Interview Experience
Problem
Given a list of 5 card strings (e.g., "AS", "10H", "KD"), classify the poker hand. Cards are rank + suit where rank is one of A,2,3,...,10,J,Q,K and suit is C,D,H,S.
Return the hand rank as a string:
"royal_flush", "straight_flush", "four_of_a_kind", "full_house", "flush", "straight", "three_of_a_kind", "two_pair", "one_pair", "high_card"
python
def classify_hand(cards: list[str]) -> str:
...
Example:
classify_hand(["10H","JH","QH","KH","AH"]) -> "royal_flush"
classify_hand(["2C","2D","2H","3S","3C"]) -> "full_house"
classify_hand(["AS","2C","3D","4H","5S"]) -> "straight"
Note: Ace can be low (A-2-3-4-5) or high (10-J-Q-K-A).
Follow-ups
- How do you handle the low-ace straight edge case cleanly?
- Extend to compare two hands and return the winner, including tiebreakers (e.g., higher pair wins).
- What changes if the game uses a 54-card deck with 2 Jokers that act as wild cards?
Full Details
Problem
Given a list of 5 card strings (e.g., "AS", "10H", "KD"), classify the poker hand. Cards are rank + suit where rank is one of A,2,3,...,10,J,Q,K and suit is C,D,H,S.
Return the hand rank as a string:
"royal_flush", "straight_flush", "four_of_a_kind", "full_house", "flush", "straight", "three_of_a_kind", "two_pair", "one_pair", "high_card"
python
def classify_hand(cards: list[str]) -> str:
...
Example:
classify_hand(["10H","JH","QH","KH","AH"]) -> "royal_flush"
classify_hand(["2C","2D","2H","3S","3C"]) -> "full_house"
classify_hand(["AS","2C","3D","4H","5S"]) -> "straight"
Note: Ace can be low (A-2-3-4-5) or high (10-J-Q-K-A).
Follow-ups
- How do you handle the low-ace straight edge case cleanly?
- Extend to compare two hands and return the winner, including tiebreakers (e.g., higher pair wins).
- What changes if the game uses a 54-card deck with 2 Jokers that act as wild cards?
About This Question
This is a candidate experience report from a codesignal interview.
It covers the following topics: Q3, Coding, General Coding Assessment, Strings .
Topics
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About Codesignal Interview Reports
This question was reported by a candidate who interviewed at Codesignal. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.
Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Codesignal are the higher-signal extractions to take from this report.
For broader preparation context, the Codesignal interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.
How To Practice This Type of Question
Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.
Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Codesignal reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Codesignal Round
Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.
The single most predictive failure mode in Codesignal reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.