Party Time Blocks

Given party intervals by neighborhood, compute party-time blocks and no-party gaps. The prompt emphasizes interval sorting, timestamp parsing, output-format precision, and production test design. Requirements Input describes party intervals grouped by neighborhood or block. For each neighborhood, find the party-time block boundaries: the earliest start and latest end for the active party interval group. Sort intervals by start_time before scanning. Find time ranges where no party is active. Time values may arrive as timestamp strings; one implementation detail is extracting the hour component with a helper such as get_hour rather than assuming a pre-parsed integer. Output format matters. One version expects an integer and dictionary-shaped output rather than a free-form list. Follow-up: design production unit tests for the implementation. Notes Treat this as an interval aggregation problem. The safe skeleton is: normalize timestamps, group by neighborhood, sort intervals by start, merge or scan active windows, then emit the requested gaps / blocks. The highest-risk part is not the algorithm; it is reading the output contract exactly and normalizing timestamps consistently. If the interviewer asks for production readiness, cover boundary tests: empty input, single interval, touching intervals, overlapping intervals, malformed timestamps, unsorted input, and multiple neighborhoods. Preparation Practice a standard interval-merge implementation and a gap-finding scan from sorted intervals. Write a small timestamp-normalization helper and test it before integrating it into the interval scan. Prepare a compact unit-test matrix that covers overlap, adjacency, gaps, and output-shape validation.