06. Comprehensions & The Walrus Operator (:=) for High Performance • Python 0-to-Hero Mastery (Big Tech SDE & ML Standard) • Rishabh Ki Kaksha

*   **List Comprehension:** `[x**2 for x in range(10) if x % 2 == 0]` (C-level bytecode loop, 30% faster than `for` loop with `.append()`).
*   **Dict Comprehension:** `{user['id']: user['name'] for user in user_list}`.
*   **Set Comprehension:** `{word.lower() for word in text_stream}`.

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### 2. The Walrus Operator (`:=` Assignment Expression) 🦭

Allows assigning variables directly inside expressions (Avoids duplicate function calls!):

```python
# Without Walrus (Calls heavy_calculation() twice):
results = [heavy_calculation(x) for x in data if heavy_calculation(x) > 100]

# With Walrus Operator (Calculates ONLY ONCE!):
results = [res for x in data if (res := heavy_calculation(x)) > 100]
```

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### 3. Interview Ke 3 Sawal Is Topic Se

1. **List Comprehension vs Generator Expression `(x for x in data)` me memory difference kya hai?** -> List comprehension poori list RAM me instantiate karta hai ($O(N)$ memory); Generator expression lazy iterator yield karta hai ($O(1)$ constant memory).
2. **List comprehension me variable leak (Python 2 vs 3) kaise fix hua?** -> Python 3 me comprehensions ke paas apna dedicated function scope hota hai, isliye loop variable outer scope ko overwrite nahi karta.
3. **Nested comprehension readability best practice kya hoti hai?** -> Max 2 levels of nesting allow karni chahiye; usse complex hone par standard `for` loops ya generator functions use karne chahiye.

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**Next Topic:** 07. First-Class Functions, *args, **kwargs & Functional Combinators

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🎯 Big Tech Coding & Interview Challenges

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1 Questions

Easy

1. Walrus Optimized Data Filter

Ek function `filter_heavy_tasks(tasks)` likhein jo walrus operator ka use karke expensive calculation ko cache kare.

💡 View Pro Interview Hint

• Use `(n := len(item)) > threshold`.

Python 3.12

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🎯 Big Tech Coding & Interview Challenges

1. Walrus Optimized Data Filter

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Rishabh Gehlot

PHP 8+ & Laravel 11 Master Track