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demo.py — Quick demo for hackathon judges / live defense
Runs everything in < 5 seconds. All output is self-explanatory.
"""
from pricer import (
Product, suggest_price, simulate_7_days,
format_sms, print_comparison_report, freshness_factor
)
def demo_single_price():
"""Show how one pricing call works, step by step."""
print("\n" + "━"*60)
print(" DEMO 1: Single Price Recommendation")
print("━"*60)
tomato = Product(
sku="TOMATO-A",
cost=1000,
shelf_life_days=7,
p_ref=1800,
Q0=50,
alpha=1.5,
)
competitors = [1600, 1700, 1900]
for age in [0, 2, 3.5, 5, 6]:
result = suggest_price(tomato, age, competitors)
freshness = result["freshness"]
price = result["suggested_price"]
label = result["freshness_label"]
print(f" Day {age:>3.1f} | Freshness: {freshness:.3f} ({label:<10}) "
f"→ Price: {price:>7.0f} UGX | "
f"Margin: {result['margin_pct']:>5.1f}%")
def demo_freshness_table():
"""Show the sigmoid freshness curve — great for interview visuals."""
print("\n" + "━"*60)
print(" DEMO 2: Freshness Curve (why sigmoid beats linear)")
print("━"*60)
print(f" {'Day':<6} {'Sigmoid':>10} {'Linear':>10} {'Difference':>12}")
print(" " + "-"*42)
shelf = 7
for day in range(8):
sigmoid = freshness_factor(day, shelf)
linear = max(0, 1 - day / shelf)
diff = sigmoid - linear
bar = "█" * int(sigmoid * 20)
print(f" {day:<6} {sigmoid:>10.3f} {linear:>10.3f} {diff:>+12.3f} {bar}")
def demo_what_at_half_life():
"""Interview: what happens at half shelf life?"""
print("\n" + "━"*60)
print(" DEMO 3: The Half-Life Moment (key interview talking point)")
print("━"*60)
tomato = Product(
sku="TOMATO-A", cost=1000, shelf_life_days=7,
p_ref=1800, Q0=50, alpha=1.5,
)
half_life = tomato.shelf_life_days / 2 # Day 3.5
fresh_result = suggest_price(tomato, 0, [1600, 1700])
mid_result = suggest_price(tomato, half_life, [1600, 1700])
late_result = suggest_price(tomato, 6, [1600, 1700])
print(f" Day 0 (fresh): {fresh_result['suggested_price']:>7.0f} UGX — {fresh_result['freshness_label']}")
print(f" Day 3.5 (half-life): {mid_result['suggested_price']:>7.0f} UGX — {mid_result['freshness_label']}")
print(f" Day 6 (near-exp): {late_result['suggested_price']:>7.0f} UGX — {late_result['freshness_label']}")
print()
price_drop = (fresh_result['suggested_price'] - mid_result['suggested_price'])
print(f" → At half-life, price drops {price_drop:.0f} UGX ({price_drop/fresh_result['suggested_price']*100:.0f}%)")
print(" → This is the inflection point — aggressive discounting begins")
print(" → Exactly where the sigmoid inflects: steepest rate of change")
def demo_sms():
"""Show SMS output for different freshness levels."""
print("\n" + "━"*60)
print(" DEMO 4: SMS Output (African Market Feature)")
print("━"*60)
tomato = Product(
sku="TOM", cost=1000, shelf_life_days=7,
p_ref=1800, Q0=50, alpha=1.5,
)
for age in [0, 3, 5, 6]:
result = suggest_price(tomato, age, [1600, 1700, 1900])
sms = format_sms(result, "UGX")
print(f" Day {age}: [{len(sms):>3}chr] {sms}")
def demo_simulation():
"""Full 7-day comparison across 3 strategies."""
tomato = Product(
sku="TOMATO", cost=1000, shelf_life_days=7,
p_ref=1800, Q0=50, alpha=1.5,
)
print_comparison_report(tomato, [1600, 1700, 1900])
# Second product: bread (shorter shelf life, different dynamics)
bread = Product(
sku="BREAD", cost=2500, shelf_life_days=3,
p_ref=4000, Q0=30, alpha=2.0,
k=10.0 # Sharper cliff for bread
)
print_comparison_report(bread, [3800, 3900])
if __name__ == "__main__":
demo_single_price()
demo_freshness_table()
demo_what_at_half_life()
demo_sms()
demo_simulation()
print("\n✅ All demos complete. Ready for live defense.")
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