Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import plotly.graph_objects as go
+import plotly.express as px
+
+st.set_page_config(page_title="Interactive 12 Pubs of Christmas", layout="wide")
+
+# ------------------------------------
+# Parameters & Constants
+# ------------------------------------
+# Julia's data
+julia_weight_lbs = 120
+julia_weight_kg = julia_weight_lbs * 0.45359237
+julia_weight_g = julia_weight_kg * 1000
+julia_r = 0.55
+
+# Sean's data
+sean_weight_kg = 86.0
+sean_weight_g = sean_weight_kg * 1000
+sean_r = 0.68
+
+beta = 0.015  # g/dL/h elimination rate
+g_per_unit = 8
+
+# Drink options
+# We'll define a few drink types with their volumes and ABVs. 
+# For simplicity, we assume:
+# - 1 UK pint = 568 ml
+# - Half beer = Half pint = 284 ml
+# - Shot = 30 ml
+# - ABV is given in percentage.
+# We'll approximate each drink's ethanol mass:
+# Ethanol mass (g) = volume (ml) * density_of_ethanol(0.789 g/ml) * (ABV/100)
+# For simplicity, we use a units-based approach:
+# 1 unit (UK) = 10ml pure ethanol = 8g ethanol
+# Units = (Volume in ml * ABV%) / 1000 (approx UK definition: 1 unit = 10ml pure ethanol)
+# So ethanol in grams = Units * 8.
+
+drink_options = {
+    "Guinness (Pint)": {"volume_ml": 568, "abv": 4.2},
+    "Heineken (Pint)": {"volume_ml": 568, "abv": 5.0},
+    "Stella Artois (Pint)": {"volume_ml": 568, "abv": 4.8},
+    "Half Beer (Generic)": {"volume_ml": 284, "abv": 4.0},
+    "Vodka Shot": {"volume_ml": 30, "abv": 40.0},
+    "Whiskey Shot": {"volume_ml": 30, "abv": 40.0},
+    "Cider (Pint)": {"volume_ml": 568, "abv": 4.5},
+    "Red Wine (175ml)": {"volume_ml": 175, "abv": 12.0}
+}
+
+# A function to calculate ethanol grams from a given drink
+def alcohol_in_grams(volume_ml, abv_percent):
+    # 1 unit (UK) ~ (volume_ml * abv) / 1000 * (8g/unit)
+    units = (volume_ml * abv_percent) / 1000
+    return units * 8  # grams of ethanol
+
+def bac_calculation(total_alcohol_g, W, r, t):
+    # Widmark formula approximation:
+    # BAC = (A/(W*r))*100 - beta*(t-1) if t>1
+    bac = (total_alcohol_g / (W * r)) * 100
+    if t > 1:
+        bac = bac - beta*(t-1)
+    return max(bac,0)
+
+st.title("12 Pubs of Christmas - Interactive Drink Selection")
+
+st.write("""
+Select the drinks you (Julia) and Sean will consume each hour over a 6-hour period.
+We'll estimate your BAC levels and show you comparisons.
+
+**Note:** These are rough estimates and not medically accurate. Actual BAC varies by individual.
+""")
+
+hours = 6
+
+col_drinks = st.columns(hours)
+selected_drinks = []
+st.subheader("Select Drinks for Each Hour")
+for i in range(hours):
+    with col_drinks[i]:
+        drink_choice = st.selectbox(
+            f"Hour {i+1} Drink",
+            list(drink_options.keys()),
+            key=f"drink_hour_{i}"
+        )
+        selected_drinks.append(drink_choice)
+
+# Calculate total alcohol consumed per hour
+alcohol_by_hour = []
+for i, d in enumerate(selected_drinks):
+    vol = drink_options[d]["volume_ml"]
+    abv = drink_options[d]["abv"]
+    grams = alcohol_in_grams(vol, abv)
+    alcohol_by_hour.append(grams)
+
+# Cumulative alcohol and BAC calculations
+time_points = list(range(hours+1))  # from 0 to 6
+julia_bac = []
+sean_bac = []
+julia_alc_over_time = []
+sean_alc_over_time = []
+
+for t in time_points:
+    # total alcohol consumed up to hour t
+    total_alc = sum(alcohol_by_hour[:t])
+    # Julia BAC
+    julia_bac_val = bac_calculation(total_alc, julia_weight_g, julia_r, t)
+    julia_bac.append(julia_bac_val)
+    # Sean BAC
+    sean_bac_val = bac_calculation(total_alc, sean_weight_g, sean_r, t)
+    sean_bac.append(sean_bac_val)
+
+df = pd.DataFrame({
+    "Hour": time_points,
+    "Julia_BAC": julia_bac,
+    "Sean_BAC": sean_bac,
+    "Total_Alcohol_Consumed_g": [sum(alcohol_by_hour[:t]) for t in time_points]
+})
+
+# Calculate difference
+df["BAC_Difference"] = df["Julia_BAC"] - df["Sean_BAC"]
+
+# Plot 1: BAC over time
+st.subheader("BAC over Time")
+fig_bac = go.Figure()
+fig_bac.add_trace(go.Scatter(x=df["Hour"], y=df["Julia_BAC"], mode='lines+markers', name="Julia BAC", line=dict(color='firebrick', width=3)))
+fig_bac.add_trace(go.Scatter(x=df["Hour"], y=df["Sean_BAC"], mode='lines+markers', name="Sean BAC", line=dict(color='royalblue', width=3)))
+fig_bac.update_layout(title="Estimated BAC vs. Time (Hours)", xaxis_title="Hours", yaxis_title="BAC (%)", template="plotly_white")
+st.plotly_chart(fig_bac, use_container_width=True)
+
+# Plot 2: Alcohol consumed vs BAC (Dual-Axis)
+st.subheader("Alcohol Consumed and BAC")
+fig_bar_line = go.Figure()
+
+# Bar for total alcohol consumed at each hour
+fig_bar_line.add_trace(go.Bar(x=df["Hour"], y=df["Total_Alcohol_Consumed_g"], name="Total Alcohol (g)", marker_color='goldenrod', yaxis='y1'))
+# Julia BAC line
+fig_bar_line.add_trace(go.Scatter(x=df["Hour"], y=df["Julia_BAC"], name="Julia BAC", mode='lines+markers', line=dict(color='firebrick', width=3), yaxis='y2'))
+# Sean BAC line
+fig_bar_line.add_trace(go.Scatter(x=df["Hour"], y=df["Sean_BAC"], name="Sean BAC", mode='lines+markers', line=dict(color='royalblue', width=3), yaxis='y2'))
+
+fig_bar_line.update_layout(
+    title="Total Alcohol (g) vs BAC (%) Over Time",
+    xaxis=dict(title="Hour"),
+    yaxis=dict(title="Total Alcohol (g)", side='left', range=[0, df["Total_Alcohol_Consumed_g"].max()*1.1]),
+    yaxis2=dict(title="BAC (%)", side='right', overlaying='y', range=[0, df[["Julia_BAC","Sean_BAC"]].max().max()*1.1]),
+    template="plotly_white"
+)
+st.plotly_chart(fig_bar_line, use_container_width=True)
+
+# Plot 3: Difference in BAC
+st.subheader("Difference in BAC (Julia - Sean)")
+fig_diff = go.Figure(go.Bar(
+    x=df["Hour"], 
+    y=df["BAC_Difference"], 
+    text=[f"{d:.3f}%" for d in df["BAC_Difference"]],
+    textposition='outside',
+    marker_color='indianred'
+))
+fig_diff.update_layout(
+    title="Difference in BAC Between Julia and Sean Over Time",
+    xaxis_title="Hour",
+    yaxis_title="Difference in BAC (%)",
+    template="plotly_white"
+)
+st.plotly_chart(fig_diff, use_container_width=True)
+
+# Plot 4: Pie/Donut Chart of Alcohol Proportions if needed
+# For a bit of fun, let's compare the total alcohol consumed to their body weight as a fraction
+st.subheader("Alcohol as a Percentage of Body Weight")
+# 1g = 0.001 kg
+julia_pct_body_weight = (df["Total_Alcohol_Consumed_g"].iloc[-1] / julia_weight_g)*100
+sean_pct_body_weight = (df["Total_Alcohol_Consumed_g"].iloc[-1] / sean_weight_g)*100
+
+donut_data = pd.DataFrame({
+    "Person": ["Julia", "Sean"],
+    "Alcohol_as_pct_body_weight": [julia_pct_body_weight, sean_pct_body_weight]
+})
+
+fig_donut = px.pie(donut_data, values='Alcohol_as_pct_body_weight', names='Person', hole=0.5,
+                   color='Person', color_discrete_map={"Julia":"firebrick","Sean":"royalblue"})
+fig_donut.update_layout(title="Alcohol Consumed as % of Body Weight", template="plotly_white")
+st.plotly_chart(fig_donut, use_container_width=True)
+
+st.write("""
+**Disclaimer:**  
+These BAC values are rough estimates. Actual impairment depends on many factors including metabolism, 
+recent food intake, and individual tolerance. This tool is for illustrative purposes only.
+""")