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Experimental Creations

A collection of innovative and experimental tomato-based recipes that push the boundaries of what's possible with TomatoPy.

Molecular Gastronomy Tomato Spheres

Ingredients

from tomatopy import Tomato, Alginate, Calcium, SpherificationKit

# Create ingredients
tomatoes = Tomato(
    ripeness=0.95,
    variety="Heirloom",
    weight=500  # grams
)

alginate = Alginate(
    amount=2,  # grams
    purity=0.99,
    viscosity=0.8
)

calcium = Calcium(
    amount=5,  # grams
    form="chloride",
    purity=0.95
)

spherification_kit = SpherificationKit(
    size="medium",
    temperature_control=True
)

Instructions

from tomatopy import Kitchen, Recipe

# Initialize kitchen
kitchen = Kitchen()

# Create recipe
spheres = Recipe("Tomato Spheres")
spheres.add_ingredient(tomatoes)
spheres.add_ingredient(alginate)
spheres.add_ingredient(calcium)

# Set preparation parameters
spheres.set_preparation_method("spherification")
spheres.set_temperature(4)  # Celsius
spheres.set_duration("2h")

# Execute recipe
final_spheres = kitchen.prepare_recipe(spheres)

Quality Control

from tomatopy import TasteTester

# Analyze spheres
tester = TasteTester()
profile = tester.analyze(final_spheres)

# Check quality metrics
print(f"Sphericity: {profile.sphericity}")
print(f"Burst strength: {profile.burst_strength}")
print(f"Flavor concentration: {profile.flavor_concentration}")

Fermented Tomato Kimchi

Ingredients

# Create ingredients
tomatoes = Tomato(
    ripeness=0.85,
    variety="Roma",
    weight=1000  # grams
)

chili = Chili(
    amount=100,  # grams
    variety="Gochugaru",
    spiciness=0.8
)

garlic = Garlic(
    cloves=10,
    freshness=0.95,
    size="large"
)

ginger = Ginger(
    amount=50,  # grams
    freshness=0.95,
    spiciness=0.7
)

fermentation_kit = FermentationKit(
    type="anaerobic",
    temperature_control=True
)

Instructions

# Create recipe
kimchi = Recipe("Tomato Kimchi")
kimchi.add_ingredient(tomatoes)
kimchi.add_ingredient(chili)
kimchi.add_ingredient(garlic)
kimchi.add_ingredient(ginger)

# Set fermentation parameters
kimchi.set_fermentation_method("lactic")
kimchi.set_temperature(20)  # Celsius
kimchi.set_duration("7d")
kimchi.set_salt_concentration(0.02)  # 2% salt

# Execute recipe
final_kimchi = kitchen.ferment_recipe(kimchi)

Quality Control

# Analyze kimchi
profile = tester.analyze(final_kimchi)

# Check quality metrics
print(f"Fermentation level: {profile.fermentation_level}")
print(f"Spiciness: {profile.spiciness}")
print(f"Umami development: {profile.umami_development}")

Tomato Ice Cream

Ingredients

# Create ingredients
tomatoes = Tomato(
    ripeness=0.9,
    variety="San Marzano",
    weight=400  # grams
)

cream = Cream(
    amount=500,  # ml
    fat_content=0.35,
    freshness=0.95
)

sugar = Sugar(
    amount=150,  # grams
    type="granulated",
    sweetness=1.0
)

vanilla = Vanilla(
    amount=2,  # pods
    quality="madagascar",
    intensity=0.9
)

ice_cream_maker = IceCreamMaker(
    type="professional",
    temperature_control=True
)

Instructions

# Create recipe
ice_cream = Recipe("Tomato Ice Cream")
ice_cream.add_ingredient(tomatoes)
ice_cream.add_ingredient(cream)
ice_cream.add_ingredient(sugar)
ice_cream.add_ingredient(vanilla)

# Set preparation parameters
ice_cream.set_preparation_method("churning")
ice_cream.set_temperature(-5)  # Celsius
ice_cream.set_duration("30m")

# Execute recipe
final_ice_cream = kitchen.prepare_recipe(ice_cream)

Quality Control

# Analyze ice cream
profile = tester.analyze(final_ice_cream)

# Check quality metrics
print(f"Creaminess: {profile.creaminess}")
print(f"Sweetness balance: {profile.sweetness_balance}")
print(f"Tomato flavor integration: {profile.flavor_integration}")

Tomato Sushi

Ingredients

# Create ingredients
tomatoes = Tomato(
    ripeness=0.95,
    variety="Cherry",
    weight=300  # grams
)

rice = Rice(
    amount=500,  # grams
    variety="sushi",
    stickiness=0.9
)

nori = Nori(
    sheets=4,
    quality="premium",
    crispness=0.95
)

wasabi = Wasabi(
    amount=20,  # grams
    spiciness=0.8,
    freshness=0.95
)

sushi_kit = SushiKit(
    type="professional",
    rice_cooker=True
)

Instructions

# Create recipe
sushi = Recipe("Tomato Sushi")
sushi.add_ingredient(tomatoes)
sushi.add_ingredient(rice)
sushi.add_ingredient(nori)
sushi.add_ingredient(wasabi)

# Set preparation parameters
sushi.set_preparation_method("rolling")
sushi.set_temperature(22)  # Celsius
sushi.set_duration("45m")

# Execute recipe
final_sushi = kitchen.prepare_recipe(sushi)

Quality Control

# Analyze sushi
profile = tester.analyze(final_sushi)

# Check quality metrics
print(f"Rice texture: {profile.rice_texture}")
print(f"Roll tightness: {profile.roll_tightness}")
print(f"Flavor balance: {profile.flavor_balance}")

Best Practices

Experimental Design

# Design experiment
def design_experiment(recipe, parameters):
    experiment = Experiment(recipe)
    for param, value in parameters.items():
        experiment.add_parameter(param, value)
    return experiment

Parameter Optimization

# Optimize parameters
def optimize_parameters(recipe, target_profile):
    optimizer = ParameterOptimizer(recipe)
    optimal_params = optimizer.find_optimal(target_profile)
    return optimal_params

Quality Monitoring

# Monitor quality
def monitor_quality(recipe, duration):
    monitor = QualityMonitor(recipe)
    with monitor.track(duration):
        result = kitchen.prepare_recipe(recipe)
        quality_data = monitor.get_data()
    return result, quality_data

Advanced Techniques

Flavor Extraction

# Extract flavors
def extract_flavors(ingredient, method):
    extractor = FlavorExtractor(ingredient)
    flavors = extractor.extract(method)
    return flavors

Texture Modification

# Modify texture
def modify_texture(ingredient, target_texture):
    modifier = TextureModifier(ingredient)
    modified = modifier.modify(target_texture)
    return modified

Molecular Manipulation

# Manipulate molecules
def manipulate_molecules(ingredient, manipulation):
    manipulator = MoleculeManipulator(ingredient)
    result = manipulator.manipulate(manipulation)
    return result

Next Steps

  • API Reference - Explore the full API

  • Tutorials - Learn advanced techniques

  • Best Practices - Learn optimization techniques

Classic Dishes

A collection of classic tomato-based recipes implemented in TomatoPy. Each recipe includes detailed instructions, ingredient specifications, and quality control measures.

Classic Marinara Sauce

Ingredients

Instructions

Quality Control

Classic Pizza Sauce

Ingredients

Instructions

Quality Control

Classic Tomato Soup

Ingredients

Instructions

Quality Control

Classic Bruschetta

Ingredients

Instructions

Quality Control

Best Practices

Ingredient Selection

Temperature Control

Quality Assessment

Recipe Optimization

Flavor Enhancement

Texture Improvement

Next Steps

- Try innovative recipes

- Explore the full API

- Learn basic techniques

from tomatopy import Tomato, Garlic, Basil, OliveOil

# Create ingredients
tomatoes = Tomato(
    ripeness=0.9,
    variety="San Marzano",
    weight=800  # grams
)

garlic = Garlic(
    cloves=4,
    freshness=0.95,
    size="medium"
)

basil = Basil(
    leaves=20,
    freshness=0.95,
    variety="Genovese"
)

olive_oil = OliveOil(
    amount=60,  # ml
    quality="extra_virgin",
    acidity=0.3  # %
)
from tomatopy import Kitchen, Recipe

# Initialize kitchen
kitchen = Kitchen()

# Create recipe
marinara = Recipe("Classic Marinara")
marinara.add_ingredient(tomatoes)
marinara.add_ingredient(garlic)
marinara.add_ingredient(basil)
marinara.add_ingredient(olive_oil)

# Set cooking parameters
marinara.set_cooking_method("simmer")
marinara.set_duration("45m")
marinara.set_temperature(100)  # Celsius

# Execute recipe
sauce = kitchen.cook_recipe(marinara)
from tomatopy import TasteTester

# Analyze sauce
tester = TasteTester()
profile = tester.analyze(sauce)

# Check quality metrics
print(f"Sweetness: {profile.sweetness}")
print(f"Acidity: {profile.acidity}")
print(f"Umami: {profile.umami}")
print(f"Overall balance: {profile.balance}")
# Create ingredients
tomatoes = Tomato(
    ripeness=0.9,
    variety="San Marzano",
    weight=400  # grams
)

garlic = Garlic(
    cloves=3,
    freshness=0.95,
    size="medium"
)

basil = Basil(
    leaves=10,
    freshness=0.95,
    variety="Genovese"
)

oregano = Oregano(
    amount=5,  # grams
    freshness=0.9,
    variety="Mediterranean"
)
# Create recipe
pizza_sauce = Recipe("Classic Pizza Sauce")
pizza_sauce.add_ingredient(tomatoes)
pizza_sauce.add_ingredient(garlic)
pizza_sauce.add_ingredient(basil)
pizza_sauce.add_ingredient(oregano)

# Set cooking parameters
pizza_sauce.set_cooking_method("simmer")
pizza_sauce.set_duration("30m")
pizza_sauce.set_temperature(90)  # Celsius

# Execute recipe
sauce = kitchen.cook_recipe(pizza_sauce)
# Analyze sauce
profile = tester.analyze(sauce)

# Check quality metrics
print(f"Consistency: {profile.consistency}")
print(f"Herb balance: {profile.herb_balance}")
print(f"Overall quality: {profile.overall_score}")
# Create ingredients
tomatoes = Tomato(
    ripeness=0.85,
    variety="Roma",
    weight=1000  # grams
)

onion = Onion(
    amount=200,  # grams
    variety="yellow",
    sweetness=0.7
)

carrot = Carrot(
    amount=100,  # grams
    freshness=0.95,
    sweetness=0.8
)

celery = Celery(
    amount=100,  # grams
    freshness=0.95,
    crunchiness=0.9
)

cream = Cream(
    amount=200,  # ml
    fat_content=0.35,
    freshness=0.95
)
# Create recipe
soup = Recipe("Classic Tomato Soup")
soup.add_ingredient(tomatoes)
soup.add_ingredient(onion)
soup.add_ingredient(carrot)
soup.add_ingredient(celery)
soup.add_ingredient(cream)

# Set cooking parameters
soup.set_cooking_method("simmer")
soup.set_duration("1h")
soup.set_temperature(95)  # Celsius

# Execute recipe
final_soup = kitchen.cook_recipe(soup)
# Analyze soup
profile = tester.analyze(final_soup)

# Check quality metrics
print(f"Consistency: {profile.consistency}")
print(f"Vegetable balance: {profile.vegetable_balance}")
print(f"Cream integration: {profile.cream_integration}")
# Create ingredients
tomatoes = Tomato(
    ripeness=0.95,
    variety="Cherry",
    weight=500  # grams
)

garlic = Garlic(
    cloves=3,
    freshness=0.95,
    size="medium"
)

basil = Basil(
    leaves=15,
    freshness=0.95,
    variety="Genovese"
)

olive_oil = OliveOil(
    amount=30,  # ml
    quality="extra_virgin",
    acidity=0.3  # %
)

bread = Bread(
    slices=8,
    type="ciabatta",
    freshness=0.9
)
# Create recipe
bruschetta = Recipe("Classic Bruschetta")
bruschetta.add_ingredient(tomatoes)
bruschetta.add_ingredient(garlic)
bruschetta.add_ingredient(basil)
bruschetta.add_ingredient(olive_oil)
bruschetta.add_ingredient(bread)

# Set cooking parameters
bruschetta.set_cooking_method("assemble")
bruschetta.set_preparation_time("15m")

# Execute recipe
final_bruschetta = kitchen.prepare_recipe(bruschetta)
# Analyze bruschetta
profile = tester.analyze(final_bruschetta)

# Check quality metrics
print(f"Freshness: {profile.freshness}")
print(f"Texture balance: {profile.texture_balance}")
print(f"Overall quality: {profile.overall_score}")
# Check ingredient quality
def validate_ingredients(ingredients):
    for ingredient in ingredients:
        if not ingredient.is_fresh():
            print(f"Warning: {ingredient.name} may not be fresh")
        if not ingredient.meets_quality_standards():
            print(f"Warning: {ingredient.name} may not meet quality standards")
# Monitor cooking temperature
def monitor_cooking(recipe, kitchen):
    with kitchen.temperature_monitor() as monitor:
        result = kitchen.cook_recipe(recipe)
        if monitor.get_max() > recipe.max_temperature:
            print("Warning: Temperature exceeded maximum")
        return result
# Assess final product
def assess_quality(result, tester):
    profile = tester.analyze(result)
    if profile.overall_score < 0.8:
        print("Warning: Product may need improvement")
    return profile
# Enhance flavor profile
def enhance_flavor(recipe, target_profile):
    current_profile = tester.analyze(recipe)
    recommendations = tester.get_optimization_recommendations(
        current_profile,
        target_profile
    )
    return recommendations
# Improve texture
def improve_texture(recipe, target_texture):
    current_texture = tester.analyze_texture(recipe)
    adjustments = tester.get_texture_recommendations(
        current_texture,
        target_texture
    )
    return adjustments
Experimental Creations
API Reference
Tutorials