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Python class names follow the CapWords convention, ensuring code is readable, maintainable, and professional for teams and solo developers.
Regular classes require manual boilerplate code; dataclasses reduce redundancy with decorators. Use dataclasses for simple data storage and regular classes for complex behaviors.
Learn how to create sets in Python efficiently using concise and readable set comprehensions, improving code quality and Pythonic style.
Dictionary comprehensions in Python enable clean, efficient dictionary creation in one line, improving readability and performance compared to loops.
List comprehensions in Python create new lists by applying expressions to iterables with optional conditions, making code more readable and efficient.
Learn key Python idioms for clearer, efficient, and more maintainable code, including elegant iteration and looping techniques.
Pythonic code embraces Python's philosophy for elegance, readability, and efficiency. It follows best practices and idioms to make programs intuitive and well-designed.