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Are you a Python programmer who has already mastered the basics and are looking to move on to some less obvious yet useful skills to add to your repertoire?
Perhaps you already know how to use lists. Maybe you are now skilled at creating functions. Conceivably you can control your program's execution flow with ease. Perchance you posess the requisite knowledge of Python's type system and what types to use when. At this point, you just desire some more advanced Python tricks.
If this sounds like you, you might find the free ebook 10 Practical Python Programming Tricks: Boost Your Efficiency and Code Quality to be useful.
Embrace these tips to enhance your Python programming skills and stand out as a proficient developer who can create high-quality, performant applications with ease.
A product of Data Science Horizons, this free ebook covers the following topics, in an effort to help boost the reader's efficiency and code quality:
- List Comprehensions
- Lambda Functions
- The Walrus Operator (Assignment Expressions)
- Itertools Module
- F-strings (Formatted String Literals)
- Context Managers and the 'with' Statement
- Generators and Generator Expressions
- Decorators
- Type Hints and Static Type Checking
- Python One-Liners
As the title alludes to, along with the demonstrating of the skills listed above, this ebook focuses on both efficiency and quality of code:
Writing efficient code means optimizing your code's execution speed and minimizing resource consumption, such as memory usage. Clean coding, on the other hand, focuses on readability, maintainability, and organization. Both aspects go hand-in-hand, as efficient code is easier to understand, debug, and modify, while clean code inherently leads to better performance. By adopting the best practices outlined in this ebook, you'll be better equipped to write high-quality Python code that is not only fast and resource-efficient but also easy to understand and modify.
Take a look at the free ebook 10 Practical Python Programming Tricks: Boost Your Efficiency and Code Quality today if you are ready to take your Python programming to the next level. It may just be what you are looking for.
Matthew Mayo (@mattmayo13) is a Data Scientist and the Editor-in-Chief of KDnuggets, the seminal online Data Science and Machine Learning resource. His interests lie in natural language processing, algorithm design and optimization, unsupervised learning, neural networks, and automated approaches to machine learning. Matthew holds a Master's degree in computer science and a graduate diploma in data mining. He can be reached at editor1 at kdnuggets[dot]com.
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