Initial PuGa toolkit: data layer, econ, depth-aware scan, state sync, plan push
- puga/: cached FIO + PRUNplanner clients, market view with order-book walk, econ formulas ported from PRUNplanner (tested against its suite and live FIO), saturation model v1 (reviewed by Opus) - tools/: scan (depth-aware), price, book, chain, state sync, plan_push (dry run default, [PuGa]-prefixed plans only), legacy prun_scan/prun_cxarb - docs/: mechanics (PRUNplanner is source of truth), roadmap, decisions, saturation design, archived handoff - secrets stay in .env (gitignored); ref/ holds PRUNplanner source (ignored) Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Claude Sonnet 5
Executable
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#!/usr/bin/env python3
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"""Depth-aware single-step recipe scan at one exchange (saturation model v1, see docs/saturation-design.md).
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For each recipe: buildings the market can absorb (N*), and ROI/day at N=1 and N* using a patient sell price
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(not top-of-book) and ask-walked inputs. Excludes thin markets by default.
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tools/scan.py # AI1, all tiers, top 30 by ROI at N*
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tools/scan.py --cogc METALLURGY --tier S # Deimos-like: metallurgy COGC, up to settlers
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tools/scan.py --sort total --min-n 3 # rank by absorbable profit/day
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"""
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import argparse, sys
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from pathlib import Path
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import yaml
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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from puga import ROOT, config, econ, fio, market, saturation as sat
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TIER_CODE = {"pioneer": "P", "settler": "S", "technician": "T", "engineer": "E", "scientist": "Sc"}
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TIER_RANK = {"P": 0, "S": 1, "T": 2, "E": 3, "Sc": 4}
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def load_state():
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p = ROOT / "state" / "company.yaml"
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return yaml.safe_load(p.read_text()) if p.exists() else {}
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--cx", default=config.DEFAULT_CX)
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ap.add_argument("--tier", help="max workforce tier: P S T E Sc")
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ap.add_argument("--cogc", help="COGC programme on the base, e.g. METALLURGY, or SETTLERS")
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ap.add_argument("--skip", default="", help="tiers left unstaffed, e.g. technician (no housing/wages; efficiency = staffed headcount share)")
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ap.add_argument("--experts", default="", help="expert counts, e.g. METALLURGY=2 (bonus x1.0306..1.284 for 1..5)")
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ap.add_argument("--hq", action="store_true", help="corp HQ bonus x1.1")
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ap.add_argument("--no-faction", action="store_true", help="ignore faction bonus from state/company.yaml")
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ap.add_argument("--min-n", type=float, default=1.0, help="min buildings the market absorbs (default 1)")
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ap.add_argument("--max-n", type=int, default=50, help="cap N* (capital/attention limit)")
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ap.add_argument("--budget", type=float, help="capital limit in AIC: caps N and drops recipes whose single-building capex exceeds it")
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ap.add_argument("--mcg", type=float, default=4.0, help="MCG per area (4 on normal planets)")
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ap.add_argument("--sort", default="roi", choices=["roi", "total", "roi1"])
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ap.add_argument("--top", type=int, default=30)
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ap.add_argument("--k", type=int, default=80, help="candidates refined with order books")
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ap.add_argument("--show-thin", action="store_true")
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a = ap.parse_args()
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snap = market.snapshot()
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Q = lambda t: snap.get((t, a.cx))
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ask = lambda t: (Q(t).ask if Q(t) else None)
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st = load_state()
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faction = None if a.no_faction else (st.get("company") or {}).get("faction")
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pu, pt = (st.get("permits") or {}).get("used", 1), (st.get("permits") or {}).get("total", 2)
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blds = {b["Ticker"]: b for b in fio.buildings()}
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mcg = ask("MCG") or 0
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def bcost(tk):
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b = blds[tk]
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parts = [(x["Amount"], ask(x["CommodityTicker"])) for x in b["BuildingCosts"]]
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if any(p is None for _, p in parts):
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return None
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return sum(n * p for n, p in parts) + a.mcg * b["AreaCost"] * mcg
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hab_head = {}
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for tier, hab in (("pioneer", "HB1"), ("settler", "HB2"), ("technician", "HB3"), ("engineer", "HB4"), ("scientist", "HB5")):
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c = bcost(hab)
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hab_head[tier] = None if c is None else c / econ.HAB_CAP[hab][tier]
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def wage(tier): # per worker per day, both luxuries supplied, at ask
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tot = 0.0
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for tk, need, _, _ in econ.CONSUMPTION[tier]:
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p = ask(tk)
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if p is None:
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return None
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tot += need / 100 * p
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return tot
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experts = {k.strip().upper(): int(v) for k, v in (x.split("=") for x in a.experts.split(",") if "=" in x)}
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skip = {x.strip() for x in a.skip.split(",") if x.strip()}
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wages = {t: wage(t) for t in econ.TIERS}
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cands = []
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for rec in fio.recipes():
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b = blds.get(rec["BuildingTicker"])
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if not b or not rec["Outputs"] or b["Ticker"].startswith("HB"):
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continue
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heads = {t: b[t.capitalize() + "s"] for t in econ.TIERS}
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used = [t for t in econ.TIERS if heads[t] and t not in skip] # staffed tiers
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if not used:
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continue
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top = TIER_CODE[used[-1]]
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if a.tier and TIER_RANK[top] > TIER_RANK[a.tier]:
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continue
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if any(hab_head[t] is None or wages[t] is None for t in used):
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continue
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ins = {i["Ticker"]: i["Amount"] for i in rec["Inputs"]}
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outs = {o["Ticker"]: o["Amount"] for o in rec["Outputs"]}
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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):
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continue
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bd = {t + "s": heads[t] for t in econ.TIERS}
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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,
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hq=a.hq, experts=experts, faction=faction, permits_used=pu, permits_total=pt)
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io = econ.production_io([dict(time_ms=rec["TimeMs"], inputs=ins, outputs=outs)], eff, 1)
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# saturation per output
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n_lim, lim, thin, mm = float("inf"), "", False, {}
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for t, qo in io["out"].items():
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x = Q(t)
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tr = sat.tref(x.traded7, x.traded30)
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if x.mm_buy and x.bid and x.mm_buy >= 0.9 * x.bid:
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mm[t] = x.mm_buy # market maker floor: unlimited depth at mm_buy
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continue
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thin |= sat.is_thin(tr, x.demand, qo)
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n = sat.n_out(tr, 0, x.demand, qo) # stage 1: flow + demand only; queue penalty applied in stage 2 with the book
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if n < n_lim:
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n_lim, lim = n, t
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if n_lim == float("inf"):
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n_lim, lim = float(a.max_n), "MM"
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if (thin or n_lim < a.min_n) and not a.show_thin:
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continue
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capex = bcost(b["Ticker"])
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if capex is None:
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continue
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capex += sum(heads[t] * hab_head[t] for t in used)
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wcost = sum(heads[t] * wages[t] for t in used)
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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
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for t in io["out"]}
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rough = sum(io["out"][t] * price0[t] for t in io["out"]) - sum(io["in"][t] * ask(t) for t in io["in"]) - wcost
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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,
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rough_roi=100 * rough / capex, top=top, ins=ins, outs=outs))
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cands.sort(key=lambda c: c["rough_roi"], reverse=True)
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rows = []
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book = {}
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def asks_of(t):
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if t not in book:
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book[t] = sorted((o["ItemCost"], (o["ItemCount"] or 0)) for o in fio.order_book(t, a.cx)["SellingOrders"])
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return book[t]
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for c in cands[:a.k]:
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io, mm = c["io"], c["mm"]
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# stage 2: queue penalty from competing asks near market price only
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n2 = float("inf")
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for t, qo in io["out"].items():
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if t in mm:
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continue
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x = Q(t)
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se = sat.effective_supply(asks_of(t), x.vwap7 or x.ask)
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n2 = min(n2, sat.n_out(sat.tref(x.traded7, x.traded30), se, x.demand, qo))
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c["n_lim"] = float(a.max_n) if n2 == float("inf") else n2
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if c["n_lim"] < a.min_n and not a.show_thin:
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continue
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def evaluate(N):
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rev = 0.0
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for t, qo in io["out"].items():
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x = Q(t)
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if t in mm:
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p = mm[t]
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else:
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p = sat.p_patient(asks_of(t), sat.tref(x.traded7, x.traded30), N * qo, x.bid, x.vwap7, x.vwap30, x.ask)
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rev += N * qo * p
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cost = 0.0
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for t, qi in io["in"].items():
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w = market.walk(t, a.cx, N * qi, "buy")
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if w["short"]:
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return None
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cost += w["total"]
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return rev - cost - N * c["wcost"]
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if a.budget and c["capex"] > a.budget:
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continue
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n_star = max(1, min(int(c["n_lim"]), a.max_n))
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if a.budget:
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n_star = max(1, min(n_star, int(a.budget // c["capex"])))
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net1 = evaluate(1)
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if net1 is None:
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continue
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netN = evaluate(n_star)
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while netN is None and n_star > 1:
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n_star = max(1, n_star // 2)
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netN = evaluate(n_star)
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if netN is None:
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continue
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rows.append(dict(roi1=100 * net1 / c["capex"], roiN=100 * netN / n_star / c["capex"], total=netN, n=n_star,
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n_lim=c["n_lim"], lim=c["lim"], capex=c["capex"] * n_star, eff=c["eff"], bld=c["b"]["Ticker"],
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top=c["top"], h=c["rec"]["TimeMs"] / 3.6e6, thin=c["thin"],
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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())))
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key = {"roi": "roiN", "roi1": "roi1", "total": "total"}[a.sort]
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rows.sort(key=lambda r: r[key], reverse=True)
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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}")
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print("# price: patient asks near VWAP (clamped), inputs ask-walked; N* = market-absorbable buildings (cap %d); all estimates" % a.max_n)
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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")
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for r in rows[:a.top]:
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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} "
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f"{r['h']:5.1f} {r['rec']}{' [thin]' if r['thin'] else ''}")
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if __name__ == "__main__":
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main()
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