#!/usr/bin/env python3
"""Depth-aware single-step recipe scan at one exchange (saturation model v1, see docs/saturation-design.md).
For each recipe: buildings the market can absorb (N*), and ROI/day at N=1 and N* using a patient sell price
(not top-of-book) and ask-walked inputs. Excludes thin markets by default.

  tools/scan.py                              # AI1, all tiers, top 30 by ROI at N*
  tools/scan.py --cogc METALLURGY --tier S   # Deimos-like: metallurgy COGC, up to settlers
  tools/scan.py --sort total --min-n 3       # rank by absorbable profit/day
"""
import argparse, sys
from pathlib import Path
import yaml
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from puga import ROOT, config, econ, fio, market, saturation as sat

TIER_CODE = {"pioneer": "P", "settler": "S", "technician": "T", "engineer": "E", "scientist": "Sc"}
TIER_RANK = {"P": 0, "S": 1, "T": 2, "E": 3, "Sc": 4}


def load_state():
    p = ROOT / "state" / "company.yaml"
    return yaml.safe_load(p.read_text()) if p.exists() else {}


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--cx", default=config.DEFAULT_CX)
    ap.add_argument("--tier", help="max workforce tier: P S T E Sc")
    ap.add_argument("--cogc", help="COGC programme on the base, e.g. METALLURGY, or SETTLERS")
    ap.add_argument("--skip", default="", help="tiers left unstaffed, e.g. technician (no housing/wages; efficiency = staffed headcount share)")
    ap.add_argument("--experts", default="", help="expert counts, e.g. METALLURGY=2 (bonus x1.0306..1.284 for 1..5)")
    ap.add_argument("--hq", action="store_true", help="corp HQ bonus x1.1")
    ap.add_argument("--no-faction", action="store_true", help="ignore faction bonus from state/company.yaml")
    ap.add_argument("--min-n", type=float, default=1.0, help="min buildings the market absorbs (default 1)")
    ap.add_argument("--max-n", type=int, default=50, help="cap N* (capital/attention limit)")
    ap.add_argument("--budget", type=float, help="capital limit in AIC: caps N and drops recipes whose single-building capex exceeds it")
    ap.add_argument("--mcg", type=float, default=4.0, help="MCG per area (4 on normal planets)")
    ap.add_argument("--sort", default="roi", choices=["roi", "total", "roi1"])
    ap.add_argument("--top", type=int, default=30)
    ap.add_argument("--k", type=int, default=80, help="candidates refined with order books")
    ap.add_argument("--show-thin", action="store_true")
    a = ap.parse_args()

    snap = market.snapshot()
    Q = lambda t: snap.get((t, a.cx))
    ask = lambda t: (Q(t).ask if Q(t) else None)
    st = load_state()
    faction = None if a.no_faction else (st.get("company") or {}).get("faction")
    pu, pt = (st.get("permits") or {}).get("used", 1), (st.get("permits") or {}).get("total", 2)

    blds = {b["Ticker"]: b for b in fio.buildings()}
    mcg = ask("MCG") or 0

    def bcost(tk):
        b = blds[tk]
        parts = [(x["Amount"], ask(x["CommodityTicker"])) for x in b["BuildingCosts"]]
        if any(p is None for _, p in parts):
            return None
        return sum(n * p for n, p in parts) + a.mcg * b["AreaCost"] * mcg

    hab_head = {}
    for tier, hab in (("pioneer", "HB1"), ("settler", "HB2"), ("technician", "HB3"), ("engineer", "HB4"), ("scientist", "HB5")):
        c = bcost(hab)
        hab_head[tier] = None if c is None else c / econ.HAB_CAP[hab][tier]

    def wage(tier):  # per worker per day, both luxuries supplied, at ask
        tot = 0.0
        for tk, need, _, _ in econ.CONSUMPTION[tier]:
            p = ask(tk)
            if p is None:
                return None
            tot += need / 100 * p
        return tot

    experts = {k.strip().upper(): int(v) for k, v in (x.split("=") for x in a.experts.split(",") if "=" in x)}
    skip = {x.strip() for x in a.skip.split(",") if x.strip()}
    wages = {t: wage(t) for t in econ.TIERS}
    cands = []
    for rec in fio.recipes():
        b = blds.get(rec["BuildingTicker"])
        if not b or not rec["Outputs"] or b["Ticker"].startswith("HB"):
            continue
        heads = {t: b[t.capitalize() + "s"] for t in econ.TIERS}
        used = [t for t in econ.TIERS if heads[t] and t not in skip]   # staffed tiers
        if not used:
            continue
        top = TIER_CODE[used[-1]]
        if a.tier and TIER_RANK[top] > TIER_RANK[a.tier]:
            continue
        if any(hab_head[t] is None or wages[t] is None for t in used):
            continue
        ins = {i["Ticker"]: i["Amount"] for i in rec["Inputs"]}
        outs = {o["Ticker"]: o["Amount"] for o in rec["Outputs"]}
        if any(not Q(t) or not Q(t).ask for t in ins) or any(not Q(t) or not Q(t).bid for t in outs):
            continue
        bd = {t + "s": heads[t] for t in econ.TIERS}
        eff, _ = econ.building_efficiency(bd, {t: (0.0 if t in skip else 1.0) for t in econ.TIERS}, expertise=b["Expertise"] or None, cogc=a.cogc,
                                          hq=a.hq, experts=experts, faction=faction, permits_used=pu, permits_total=pt)
        io = econ.production_io([dict(time_ms=rec["TimeMs"], inputs=ins, outputs=outs)], eff, 1)
        # saturation per output
        n_lim, lim, thin, mm = float("inf"), "", False, {}
        for t, qo in io["out"].items():
            x = Q(t)
            tr = sat.tref(x.traded7, x.traded30)
            if x.mm_buy and x.bid and x.mm_buy >= 0.9 * x.bid:
                mm[t] = x.mm_buy          # market maker floor: unlimited depth at mm_buy
                continue
            thin |= sat.is_thin(tr, x.demand, qo)
            n = sat.n_out(tr, 0, x.demand, qo)      # stage 1: flow + demand only; queue penalty applied in stage 2 with the book
            if n < n_lim:
                n_lim, lim = n, t
        if n_lim == float("inf"):
            n_lim, lim = float(a.max_n), "MM"
        if (thin or n_lim < a.min_n) and not a.show_thin:
            continue
        capex = bcost(b["Ticker"])
        if capex is None:
            continue
        capex += sum(heads[t] * hab_head[t] for t in used)
        wcost = sum(heads[t] * wages[t] for t in used)
        price0 = {t: mm.get(t) or min(x for x in (Q(t).vwap7, Q(t).vwap30, Q(t).ask) if x) if (Q(t).vwap7 or Q(t).vwap30 or Q(t).ask) else Q(t).bid
                  for t in io["out"]}
        rough = sum(io["out"][t] * price0[t] for t in io["out"]) - sum(io["in"][t] * ask(t) for t in io["in"]) - wcost
        cands.append(dict(rec=rec, b=b, io=io, eff=eff, capex=capex, wcost=wcost, n_lim=n_lim, lim=lim, thin=thin, mm=mm,
                          rough_roi=100 * rough / capex, top=top, ins=ins, outs=outs))

    cands.sort(key=lambda c: c["rough_roi"], reverse=True)
    rows = []
    book = {}

    def asks_of(t):
        if t not in book:
            book[t] = sorted((o["ItemCost"], (o["ItemCount"] or 0)) for o in fio.order_book(t, a.cx)["SellingOrders"])
        return book[t]

    for c in cands[:a.k]:
        io, mm = c["io"], c["mm"]
        # stage 2: queue penalty from competing asks near market price only
        n2 = float("inf")
        for t, qo in io["out"].items():
            if t in mm:
                continue
            x = Q(t)
            se = sat.effective_supply(asks_of(t), x.vwap7 or x.ask)
            n2 = min(n2, sat.n_out(sat.tref(x.traded7, x.traded30), se, x.demand, qo))
        c["n_lim"] = float(a.max_n) if n2 == float("inf") else n2
        if c["n_lim"] < a.min_n and not a.show_thin:
            continue

        def evaluate(N):
            rev = 0.0
            for t, qo in io["out"].items():
                x = Q(t)
                if t in mm:
                    p = mm[t]
                else:
                    p = sat.p_patient(asks_of(t), sat.tref(x.traded7, x.traded30), N * qo, x.bid, x.vwap7, x.vwap30, x.ask)
                rev += N * qo * p
            cost = 0.0
            for t, qi in io["in"].items():
                w = market.walk(t, a.cx, N * qi, "buy")
                if w["short"]:
                    return None
                cost += w["total"]
            return rev - cost - N * c["wcost"]

        if a.budget and c["capex"] > a.budget:
            continue
        n_star = max(1, min(int(c["n_lim"]), a.max_n))
        if a.budget:
            n_star = max(1, min(n_star, int(a.budget // c["capex"])))
        net1 = evaluate(1)
        if net1 is None:
            continue
        netN = evaluate(n_star)
        while netN is None and n_star > 1:
            n_star = max(1, n_star // 2)
            netN = evaluate(n_star)
        if netN is None:
            continue
        rows.append(dict(roi1=100 * net1 / c["capex"], roiN=100 * netN / n_star / c["capex"], total=netN, n=n_star,
                         n_lim=c["n_lim"], lim=c["lim"], capex=c["capex"] * n_star, eff=c["eff"], bld=c["b"]["Ticker"],
                         top=c["top"], h=c["rec"]["TimeMs"] / 3.6e6, thin=c["thin"],
                         rec=" ".join(f"{v:g}{k}" for k, v in c["ins"].items()) + " -> " + " ".join(f"{v:g}{k}" for k, v in c["outs"].items())))
    key = {"roi": "roiN", "roi1": "roi1", "total": "total"}[a.sort]
    rows.sort(key=lambda r: r[key], reverse=True)
    print(f"# {a.cx}  tier<={a.tier or 'any'}  cogc={a.cogc or '-'}  faction={faction or '-'} ({pu}/{pt} permits)  min-n>={a.min_n}  sorted by {a.sort}")
    print("# price: patient asks near VWAP (clamped), inputs ask-walked; N* = market-absorbable buildings (cap %d); all estimates" % a.max_n)
    print(f"{'ROI@1':>6} {'ROI@N*':>7} {'N*':>4} {'lim':4} {'profit/d@N*':>11} {'capex@N*':>9} {'eff':>4} {'bld':4} {'tier':4} {'h':>5}  recipe")
    for r in rows[:a.top]:
        print(f"{r['roi1']:6.1f} {r['roiN']:7.1f} {r['n']:4d} {r['lim']:4} {r['total']:11.0f} {r['capex']:9.0f} {r['eff']*100:4.0f} {r['bld']:4} {r['top']:4} "
              f"{r['h']:5.1f}  {r['rec']}{'  [thin]' if r['thin'] else ''}")


if __name__ == "__main__":
    main()