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            About
            The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.
             
            
        
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            dotCover is a .NET unit testing and code coverage tool that works right in Visual Studio and in JetBrains Rider, helps you know to what extent your code is covered with unit tests, provides great ways to visualize code coverage, and is Continuous Integration ready. dotCover calculates and reports statement-level code coverage in applications targeting .NET Framework, .NET Core, Mono for Unity, etc. dotCover is a plug-in to Visual Studio and JetBrains Rider, giving you the advantage of analyzing and visualizing code coverage without leaving the code editor. This includes running unit tests and analyzing coverage results right in the IDEs, as well as support for different color themes, new icons and menus. dotCover comes bundled with a unit test runner that it shares with another JetBrains tool for .NET developers, ReSharper. dotCover supports continuous testing, a modern unit testing workflow whereby dotCover figures out on-the-fly which unit tests are affected by your code changes.
             
            
        
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            About
            gitStream lets you configure rules that decide how each pull request is treated based on the content of the code. These rules automatically find the right reviewer, check for deprecation, add context tags, and much more. The practice of improving merge efficiency by classifying pull requests based on change size and complexity. Automating the merge path based on the unique merge conditions allows work to flow more efficiently. gitStream adds context to your PRs with labels and comments. This added context empowers your developers to make the best decisions about how and when to work. Speed up time to merge by applying an auto-approve check on pull requests with simple changes like minor version updates of internal libraries. Automate change requests based on org. level coding practices like moving away from deprecated services.
             
            
        
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