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As one of the most popular languages, Python is the choice of language for many first-time coding learners. Its open-source, general-purpose, platform-independent nature has engendered probably the most active developer community that results in tens of thousands of freely available packages and libraries for web development, machine learning (ML), data science, and many other specialties. No matter whether you just started with Python or learning to program in general, I hope that we share the same belief: we’ve entered an era in which knowing to code in Python gives you a tremendous advantage — you’re having access to numerous tools that Python has to offer.

In the Python ecosystem, we use domain-specific Python tools, such as web frameworks and ML libraries, to address specific tasks in our jobs. The effective employment of these Python tools is nontrivial, as it requires a considerable breadth of familiarity with essential Python skills in performing a variety of tasks, such as processing texts, dealing with structured data, creating control flows, and handling files. Python programmers can write different versions of code to address the same tasks. Among these versions, one of them is probably better than others, because it may be more concise, more readable, and more efficient, which we term as “Pythonic”, an idiomatic coding style that all Python programmers strive to acquire. It is what this book is about — how to write Pythonic code to address common programming tasks.