Account-overlap matrix with a partner, authored for STUD.com's own partner motion.

Rows are STUD.com's funnel stages, columns are the partner's; each cell is the deduped

intersection of account ids, totals are distinct unions per stage, and the biggest cell

is the first maximum in row-major order.

STAGES = ["prospects", "opportunities", "customers"]

def build_account_mapping_matrix(inp): normalize = str(inp.get("normalize_ids", "yes")) != "no"

def clean(values):
    out = set()
    for v in (values or []):
        s = str(v).strip().lower() if normalize else str(v)
        if s:
            out.add(s)
    return out

mine = {stage: clean((inp.get("mine") or {}).get(stage)) for stage in STAGES}
partner = {stage: clean((inp.get("partner") or {}).get(stage)) for stage in STAGES}

cells = []
for my_stage in STAGES:
    for partner_stage in STAGES:
        shared = sorted(mine[my_stage] & partner[partner_stage])
        cells.append({
            "mine": my_stage,
            "partner": partner_stage,
            "count": len(shared),
            "accounts": shared,
        })

all_mine = set().union(*mine.values())
all_partner = set().union(*partner.values())
row_totals = {stage: len(mine[stage] & all_partner) for stage in STAGES}
col_totals = {stage: len(partner[stage] & all_mine) for stage in STAGES}
biggest = max(cells, key=lambda c: c["count"])

return {
    "stages": list(STAGES),
    "cells": cells,
    "row_totals": row_totals,
    "col_totals": col_totals,
    "grand_total": len(all_mine & all_partner),
    "biggest_cell": {
        "mine": biggest["mine"],
        "partner": biggest["partner"],
        "count": biggest["count"],
    },
}