wright /rīt/ — noun: a maker or builder. From Old English wyrhta (worker), as in shipwright, wheelwright, playwright. Here: a wright for your recipes, assemblies, and bills of materials.
Pure Python library for production planning, cost calculation, shopping list generation, allergen detection, nutrition analysis, and supply tracking.
Data-source agnostic. No I/O inside the core — models are plain Pydantic, the
PurchasedItem protocol accepts anything. Subclass to add your own fields.
Domains: food recipes, construction materials, brewing grain bills, manufacturing BOMs — any domain where you need to aggregate named items with quantities and units into a consolidated supply list with costs.
pip install wrightfrom wright import Recipe, Ingredient, RecipeComponent
cake = Recipe(
name="Lemon Cake",
components=[RecipeComponent(name="Batter", ingredients=[
Ingredient(name="Flour", quantity=300, unit="g"),
Ingredient(name="Butter", quantity=200, unit="g"),
Ingredient(name="Lemon Juice", quantity=3, unit="tbsp"),
])],
prep_time=30, cook_time=45,
servings=12,
)
# Scale it
double_batch = cake * 2 # same as cake.size_up(2)
half_batch = cake * 0.5from decimal import Decimal
from wright import Purchase, calculate_recipe_cost
groceries = [
Purchase(name="Flour", quantity=1000, unit="g", price=Decimal("3.99")),
Purchase(name="Butter", quantity=500, unit="g", price=Decimal("5.49")),
Purchase(name="Lemon Juice", quantity=250, unit="ml", price=Decimal("1.99")),
]
cost = calculate_recipe_cost(cake, groceries)
print(cost.total_cost_range.midpoint) # → 3.10
print(cost.cost_per_serving_range.midpoint) # → 0.26from datetime import date
from wright import (
ProductionRun, ProductionItem,
generate_shopping_list, group_shopping_items,
calculate_shopping_list_cost, analyze_menu,
DEFAULT_CATEGORY_RULES,
)
session = ProductionRun(
date=date(2026, 6, 20),
production=[ProductionItem(assembly="Lemon Cake", quantity=3)],
target_dates=[date(2026, 6, 20)],
)
shopping = generate_shopping_list(session, [cake])Group items by store aisle:
grouped = group_shopping_items(
shopping.all_items,
category_rules=DEFAULT_CATEGORY_RULES,
)
for group in grouped:
for item in group.items:
print(f" {item.name:<22s} {item.quantity:g} {item.unit}") Dairy & Eggs ----------------------------------------------
Butter 600 g
Lemon Juice 9 tbsp
Dry Goods -------------------------------------------------
Flour 900 g
Enrich with costs and analyze:
costs = calculate_shopping_list_cost(shopping, groceries)
total = sum(c.total_cost for c in costs if c.total_cost is not None)
# → Decimal('9.30')
menu = analyze_menu(
[ProductionItem(assembly="Lemon Cake", quantity=3)],
[cake], groceries,
)
for item in menu.top_drivers:
print(f" {item.item.name}: ${item.total_cost} ({menu.cost_share(item):.0%})")
# → Butter: $3.29 (35%)
# → Flour: $2.39 (26%)Full grocery list example with 3 recipes, 16 grocery items, and formatted output. Meal prep planner — 5-day week, 2 cook sessions, macros per day.
from wright import detect_allergens, detect_dietary_properties
allergens = detect_allergens(cake, allergy_map={"milk": "Dairy", "wheat": "Wheat"})
# → ["Dairy", "Gluten", "Eggs"]
badges = detect_dietary_properties(cake)
# → ["VEGAN", "DAIRY-FREE", "GLUTEN-FREE"]Supplement keyword detection with purchase data:
badges = detect_dietary_properties(cake, ingredient_properties=lambda ing: (
frozenset({"vegan", "gluten-free"}) if "gf" in ing.require_tags else frozenset()
))from wright import calculate_recipe_macros, NutritionInfo, FoodRecord
registry = [
FoodRecord(ingredient="Flour", nutrition=NutritionInfo(protein_g=10, carbs_g=76, fat_g=1, kcal=364)),
FoodRecord(ingredient="Butter", nutrition=NutritionInfo(protein_g=0.9, carbs_g=0.1, fat_g=81, kcal=717)),
]
macros = calculate_recipe_macros(cake, nutrition_registry=registry)
print(macros.per_serving.kcal)from wright import Stock, SupplyItem
stock = Stock([SupplyItem(name="Flour", quantity=2000, unit="g")])
stock, deficit = stock.use([SupplyItem(name="Flour", quantity=900, unit="g")])
# deficit → [] — stock covers itfrom wright import margin_price, multiplier_price
margin_price(Decimal("2.00"), 0.67) # → 6.06 (67% margin)
multiplier_price(Decimal("2.00"), 3) # → 6.00 (3× cost)from wright import chain, pinned_picker, cheapest_picker
# Compose pickers: pinned first, then cheapest
picker = chain(pinned_picker({"Butter": my_brand}), cheapest_picker)
items = calculate_shopping_list_cost(shopping, groceries, picker=picker)
# Custom volume display for metric users
shopping = generate_shopping_list(session, [cake],
display_normalizer=lambda q, u: ...,
)
# Custom name matcher
cost = calculate_recipe_cost(cake, groceries,
matcher=my_fuzzy_matcher,
)Assembly, Component, and Material work for construction, brewing,
manufacturing, or any bill-of-materials domain. No dummy food fields needed:
from datetime import date
from decimal import Decimal
from wright import (
Assembly, Component, ProductionItem, ProductionRun, Purchase,
generate_shopping_list, calculate_item_costs,
)
# ── Two home projects ──────────────────────────────────────────────────────
deck = Assembly(name="Backyard Deck", components=[
Component(name="Framing", materials=[
Material(name="2x6 Pressure-Treated", quantity=48, unit="ft"),
Material(name="Joist Hangers", quantity=16, unit="each"),
]),
Component(name="Surface", materials=[
Material(name='5/4" Cedar Decking', quantity=160, unit="ft"),
Material(name='2" Stainless Screws', quantity=600, unit="each"),
]),
])
bed = Assembly(name="Raised Garden Bed", components=[
Component(name="Frame", materials=[
Material(name="2x8 Cedar", quantity=24, unit="ft"),
Material(name='3" Deck Screws', quantity=64, unit="each"),
]),
])
# ── Hardware store prices ──────────────────────────────────────────────────
prices = [
Purchase(name="2x6 Pressure-Treated", quantity=8, unit="ft",
price=Decimal("12.97"), store="Home Depot"),
Purchase(name='2" Stainless Screws', quantity=100, unit="each",
price=Decimal("3.49"), store="Home Depot"),
]
# ── Cost one project ───────────────────────────────────────────────────────
deck_costs = calculate_item_costs(deck.all_materials, prices)
total = sum(c.total_cost for c in deck_costs if c.total_cost is not None)
print(f"Deck materials: ${total}")
# ── Plan a weekend build session ───────────────────────────────────────────
plan = ProductionRun(
date=date(2026, 6, 20),
production=[
ProductionItem(assembly="Backyard Deck", quantity=1),
ProductionItem(assembly="Raised Garden Bed", quantity=1),
],
target_dates=[date(2026, 6, 20)],
)
shopping = generate_shopping_list(plan, [deck, bed])
for item in shopping.all_items:
print(f"{item.name}: {item.quantity:.0f} {item.unit}")
# ── Cross-reference with home inventory ───────────────────────────────────
from wright import Stock, SupplyItem
# What's already in the garage
garage_stock = Stock([
SupplyItem(name='2" Stainless Screws', quantity=100, unit="each"),
SupplyItem(name="Joist Hangers", quantity=8, unit="each"),
])
# Deduct stock — get only what you still need to buy
garage_stock, buy_list = garage_stock.use(deck.all_materials)
for item in buy_list:
print(f"Buy: {item.name} — {item.quantity:.0f} {item.unit}")
# → Buy: 2x6 Pressure-Treated — 48 ft
# → Buy: Joist Hangers — 8 each (16 needed − 8 on hand)
# → Buy: 5/4" Cedar Decking — 160 ft
# → Buy: 2" Stainless Screws — 500 each (600 needed − 100 on hand)The same calculate_ingredient_cost() and Stock work across all domains.
Python 3.11+. Dependencies: pydantic>=2.8.2, pint>=0.25, pyyaml>=6.0.3.
MIT. See LICENSE.
wright is created and maintained by 3pm German Baking, LLC a farmers market bakery in Asheville, NC.