wright

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.

pip install wright-core

Recipes and ingredients¶

from 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"),
            ],
        )
    ],
    prep_time=30,
    cook_time=45,
    servings=12,
)

double = cake * 2  # scale a recipe with *

Beyond food — Material and Component¶

Material and Component are the domain-agnostic base classes behind Ingredient and RecipeComponent. Use them directly for non-food domains:

from wright import Material, Component

# Construction: a deck's bill of materials
framing = Component(
    name="Deck Framing",
    materials=[
        Material(
            name="2x6 Pressure-Treated", quantity=24, unit="ft", require_tags=["#2"]
        ),
        Material(name='3" Deck Screws', quantity=200, unit="each"),
    ],
)
footings = Component(
    name="Footings",
    materials=[
        Material(
            name="Concrete Mix",
            quantity=6,
            unit="bag",
            equivalent_quantity=60,
            equivalent_unit="lb",
        ),
    ],
)

Same scale(), __mul__, and supply list pipeline works across all domains.

Costing¶

from 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")),
]

cost = calculate_recipe_cost(cake, groceries)
print(cost.cost_per_serving_range.midpoint)

Planning a production run¶

from datetime import date
from wright import ProductionRun, ProductionItem, generate_shopping_list

session = ProductionRun(
    date=date(2026, 6, 20),
    production=[ProductionItem(recipe="Lemon Cake", quantity=3)],
    target_dates=[date(2026, 6, 20)],
)

shopping = generate_shopping_list(session, [cake])

Full grocery list example — grouped by store aisle with costs.

Allergens, nutrition, supply, pricing¶

from wright import detect_dietary_properties, calculate_recipe_macros
from wright import Stock, SupplyItem
from wright import margin_price

badges = detect_dietary_properties(cake)
macros = calculate_recipe_macros(cake, nutrition_registry=registry)
stock = Stock([SupplyItem(name="Flour", quantity=2000, unit="g")])
price = margin_price(Decimal("2.00"), 0.67)

Design¶

No I/O. Functions take data in, return data out.
Protocol-based. PurchasedItem accepts any class with the right attributes.
Pluggable. Every decision point accepts an injection.
Subclass-friendly. Material / Ingredient inheritance chain lets you add domain fields (construction grades, food vendor info) without monkey-patching.
Multi-domain. Same pipeline for cookies, decks, beer recipes, or assembly lines — just swap the model subclass and category rules.

Requirements¶

Python 3.11+. Dependencies: pydantic>=2.8.2, pint>=0.25, pyyaml>=6.0.3.

License¶

MIT. See LICENSE.

wright is created and maintained by 3pm German Baking, LLC a farmers market bakery in Asheville, NC.