My Project 6: Swiss Living Cost Calculator PRO(with Python + Streamlit)

#learning #python #beginners #codenewbie

🇨🇭 Swiss Living Cost Calculator PRO

After spending time studying the basics of Python syntax, I’ve now moved on to building projects to deepen my understanding. I realized that learning line by line doesn’t really match my style — instead, I learn much better when I can see how the overall structure fits together while creating something real. (AI definitely helps me a lot along the way!)

So my current approach is to keep building projects and repeatedly observe how the full system connects, rather than focusing on isolated pieces of code. Everyone has their own way of learning, of course, but I hope the projects I share here can be helpful to anyone following a similar path.

Since I live in Switzerland, I thought it would be meaningful to create a project that reflects real living conditions here — something practical that I could use myself while also learning new concepts. That’s how this Swiss living cost calculator was born.

And if you leave a reaction, it genuinely encourages me — it makes me feel like someone out there is learning alongside me. 🙏

🧱 1. Project Overview

This app allows you to:

Enter monthly fixed and variable costs
Automatically calculate your total living cost
Visualize spending using pie and bar charts (Plotly)
Convert CHF → EUR, USD, KRW using live exchange rates
Download a full PDF summary including charts

📂 2. Project Structure

swiss_living_app/
│
├── app.py                     # Main Streamlit app
├── requirements.txt           # Dependencies
└── README.md                  # optional

🖥️ 3. Main Code (app.py)

Below is the full implementation:

import streamlit as st
import requests
import plotly.graph_objects as go
import pandas as pd
from fpdf import FPDF
import tempfile

st.title("🇨🇭 Swiss Living Cost Calculator PRO")

# Initialize session state
if "fixed" not in st.session_state:
    st.session_state.fixed = {}

if "variable" not in st.session_state:
    st.session_state.variable = {}

# Fetch exchange rates
def get_rates():
    url = "https://open.er-api.com/v6/latest/CHF"
    response = requests.get(url)

    if response.status_code != 200:
        return None

    data = response.json()
    rates = data["rates"]

    return {
        "EUR": rates["EUR"],
        "USD": rates["USD"],
        "KRW": rates["KRW"]
    }

# Categories
fixed_cost_categories = [
    "Rent",
    "Insurance",
    "Internet & Mobile",
    "Transport Pass",
    "Kindergarten/Childcare",
    "Bills"
]

variable_cost_categories = [
    "Food",
    "Baby",
    "Shopping",
    "Medicine/Health",
    "Entertainment"
]

menu = st.sidebar.radio("Menu", [
    "Fixed Costs",
    "Variable Costs",
    "Summary"
])

# ======================
# Fixed Costs
# ======================
if menu == "Fixed Costs":
    st.subheader("🏠 Monthly Fixed Costs")

    for cat in fixed_cost_categories:
        st.session_state.fixed[cat] = st.number_input(
            f"{cat} (CHF)", min_value=0.0, format="%.2f",
            key=f"fixed_{cat}"
        )

    st.write("Your fixed costs:", st.session_state.fixed)

# ======================
# Variable Costs
# ======================
elif menu == "Variable Costs":
    st.subheader("🛒 Monthly Variable Costs")

    for cat in variable_cost_categories:
        st.session_state.variable[cat] = st.number_input(
            f"{cat} (CHF)", min_value=0.0, format="%.2f",
            key=f"var_{cat}"
        )

    st.write("Your variable costs:", st.session_state.variable)

# ======================
# Summary
# ======================
elif menu == "Summary":
    st.subheader("📊 Monthly Summary")

    total_fixed = sum(st.session_state.fixed.values())
    total_variable = sum(st.session_state.variable.values())
    grand_total = total_fixed + total_variable

    st.write(f"**Total Fixed Costs:** {total_fixed:.2f} CHF")
    st.write(f"**Total Variable Costs:** {total_variable:.22f} CHF")
    st.write(f"### 💰 Total Monthly Living Cost: {grand_total:.2f} CHF")

    # Prepare chart data
    total_data = {}
    for k, v in st.session_state.fixed.items():
        if v > 0:
            total_data[k] = v

    for k, v in st.session_state.variable.items():
        if v > 0:
            total_data[k] = v

    if total_data:
        df_total = pd.DataFrame({
            "Category": list(total_data.keys()),
            "Amount": list(total_data.values())
        })

        st.write("### Spending Breakdown")
        st.dataframe(df_total)

        # PLOTLY PIE CHART
        pie_colors = ["#66c2a5", "#fc8d62", "#8da0cb",
                      "#e78ac3", "#a6d854", "#ffd92f"]

        fig_pie = go.Figure(
            data=[go.Pie(
                labels=df_total["Category"],
                values=df_total["Amount"],
                marker=dict(colors=pie_colors)
            )]
        )

        st.write("### 📘 Pie Chart")
        st.plotly_chart(fig_pie, use_container_width=True)

        # BAR CHART
        fig_bar = go.Figure(
            data=[go.Bar(
                x=df_total["Category"],
                y=df_total["Amount"],
                marker_color=pie_colors
            )]
        )

        st.write("### 📗 Bar Chart")
        st.plotly_chart(fig_bar, use_container_width=True)

    # Currency Conversion
    st.write("### 🌍 Currency Conversion")

    rates = get_rates()

    if rates:
        eur_value = grand_total * rates["EUR"]
        usd_value = grand_total * rates["USD"]
        krw_value = grand_total * rates["KRW"]

        st.write(f"**EUR:** € {eur_value:,.2f}")
        st.write(f"**USD:** $ {usd_value:,.2f}")
        st.write(f"**KRW:** ₩ {krw_value:,.0f}")
    else:
        st.warning("⚠ Unable to load exchange rate data.")

# ======================
# PDF EXPORT
# ======================

if st.button("📄 Download PDF Summary"):
    pdf = FPDF()
    pdf.add_page()

    # Universal Linux-safe font
    font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf"
    pdf.add_font("DejaVu", "", font_path, uni=True)
    pdf.set_font("DejaVu", size=12)

    pdf.cell(200, 10, txt="Swiss Living Cost Summary", ln=True)
    pdf.ln(5)

    pdf.cell(200, 10, txt=f"Total Fixed Costs: {total_fixed:.2f} CHF", ln=True)
    pdf.cell(200, 10, txt=f"Total Variable Costs: {total_variable:.2f} CHF", ln=True)
    pdf.cell(200, 10, txt=f"Total Monthly Living Cost: {grand_total:.2f} CHF", ln=True)
    pdf.ln(10)

    pdf.cell(200, 10, txt="Currency Conversion:", ln=True)
    pdf.cell(200, 10, txt=f"EUR: € {eur_value:,.2f}", ln=True)
    pdf.cell(200, 10, txt=f"USD: $ {usd_value:,.2f}", ln=True)
    pdf.cell(200, 10, txt=f"KRW: ₩ {krw_value:,.0f}", ln=True)

    # Save Pie Chart Image
    pie_path = tempfile.NamedTemporaryFile(delete=False, suffix=".png").name
    fig_pie.write_image(pie_path, scale=2)

    pdf.ln(10)
    pdf.image(pie_path, x=15, y=pdf.get_y(), w=170)

    # Page 2 for Bar Chart
    pdf.add_page()
    pdf.set_font("DejaVu", size=14)
    pdf.cell(200, 10, txt="Category – Bar Chart", ln=True)
    pdf.ln(5)

    bar_path = tempfile.NamedTemporaryFile(delete=False, suffix=".png").name
    fig_bar.write_image(bar_path, scale=2)

    pdf.image(bar_path, x=15, y=pdf.get_y(), w=170)

    temp_pdf = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
    pdf.output(temp_pdf.name)

    with open(temp_pdf.name, "rb") as f:
        st.download_button(
            label="📄 Download PDF",
            data=f,
            file_name="swiss_living_cost_summary.pdf",
            mime="application/pdf"
        )


if __name__ == "__main__":
    print(get_rates())

📦 4. Requirements

streamlit
requests
plotly==5.24.1
kaleido==0.2.1
fpdf2
pandas

📚 5. What I Learned

Building multi-step Streamlit apps with session state
Integrating live API data (exchange rates)
Creating interactive charts with Plotly
Exporting PDF reports with charts (fpdf2 + Kaleido)
Designing forms & dashboards inside Streamlit

🔧 6. Future Improvements

Add dark mode UI
Save/load presets for recurring costs
Support multiple household members
More currency options
Connect to a cloud database (Supabase / Firebase)

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