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Source channel @githubtrending · Post #15105 · Aug 30

#other This guide helps you prepare for software engineering technical interviews by covering key topics like good coding practices (SOLID principles, DRY, Clean Code, Clean Architecture), algorithms and data structures, design patterns, system design, databases, version control, CI/CD, containers, and AI tools. It offers practical resources and examples for many programming languages and frameworks, plus common interview questions for frontend and backend roles. Using this guide improves your coding skills, helps you understand important concepts, and boosts your confidence to perform well in interviews and real projects. It saves you time by gathering essential knowledge and practice materials in one place. https://github.com/DevCaress/guia-entrevistas-de-programacion

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djangoproject

@djangoproject · Post #206 · 12/06/2016, 03:28 PM

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http://www.enlistq.com/10-python-idioms-to-help-you-improve-your-code/ If you have ever tried to learn a new language (not a programming language), you know that we always think in our native language before we translate it to the new language. This can lead to you forming some sentences that don’t make sense in the new language but are perfectly normal in your native language. For example, in a lot of languages, you ‘open’ an electronic gadget such as fan, AC or cell phone. When you say that in English, it means to literally open the gadget instead of turning it on. The same is true for programming languages. As we pick up new languages, such as #python, we are using our prior knowledge of programming in another language (q, java, c++ etc) and translating that to python. Many times, your code will work but it won’t be ‘#pretty’ or #fast. In python terms, your code won’t be ‘#pythonic’.

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