mypy VS Gitential
Compare mypy VS Gitential and see what are their differences
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mypy
PyLint
flake8
PyFlakes
PyCharm
SonarQube
PyChecker
PEP8
Gitential
GitPrime
Teamplify
Waydev
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Haystack Analytics
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Code Climate Velocity
mypy GitentialBased on our record, mypy seems to be a lot more popular than Gitential. While we know about 49 links to mypy, we've tracked only 3 mentions of Gitential. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I’m not here to tell people which languages they should love. But if you do find yourself writing production code in a dynamically typed language like Python, Ruby, or JavaScript, I would give serious consideration to opting into the type-checking tools that have become available in those ecosystems. In Python, consider requiring type hints and adding mypy checks to your CI to move your type safety bugs forward... - Source: dev.to / 28 days ago
Mypy is "an optional static type checker for Python that aims to combine the benefits of dynamic (or "duck") typing and static typing". As Python is dynamically typed, Mypy adds an extra layer of safety by checking types at compile time (based on type annotations conforming to PEP 484), catching potential errors before runtime. - Source: dev.to / 6 months ago
Mypy stands as an essential static type-checking tool. Its primary function is to verify the correctness of types in your codebase. However, manually annotating types in legacy code can be laborious and time-consuming. - Source: dev.to / 8 months ago
Lua is a great language for embedding, but one thing I wish it had was some form of optional type annotations that could be checked by a linter. Something like mypy for Lua would be super-useful. Source: about 1 year ago
Python is a dynamically typed language (unlike C or java which are statically typed) meaning that there's no enforcement on the type. This var ; type syntax is called Type Hints, and they are just that, merely hints. So they serve as a reminder to developers of what types of variables a function should receive and output, but they implement no real restrictions. So if you try to pass a string to collatz for... Source: about 1 year ago
Gitential.com — Software Development Analytics platform. Free: unlimited public repositories, unlimited users, free trial for private repos. On-prem version available for enterprise. - Source: dev.to / almost 3 years ago
There are additional analytics you can see on git activities using this tool: https://gitential.com/. Completely free for a couple of repos and developers, like for university projects and small companies. Source: about 3 years ago
I'm validating if you are having the same challenges with your projects, and if this is an analytics you would use to boost efficiency with your teams. Here is the link to check it out: https://gitential.com/. Source: about 3 years ago
PyLint - Pylint is a Python source code analyzer which looks for programming errors.
GitPrime - GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
flake8 - A wrapper around Python tools to check the style and quality of Python code.
Teamplify - Team Management for developers. Simplified and automated
PyFlakes - A simple program which checks Python source files for errors.
Waydev - Waydev analyzes your codebase from Github, Gitlab, Azure DevOps & Bitbucket to help you bring out the best in your engineers work.