Built-in Functions Mastery (map, filter, zip, enumerate, any, all)

🌟 Introduction

"Python me aise kuch tools hote hain jo chhote dikhte hai, lekin kaam karte hain bade logon wale!

Aaj hum dekhenge 6 aise built-in functions jo har Python coder ko master karne chahiye."

Covered:

• map()
• filter()
• zip()
• enumerate()
• any()
• all()

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1️⃣ map() — The Transformer

nums = [1, 2, 3, 4]
squares = list(map(lambda x: x ** 2, nums))
# Output: [1, 4, 9, 16]

"Map function har item pe function apply karta hai. Clean, fast, aur memory-friendly!"

Real Use:

• String to float
• Discount logic
• Normalize data

Tips:

• Avoid if lambda gets too complex
• Prefer def in such case

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2️⃣ filter() — The Bouncer

nums = [1, 2, 3, 4, 5]
evens = list(filter(lambda x: x % 2 == 0, nums))
# Output: [2, 4]

"Filter unhi values ko rakhta hai jo condition me true return karti hai."

Combine with map:

squared_evens = list(map(lambda x: x**2, filter(lambda x: x%2==0, nums)))

Use:

• Remove blank entries
• Clean junk data

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3️⃣ zip() — The Zipper

names = ["A", "B", "C"]
marks = [90, 80, 70]
combined = list(zip(names, marks))
# [('A', 90), ('B', 80), ('C', 70)]

• Combines element-wise
• Shortest list wins

Unzip:

a, b = zip(*combined)

Use:

• Join columns
• Merge CSV

Tips:

• Use zip with *args to reverse!

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4️⃣ enumerate() — Index Manager

fruits = ["apple", "banana", "cherry"]
for idx, fruit in enumerate(fruits):
    print(f"{idx}: {fruit}")

Bonus:

enumerate(fruits, start=1)

Use:

• Index + item print
• Replace range(len(...)) loop

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5️⃣ any() & all() — Truth Checkers

any([False, False, True])  # True
all([True, True, False])   # False

Real Use:

• Form validation
• Checking if any user active

List Comp:

ages = [21, 34, 18]
all_adult = all([age >= 18 for age in ages])

Tip:

• Use any() with not for cleaner logic!

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🔥 Combine Like a Pro

students = ["ram", "shyam", "geeta"]
marks = [90, 45, 60]
result = list(filter(lambda x: x[1] >= 50, zip(students, marks)))
# [('ram', 90), ('geeta', 60)]

"Combination of zip + filter = superpower for tabular data!"

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⚠ Pitfalls & Best Practices

• Avoid complex logic in lambda
• Use list comprehension for readability
• Prefer map/filter with pure functions

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🧪 Practice Section

1. map() → Uppercase list of strings
2. filter() → Keep only prime numbers
3. zip() → Combine 3 lists: names, emails, phones
4. enumerate() → Index of vowels in string
5. any() → Check if any student failed
6. all() → All passwords ≥ 8 chars?

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🚀 WOW nice going!

"Ab aap Python ke built-in tools ke ninja ban gaye ho!

Inhe har codebase me use karo — clean, fast, elegant Python!"

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