Question 1

What is the difference between a list and a tuple in Python?

Accepted Answer

List: Mutable, []; tuple: immutable, (). Why it matters: Mutability drives use—lists for collections that change; tuples for fixed data, dict keys (hashable), multiple return values. Performance: Tuples are slightly faster (less overhead, fixed size). Hashability: Tuples can be dict keys/set members; lists cannot. In data pipelines: Tuples for schema-like rows (column names); lists for buffers, accumulators....

Question 2

Explain the difference between shallow copy and deep copy in Python.

Accepted Answer

Shallow (copy.copy()): New top-level object; nested objects are references. Nested mutations affect original. Deep (copy.deepcopy()): Recursive copy; fully independent. Why it matters: Shallow is O(n) for top level only; deep is O(n) for entire structure—can be slow for large nested dicts. Use shallow when: No nested mutables or shared refs OK. Use deep when: Need full isolation (e.g., config that will be modified)....

Question 3

Write a Python function to find the first non-repeating character in a string.

Accepted Answer

Approach: Two-pass—count chars, then find first with count 1. Code: def first_non_repeating(s): counts = {}; [counts.update({c: counts.get(c, 0) + 1}) for c in s]; return next((c for c in s if counts[c] == 1), None). Or: from collections import Counter; counts = Counter(s); return next((c for c in s if counts[c] == 1), None). Complexity: O(n) time, O(k) space. Why: Single pass can't know if char is unique until full scan....

Question 4

What are decorators in Python, and how do they work?

Accepted Answer

Decorator: Higher-order function that wraps another function; @decorator syntax. Implementation: def timer(f): def wrapper(*args, **kwargs): start=time(); r=f(*args,**kwargs); print(time()-start); return r; return wrapper. Why: Cross-cutting concerns—logging, retries, auth, caching—without cluttering business logic. In data pipelines: @retry, @logged, @rate_limited on API fetchers. Scalability: Decorators add indirection; overuse can make stack traces deep....

Question 5

Explain the difference between args and kwargs in Python.

Accepted Answer

*args: Variable positional args, received as tuple. **kwargs: Variable keyword args, received as dict. Why: Flexible signatures—wrappers, decorators, config-driven functions. Example: def run_pipeline(*sources, **config): ... allows run_pipeline('s3://a','s3://b', parallelism=4). Order: (regular, *args, keyword-only, **kwargs). Pitfall: Passing through—func(*args, **kwargs)—preserves interface. In data pipelines: **kwargs for optional connector params (region, timeout, retries)....

Question 6

Write a Python function to find the first non-repeating character in a string.

Accepted Answer

**Approach**: Two-pass—first pass counts characters; second pass finds first with count 1. Preserves order of first occurrence. **Code**: def first_non_repeating(s): counts = {}; for c in s: counts[c] = counts.get(c, 0) + 1; return next((c for c in s if counts[c] == 1), None). Alternative with Counter: def first_non_repeating(s): from collections import Counter; cnt = Counter(s); return next((c for c in s if cnt[c] == 1), None). **Complexity**: O(n) time, O(k) space (k = unique chars)....

Question 7

How would you implement a program to determine the frequency of each letter in a string?

Accepted Answer

**Code:** `Counter(c.lower() for c in s if c.isalpha())`. Or defaultdict. O(n). **Why:** Character analysis. **Production:** Unicode handling.

Question 8

Implement a program to find the intersection of two lists.

Accepted Answer

**Code:** list(set(a)&set(b)). O(n+m). **With duplicates:** Counter; (c1&c2).elements(). **Why:** Set membership. **Production:** Preserve order if needed.

Question 9

Implement a program to remove duplicates from a list while maintaining order.

Accepted Answer

**Code:** seen=set(); [x for x in lst if not (x in seen or seen.add(x))]. Or list(dict.fromkeys(lst)). O(n). **dict.fromkeys** fastest Py3.7+. **Why:** Order preservation. **Production:** Hashable elements.

Question 10

Write a Python code that determines if all the people in their seats can see the screen in the theatre.

Accepted Answer

**Modeling:** Front row always sees. A person is blocked if someone in front (same column, closer to screen) is taller. So per column, heights must be non-decreasing back-to-front.

**Check:** For each column, iterate rows front-to-back; if height decreases, someone is blocked....

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