Syllabus Lesson 65 of 141 · Data models that bend
Data models that bend

Flat is fine

Why it matters After four models that needed more structure, it is tempting to build a nested, indexed model for everything. For a small table that is read in new ways every week, a plain list of rows bends better than any structure.

A facilities team logs temperature readings as rows of (day, site, value), a few hundred a season. They keep asking new questions of it: per site this week, by date next week, "anything above 30?" after that. Every question is a filter over the same rows.

Your turn

Write load(rows) (returns your model), average(model, site) (mean value, or None if the site has no readings), between(model, start, end) (rows with start <= day < end) and above(model, level) (rows with value > level). Rows are (day, site, value) tuples; lists of rows keep the original order. Rule: your whole code may have at most 130 syntax nodes (code_size). There are a few hundred rows.

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