shipbuilding: make everything except hardcoded list

identify which parts are liquid
group mats by expertise

shipbuilding.py

@@ -6,6 +6,13 @@ import typing
 import cache
 import roi
 
+BUY = frozenset([
+	# definitely buy
+	'C', 'FLX', 'H', 'H2O', 'HAL', 'HCP', 'HE', 'LST', 'MG', 'N', 'NA', 'NCS', 'NS', 'O', 'PE', 'PG', 'S', 'TCL',
+	# maybe buy
+	'AU', 'BRM', 'CU', 'FE', 'LI', 'RG', 'ROM', 'SI', 'TI',
+])
+
 def main() -> None:
 	blueprint = {
 		'FFC': 1,
@@ -26,17 +33,32 @@ def main() -> None:
 			for p in cache.get('https://refined-prun.github.io/refined-prices/all.json') if p['ExchangeCode'] == 'IC1'}
 	recipes = recipe_for_mats()
 
-	buildings: dict[str, set[str]] = collections.defaultdict(set)
+	production: dict[str, dict[str, float]] = collections.defaultdict(lambda: collections.defaultdict(float))
 	cost = 0.0
 	for mat, amount in blueprint.items():
-		cost += analyze_mat(0, mat, amount, buildings, prices, recipes)
+		cost += analyze_mat(0, mat, amount, production, prices, recipes)
 		print()
 	print(f'total cost: {cost:,}')
-	for building, mats in buildings.items():
-		print(f'{building:3}: {", ".join(mats)}')
+
+	buildings: typing.Sequence[roi.Building] = cache.get('https://api.prunplanner.org/data/buildings/', expiry=cache.ONE_DAY)
+	expertise = collections.defaultdict(list)
+	for building in buildings:
+		if building['building_ticker'] in production:
+			expertise[building['expertise']].append(building['building_ticker'])
+	for expertise, buildings in expertise.items():
+		print(expertise)
+		for building in buildings:
+			print(f'\t{building:3}:', end='')
+			for mat, amount in production[building].items():
+				traded = prices[mat]['AverageTraded30D'] or 0
+				if traded > amount * 2:
+					print(f' \033[32m{mat}\033[0m', end='')
+				else:
+					print(f' \033[31m{mat}\033[0m', end='')
+			print()
 
 def recipe_for_mats() -> dict[str, roi.Recipe]:
-	all_recipes: list[roi.Recipe] = cache.get('https://api.prunplanner.org/data/recipes/')
+	all_recipes: list[roi.Recipe] = cache.get('https://api.prunplanner.org/data/recipes/', expiry=cache.ONE_DAY)
 	mat_recipes = collections.defaultdict(list) # all ways to make a mat
 	for recipe in all_recipes:
 		for output in recipe['outputs']:
@@ -48,12 +70,12 @@ def recipe_for_mats() -> dict[str, roi.Recipe]:
 			mat_recipe[mat] = recipes[0]
 	return mat_recipe
 
-def analyze_mat(level: int, mat: str, amount: float, buildings: dict[str, set[str]],
+def analyze_mat(level: int, mat: str, amount: float, production: dict[str, dict[str, float]],
 		prices: typing.Mapping[str, RawPrice], recipes: dict[str, roi.Recipe]) -> float:
 	price = prices[mat]
 	traded = price['AverageTraded30D'] or 0
-	if (price['Supply'] > amount * 10 and traded > 0) or (price['Supply'] > amount * 4 and amount < traded):
-		print('\t' * level + f'{amount:g}×{mat} buy: {price["Ask"]:9,}, daily traded {traded:5.1f}, supply {price["Supply"]:4}')
+	if mat in BUY:
+		print('\t' * level + f'{amount:g}×{mat} buy: {price["Ask"]}, daily traded {traded:5.1f}')
 		assert price['Ask'] is not None
 		return price['Ask'] * amount
 	else:
@@ -62,12 +84,17 @@ def analyze_mat(level: int, mat: str, amount: float, buildings: dict[str, set[st
 			return 0
 		else:
 			building = recipe['building_ticker']
-			print('\t' * level + f'{amount:g}×{mat} make ({building})')
-			buildings[building].add(mat)
+			production[building][mat] += amount
+
+			liquid = '\033[31mnot liquid\033[0m'
+			if traded > amount * 2:
+				liquid = '\033[32mliquid\033[0m'
+			print('\t' * level + f'{amount:g}×{mat} make ({building}, {liquid})')
+
 			total_cost = 0.0
 			for input_mat in recipe['inputs']:
 				input_amount = input_mat['material_amount'] * amount / recipe['outputs'][0]['material_amount']
-				total_cost += analyze_mat(level + 1, input_mat['material_ticker'], input_amount, buildings, prices, recipes)
+				total_cost += analyze_mat(level + 1, input_mat['material_ticker'], input_amount, production, prices, recipes)
 			print('\t' * level + f'\tcost: {total_cost:9,.2f}')
 		return total_cost