groceries-tobiasli 1.0.1

Module for parsing shopping lists and dinner menus and compiling shopping lists.

groceries

groceries is a package for parsing shopping lists and dinner menus and compiling shopping lists with all the items.

Install

pip install groceries-tobiasli

Usage

groceries contains a set of classes that solve a lot of shopping and food-related problems:

• Ingredient is a container for a food item, and parses amount, unit and item name from an arbitrary string.
• GroceryList is a container for Ingredients and handles summation of all ingredients, as well as algebra.
• Cookbook is a container for Recipe, and make them searchable.
• Menu is the class returned when you use a Cookbook to parse an actual, typed shopping list. It contains the recipes and ingredients that are parsed from the shopping list.

GroceryList

GroceryList is the base component for most of the functionality in groceries. A GroceryList accepts groceries as strings on a human readable format. They are added to a GroceryList as Ingredient instances. Groceries lists can be added, subtracted and multiplied.

from groceries import GroceryList

gl = GroceryList()

gl.add_ingredients([
    '2 pounds sugar',
    '2 kg sugar',
    'chocolate',
    '4 floz foo',
    '4 tbs foo'
])

print(gl)

# <GroceryList object: 3 ingredients
#                chocolate,
#        1.78 dl foo,
#        2.91 kg sugar
# >

gl = gl - GroceryList(ingredients=['953.5 kg sugar', 'chocolate']) * 2
print(gl)

# <GroceryList object: 2 ingredients
#        1.78 dl foo,
#        1.00 kg sugar
# >

The base structure for an Ingredient string is

Optional[amount] Optional[unit] grocery_name, Optional[comment].

Recipe and Cookbooks

The GroceryList class is used to represent ingredients in recipes. Recipe is a class that contains information on how to cook a specific meal. You can have multiple Recipes and add them to a Cookbook.

The recipes are searchable both on name and tags.

# Demo scripts for grocery readme.
from groceries import Recipe, Cookbook


recipe1 = Recipe(
    name='Carbonara',
    tags=['pasta', 'fast', 'egg', 'bacon'],
    time=20,
    serves=2,
    how_to='''Cook pasta. As pasta is preparing, fry bacon. When bacon is done, add frozen pees and continue frying
    until pees are cooked. Mix finished pasta with bacon and pees. Add eggs and grated parmesan and stir. Season with
    salt and pepper.''',
    ingredients=[
        '150 g spaghetti',
        '100 g bacon',
        '100 g frozen green pees',
        '2 eggs',
        '50 g parmesan',
        'salt',
        'pepper'
    ])

recipe2 = Recipe(name="Mac'n cheese", tags=['pasta', 'fast'], time=5, serves=2,
                 how_to='''Cook mac. Add cheese. serve.''', ingredients=['150 g maccaroni', '100 g cheese', ])

recipe3 = Recipe(name='Chocolate', tags=['sweet', 'dessert'], time=2, serves=2, how_to='''Eat chocolate.''',
                 ingredients=['200 g chocolate'])

cookbook = Cookbook(recipes=[recipe1, recipe2, recipe3])

# Accepts fuzzy string matching:

print(cookbook.find_recipe('mac cheese'))

# <Recipe object: Mac'n cheese>

# Mac'n cheese is the first match for pasta, but searches are cycling. 
# So when performing a category match again you won't be presented 
# with the same recipe again:

print(cookbook.find_recipe('pasta'))

# <Recipe object: Carbonara>

Menu

Menu is a class for parsing an entire weeks worth of shopping, with syntax for meals on specific days as well as regular groceries.

# Continuation from previous code block.
menu = cookbook.parse_menu('''Monday: mac cheese
    Tuesday: sweet
    Wednesday: pasta
    2 tbs coffee
    1 floz baked beans
    1 banana
    2 banana
    4 liters coffee''')

print(menu.generate_processed_menu_str())
# Monday: Mac'n cheese til 2
# Tuesday: Chocolate til 2
# Wednesday: Carbonara til 2
# 0.30 dl coffee
# 0.30 dl baked beans
# 1 banana
# 2 banana
# 4 l coffee

print(menu.groceries)
# <GroceryList object: 13 ingredients
#          100 g bacon,
#        0.30 dl baked beans,
#              3 banana,
#          100 g cheese,
#          200 g chocolate,
#         4.03 l coffee,
#              2 eggs,
#          100 g frozen green pees,
#          150 g maccaroni,
#           50 g parmesan,
#                pepper,
#                salt,
#          150 g spaghetti
# >

So, happy shopping!