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Quick Summary

Aggregate purchase logs to build per-user profiles tracking activity days, distinct order types, and spending ranges.
Filter users appearing on both days who have transacted in at least two different order categories.
Calculate a composite trust score based on historical order type familiarity and amount consistency relative to past min/max bounds.

What This Tests

Using hash maps and sets for efficient data aggregation and lookups.
Performing set intersections and filtering based on aggregated criteria.
Implementing mathematical scoring logic with bounds checking and percentage calculations.
Handling string-to-number conversion and lexicographical sorting.

Common Patterns

HashingSorting

Hint 1

Hint 2

What Interviewers May Ask Next

Report seen similar question in interview

python

Test Cases

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Output

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