188ef320cc
api.py
191 lines
4.8 KiB
Python
191 lines
4.8 KiB
Python
from nullptr.models.marketplace import Marketplace
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from nullptr.models.jumpgate import Jumpgate
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from nullptr.models.system import System
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from nullptr.models.waypoint import Waypoint
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from dataclasses import dataclass
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from nullptr.util import pprint
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from copy import copy
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class AnalyzerException(Exception):
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pass
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def path_dist(m):
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t = 0
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o = Point(0,0)
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for w in m:
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t +=w.distance(o)
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o = w
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return t
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@dataclass
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class Point:
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x: int
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y: int
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@dataclass
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class TradeOption:
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resource: str
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source: Waypoint
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dest: Waypoint
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margin: int
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dist: int
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score: float
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@dataclass
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class SearchNode:
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system: System
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parent: 'SearchNode'
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def __hash__(self):
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return hash(self.system.symbol)
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def path(self):
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result = []
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n = self
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while n is not None:
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result.append(n.system)
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n = n.parent
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result.reverse()
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return result
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def __repr__(self):
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return self.system.symbol
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class Analyzer:
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def __init__(self, store):
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self.store = store
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def find_markets(self, resource, sellbuy):
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for m in self.store.all(Marketplace):
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if 'sell' in sellbuy and resource in m.imports:
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yield ('sell', m)
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elif 'buy' in sellbuy and resource in m.exports:
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yield ('buy', m)
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elif 'exchange' in sellbuy and resource in m.exchange:
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yield ('exchange', m)
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def find_closest_markets(self, resource, sellbuy, location):
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if type(location) == str:
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location = self.store.get(Waypoint, location)
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mkts = self.find_markets(resource, sellbuy)
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candidates = []
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origin = location.system
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for typ, m in mkts:
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system = m.waypoint.system
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d = origin.distance(system)
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candidates.append((typ, m, d))
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possibles = sorted(candidates, key=lambda m: m[2])
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possibles = possibles[:10]
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results = []
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for typ,m,d in possibles:
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system = m.waypoint.system
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p = self.find_path(origin, system)
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if p is None: continue
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results.append((typ,m,d,len(p)))
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return results
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def solve_tsp(self, waypoints):
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wps = copy(waypoints)
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path = []
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cur = Point(0,0)
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while len(wps) > 0:
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closest = wps[0]
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for w in wps:
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if w.distance(cur) < closest.distance(cur):
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closest = w
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cur = closest
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path.append(closest)
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wps.remove(closest)
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return path
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def get_jumpgate(self, system):
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gates = self.store.all_members(system, Jumpgate)
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return next(gates, None)
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# dijkstra shmijkstra
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def find_nav_path(self, orig, to, ran):
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path = []
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mkts = [m.waypoint for m in self.store.all_members(orig.system, Marketplace)]
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cur = orig
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if orig == to:
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return []
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while cur != to:
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best = cur
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bestdist = cur.distance(to)
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if bestdist < ran:
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path.append(to)
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break
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for m in mkts:
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dist = m.distance(to)
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if dist < bestdist and cur.distance(m) < ran:
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best = m
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bestdist = dist
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if best == cur:
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raise AnalyzerException(f'no path to {to}')
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cur = best
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path.append(cur)
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return path
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def find_jump_path(self, orig, to, depth=100, seen=None):
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if depth < 1: return None
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if seen is None:
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seen = set()
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if type(orig) == System:
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orig = set([SearchNode(orig,None)])
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result = [n for n in orig if n==to]
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if len(result) > 0:
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return result[0].path()
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dest = set()
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for o in orig:
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jg = self.get_jumpgate(o)
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if jg is None: continue
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for s in jg.connections:
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if s in seen: continue
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seen.add(s)
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dest.add(SearchNode(s, o))
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if len(dest) == 0:
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return None
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return self.find_path(dest, to, depth-1, seen)
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def prices(self, system):
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prices = {}
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for m in self.store.all_members(system, Marketplace):
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for p in m.prices.values():
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r = p['symbol']
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if not r in prices:
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prices[r] = []
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prices[r].append({
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'wp': m.waypoint,
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'buy': p.buy,
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'sell': p.sell
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})
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return prices
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def find_trade(self, system):
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prices = self.prices(system)
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occupied_resources = set()
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for s in self.store.all('Ship'):
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if s.mission != 'haul':
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continue
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occupied_resources.add(s.mission_state['resource'])
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best = None
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for resource, markets in prices.items():
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if resource in occupied_resources:
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continue
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source = sorted(markets, key=lambda x: x['buy'])[0]
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dest = sorted(markets, key=lambda x: x['sell'])[-1]
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margin = dest['sell'] -source['buy']
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dist = source['wp'].distance(dest['wp'])
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dist = max(dist, 0.0001)
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score = margin / dist
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if margin < 0:
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continue
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o = TradeOption(resource, source['wp'], dest['wp'], margin, dist, score)
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if best is None or best.score < o.score:
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best = o
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return best
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