
    See all alternatives
    Reviews of codebeat and Quantifiedcode
    Software Engineer at Gludo
    Review of
    Quantifiedcode

    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.