Review of Grok's Python interview snippets#

Reviewed 7 September 2026 against the current grok_python_snippets.md and your 12-week L4/L5 preparation plan.

Verdict: broad, useful coverage, but correct the issues below before using it as a typing reference. Graphs, heaps, binary search, tries, backtracking, and LRU are substantially covered. The main gaps are complete, reusable implementations of some window, DP, and tree patterns, plus several incorrect explanations.

This review records findings and suggested corrections; it does not rewrite the original file. Line links refer to the version reviewed.

What was validated#

• Read all 26 numbered sections and examined all 36 Python code fences.
• Ran 16,118 passing checks on Python 3.12.14, including randomized comparisons of binary-search boundaries against bisect, Dijkstra and 0–1 BFS against Floyd–Warshall, union-find connectivity against BFS, permutations against itertools, and both LRU implementations against an OrderedDict model.
• Checked representative trie, linked-list reversal, subset, topological-sort, and nonempty-target minimum-window examples.
• Separately reproduced the failures listed below. Passing checks do not mean the whole document passes or every fragment is complete.
• Standalone compilation found three invalid fences: function-body fragments with top-level return at lines 245 and 641, and the deliberately bad mutable-default example with no body at line 1139. The first two are usable when wrapped in functions; the third should be commented out or made a complete bad example. Treat these as presentation/completeness issues, not three incorrect algorithms.
• Checked version-sensitive Python claims against the official documentation linked below.

Fix these first#

Correct the explanations as well#

1. The next-greater stack is non-increasing in value, not increasing. Lines 391–402: after popping smaller values, the survivors run from larger to smaller from bottom to top. Equal values can remain because the condition is <. The next-greater code itself is correct. For a strict previous-greater variant, define the traversal and pop <= before reading the surviving top.

2. Dijkstra works on 0/1-weight graphs. Line 674 incorrectly says it is not for those weights. They are nonnegative, so they satisfy its precondition; 0–1 BFS is a faster specialized alternative. The supplied Dijkstra passed randomized 0/1-weight comparisons. Add complexity for this lazy-heap implementation: O(V + E log(E+1)) time and O(V+E) auxiliary storage in the general case; the familiar O((V+E) log V) expression assumes the usual simple-graph setting.

3. A deque has no pop(0). Line 531 suggests deserializing with it. That raises TypeError; use popleft() or next(tokens) on an iterator.

4. The lower-bound answer is not always in [lo, hi). Line 226: the search maintains an unresolved element interval, but the answer can equal hi, including sentinel n. A clean invariant is: all indices below lo contain values < target; all indices at or above hi contain values >= target; the insertion boundary lies in [lo, hi]. The actual lower-bound code is correct.

5. heapq gained public max-heap functions in Python 3.14. Line 125 is accurate for the older-runtime approach but wrong as an unqualified current statement. Keep negation as a portable template; label the runtime and mention heapify_max, heappush_max, and heappop_max for 3.14+. Official heap documentation

6. Lists are not inherently unorderable. Line 155: numeric lists compare lexicographically, so (1, [1]) < (1, [2]) is valid. Custom nodes usually have no ordering. Keep the unique tie-breaker advice, but explain that it avoids comparing arbitrary payloads, including mixed or otherwise unorderable contents. Python sequence comparisons

7. isdigit() does not guarantee int(ch) works. Line 991: '²'.isdigit() is true, but int('²') raises ValueError. For an ASCII calculator use '0' <= ch <= '9'; otherwise define the Unicode input contract. Python character classification

8. Raising the recursion limit is not a general solution. Line 19: the usable depth is platform-dependent; an excessively high limit can crash the process. Prefer iterative traversal for long chains. Use sys.getrecursionlimit() rather than treating 1,000 as a universal setting. Python recursion-limit documentation

9. Restoring cells after each DFS is not interchangeable with island visitation. Line 621: restoration is appropriate for path backtracking such as word search. An island-counting outer loop must retain global visitation; otherwise it rediscovers the same component. To preserve the input, use a separate visited set or traverse a copied grid.

10. LCA needs a presence contract. Line 506 assumes both target node references exist. If one is absent it can return the other node, which is not a valid “both nodes present” LCA result. State the assumption or validate presence.

11. The fixed-window code is not O(n). Line 299 allocates a length-k slice for every window: Θ((n-k+1)k) time and O(k) transient space. The prose warns about this, but the main recall snippet should show a running aggregate.

12. Make heap-selection complexity conditional. Line 92: Counter.most_common(k) has different paths for different k; “always heap internally” is too strong. For N input values and U distinct keys, describe frequency construction plus selection as expected O(N + U log(k+1)) for a small bounded k, with sorting when selecting all. Likewise, nlargest(1, ...) is linear, not literally O(n log 1). Official selection guidance

What is missing or only partially implemented#

These priorities reflect your preparation plan, not an official Google frequency ranking. Do not add every advanced algorithm merely to increase the document's length.

Memoization reference: Python functools documentation.

Small corrections you can apply directly#

At-most-k-distinct window#

from collections import Counter

def longest_at_most_k_distinct(s, k):
    if k <= 0:
        return 0
    counts = Counter()
    left = best = 0
    for right, ch in enumerate(s):
        counts[ch] += 1
        while len(counts) > k:
            old = s[left]
            counts[old] -= 1
            if counts[old] == 0:
                del counts[old]
            left += 1
        best = max(best, right - left + 1)
    return best

Expected O(n) time and O(min(alphabet size, k+1)) auxiliary space.

LCS with the correct boundaries#

def lcs(a, b):
    dp = [[0] * (len(b) + 1) for _ in range(len(a) + 1)]
    for i in range(1, len(a) + 1):
        for j in range(1, len(b) + 1):
            if a[i - 1] == b[j - 1]:
                dp[i][j] = dp[i - 1][j - 1] + 1
            else:
                dp[i][j] = max(dp[i - 1][j], dp[i][j - 1])
    return dp[-1][-1]

O(mn) time and O((m+1)(n+1)) allocated space. Empty prefixes have LCS zero.

Empty-tree-safe level order#

from collections import deque

def level_order(root):
    if root is None:
        return []
    result, queue = [], deque([root])
    while queue:
        level = []
        for _ in range(len(queue)):
            node = queue.popleft()
            level.append(node.val)
            if node.left is not None:
                queue.append(node.left)
            if node.right is not None:
                queue.append(node.right)
        result.append(level)
    return result

O(n) time and O(maximum width) auxiliary queue space, excluding output.

Integer-only division#

def trunc_div(a, b):
    # Integer inputs, b != 0; truncates toward zero without float conversion.
    quotient = abs(a) // abs(b)
    return -quotient if (a < 0) != (b < 0) else quotient

def ceil_div(a, b):
    # Integer inputs, b > 0; a may be negative.
    return -(-a // b)

Python integer operation costs grow with operand size; arbitrary precision does not imply constant-time arithmetic for arbitrarily large values.

Interview advice to soften#

• Line 3: “No comments unless asked” is not a useful general rule. A short invariant or state-definition comment can help; avoid narrating every assignment.
• Line 836: “n > 12 means backtracking is probably wrong” confuses permutations with subsets and ignores pruning/output size. Thirteen distinct elements have 8,192 subsets; that is very different from 13! permutations.
• Line 1195: do not always write return 0 for empty input; the correct result depends on the contract. Clarify before committing to a stub or return type.
• Line 1221: twelve substantial templates do not make a realistic ten-minute typing drill. Rotate two or three per session; keep the final day light.
• Treat “90% of Google DSA,” universal interviewer behaviors, company-specific acceptance statements, and hard input-size/time cutoffs as unsupported coaching heuristics, not documented hiring rules. Input size is one factor alongside operations, runtime, and time limit.

Recommended next edit order#

1. Correct LCS, windows, empty-tree handling, serializer, dynamic union-find, and division examples.
2. Fix the stack, Dijkstra, binary-search, and Python API explanations.
3. Add the high-priority missing implementations above.
4. Give each executable template a signature, input assumptions, return convention, mutation behavior, time/space analysis, and two or three boundary examples.
5. Retest extracted functions separately; give graph nodes and cache nodes different names if combining snippets into one module.