## Why 2-√2×√2 ≠ 0 in Python: A Tale of Floating-Point Frustration
Have you ever coded in Python and gotten a surprising result? Let's say you try this:
```python
x=2
result = x - (2**.5) * (2**.5)
print(result)
You might expect the answer to be zero, since 2**(1/2) times itself is 2 , and 2 minus itself is zero, right? ➖ But hold on! Python might print something like:
```
0.0000000000000004
```
What's going on here? The culprit is something called **floating-point arithmetic**. Computers store numbers in a special way, kind of like having a limited number of decimal places for everything. This means super precise numbers like the square root of 2 can't be stored perfectly.
In this case, that tiny imperfection in storing √2 gets carried over when we subtract it from 2. The result is a small, non-zero value. It's like trying to perfectly measure ingredients with a teaspoon – there's always a little leftover!
**Key points to remember:**
* Floating-point math is super useful, but it's not perfect for ultra-precise calculations.
* Not all calculations will equal exactly what you expect.
* For super precise work, there are special Python libraries designed for high-accuracy math.
So next time you see a surprising result in Python, remember the floating-point gremlins might be at play! Just a sprinkle of awareness can help you understand what's going on behind the scenes.

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