Compute capacities after site closures
Company: Meta
Role: Data Engineer
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Technical Screen
You are given a nested dictionary redistribution where redistribution[closed_site][dest_site] equals the additional capacity required at dest_site if closed_site is shut down. The baseline capacity for each site s is baseline[s] = redistribution[s][s]. Given a set of closed sites C (possibly empty), compute and return a dictionary over the open sites O = AllSites − C with capacity[o] = baseline[o] + sum(redistribution[c][o] for c in C). Exclude closed sites from the output. For example, if C = {} return the baselines; if C = {'A'}, then capacity['B'] = baseline['B'] + redistribution['A']['B'] (e.g., 110 + 10 =
120).
Quick Answer: This question evaluates a candidate's ability to manipulate nested dictionary data structures and perform aggregate capacity computations, assessing data transformation, mapping, and set-based reasoning skills relevant to a Data Engineer within the Coding & Algorithms domain.
Given redistribution[closed][dest] and closed sites, return capacities for open sites.
Constraints
- Inputs are Python literals matching the function signature.
- Return a deterministic exact-match value.
Examples
Input: ({'A':{'A':100,'B':10}, 'B':{'A':5,'B':110}}, [])
Expected Output: {'A': 100, 'B': 110}
Explanation: No closures returns baselines.
Input: ({'A':{'A':100,'B':10}, 'B':{'A':5,'B':110}}, ['A'])
Expected Output: {'B': 120}
Explanation: A closure adds to B.
Hints
- Model object-style prompts as arrays or operation streams when needed.
- Handle empty and boundary cases before the main logic.