Why is "1000000000000000 in range(1000000000000001)" so fast in Python 3?

Why is "1000000000000000 in range(1000000000000001)" so fast in Python 3? 🚀

Do you ever wonder why checking if a super large number is in a range using Python's range() function is lightning fast? How is it possible that regardless of the number of digits in the range, the calculation is almost instantaneous? 🤔

Let's dive into it and unravel the mystery behind the speed of range(). 💨

Understanding the concept of range() in Python 3 📚

First, let's clarify what the range() function actually is in Python 3. Unlike its predecessor in Python 2, range() in Python 3 is not a list. It is an object type that generates its contents on the fly, similar to a generator. This lazy evaluation makes it memory-efficient and allows us to work with large ranges without consuming excessive resources. 🤯

The magic behind the speed of range() ⚡️

Now, let's address our initial question. Why does checking if a quadrillion is in a range of a quadrillion and one values not take an inordinate amount of time? The answer lies in the clever optimization implemented in the range() object.

When evaluating whether a value is in a range(), Python's interpreter doesn't generate every single number in the range. Instead, it uses clever mathematics and optimizes the calculation process.

To check if a value is in the range, range() utilizes the mathematical property of arithmetic progression. It calculates the starting point, the step size, and performs simple arithmetic operations to determine if the value falls within the range without having to generate every single number.

This optimization allows range() to perform lightning-fast checks, regardless of the magnitude of the number or the length of the range. Whether you're checking for a billion, trillion, or quadrillion, the speed remains virtually the same – instantaneous! ⚡️✨

Comparing custom implementation with range() 🔄

Curious about what would happen if you implemented your own range function? Well, don't expect it to match range()'s lightning speed.

In the example function, my_crappy_range(), we see a straightforward implementation where values are generated incrementally using a while loop. While this implementation works, it lacks the mathematical optimizations that make range() so fast.

🤔 So, if you ever find yourself needing to work with massive ranges, stick with Python's built-in range() for optimal performance.

Engage with the community! 🌟

Python's range() is an incredibly powerful tool that can save you time and resources when working with large ranges. Now that you understand the magic behind its speed, don't hesitate to use it in your projects.

If you found this exploration of range() enlightening, share it with your friends and fellow Python enthusiasts. Let's spread the word about the hidden optimizations that make Python such a powerful language! 🙌

Remember, if you have any questions or want to contribute to the discussion, feel free to leave a comment below. Let's keep exploring the wonders of Python together! 🚀✨