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Update app.py
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app.py
CHANGED
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@@ -5,16 +5,15 @@ import json
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import os
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from datetime import datetime
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# -------------------------------
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# App
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# -------------------------------
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st.set_page_config(page_title="Climate Clock Observatory", layout="wide")
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st.title("🌍 Climate Clock Observatory")
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st.write("This dashboard presents key climate indicators using pseudo real-time data from the Climate Clock API.")
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# -------------------------------
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#
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# -------------------------------
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try:
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file_stats = os.stat("climate_data.json")
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last_updated = datetime.fromtimestamp(file_stats.st_mtime).strftime("%Y-%m-%d %H:%M:%S")
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@@ -22,143 +21,137 @@ try:
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except:
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st.caption("🕒 Last updated time not available")
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# -------------------------------
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# Refresh Button
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# -------------------------------
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if st.button("🔁 Refresh Data"):
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with st.spinner("Refreshing data..."):
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st.experimental_rerun()
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# -------------------------------
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# Load
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# -------------------------------
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try:
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with open("climate_data.json") as f:
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clock = json.load(f)
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except Exception:
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st.error("Failed to load climate data.")
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st.stop()
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# -------------------------------
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# 1
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# -------------------------------
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st.header("1️⃣ CO₂ Budget Depletion Projection")
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try:
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co2 = clock.get("co2", {})
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co2_remaining = float(co2.get("remaining", 0))
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co2_rate = float(co2.get("rate", 0))
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})
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st.altair_chart(chart, use_container_width=True)
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st.warning(f"Could not render CO₂ projection chart: {e}")
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# -------------------------------
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# 2
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# -------------------------------
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st.header("2️⃣ Global Energy Mix – Renewables vs Others")
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try:
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renewables = clock.get("renewables", {})
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renewable_percent = float(renewables.get("percentage", 0))
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energy_df = pd.DataFrame({
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"Type": ["Renewables", "Other"],
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"Percentage": [renewable_percent, 100 - renewable_percent]
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})
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donut = alt.Chart(energy_df).mark_arc(innerRadius=50).encode(
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theta="Percentage:Q",
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color="Type:N",
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tooltip=["Type", "Percentage"]
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).properties(width=400, height=400)
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st.altair_chart(donut, use_container_width=True)
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except Exception as e:
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st.warning(f"Could not render energy mix chart: {e}")
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# ----------------------------------------
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# 3. Lifeline Metrics (Bar Chart)
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# ----------------------------------------
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st.header("3️⃣ Lifeline Metrics – Positive Climate Interventions")
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try:
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lifelines = clock.get("lifelines", [])
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lifeline_df = pd.DataFrame([
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{"Label": item.get("label", ""), "Value": float(item.get("value", 0))}
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for item in lifelines
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])
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lifeline_chart = alt.Chart(lifeline_df).mark_bar().encode(
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x=alt.X("Label:N", sort="-y"),
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y="Value:Q",
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tooltip=["Label", "Value"]
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).properties(width=700)
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st.altair_chart(lifeline_chart, use_container_width=True)
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st.header("4️⃣ Time Left to 1.5°C Threshold")
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try:
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deadline = clock.get("deadline", {})
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parts = list(map(int, deadline.get("time_left", "0:0:0:0:0").split(":")))
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display_str = f"{parts[0]} years, {parts[1]} months, {parts[2]} days"
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st.success(f"⏳ Estimated Time Remaining: {display_str}")
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except Exception as e:
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st.warning(f"Could not display climate deadline: {e}")
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# ----------------------------------------
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st.header("5️⃣ CO₂ Budget Simulator – What If We Reduce Emissions?")
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try:
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sim_budgets = []
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budget = co2_remaining
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year = datetime.now().year
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while budget > 0 and len(sim_years) < 20:
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sim_years.append(year)
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sim_budgets.append(budget)
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budget -= new_rate
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year += 1
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sim_df = pd.DataFrame({
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"Year": sim_years,
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"Projected CO₂ Budget (Gt)": sim_budgets
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})
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sim_chart = alt.Chart(sim_df).mark_line(point=True).encode(
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x="Year:O",
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y="Projected CO₂ Budget (Gt):Q",
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tooltip=["Year", "Projected CO₂ Budget (Gt)"]
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).properties(width=700)
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st.altair_chart(sim_chart, use_container_width=True)
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# Footer
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# -------------------------------
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st.markdown("---")
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st.caption("Made by Sanidhya and Group Members | Data
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import os
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from datetime import datetime
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# -------------------------------
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# App Config and Title
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# -------------------------------
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st.set_page_config(page_title="Climate Clock Observatory", layout="wide")
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st.title("🌍 Real-Time Climate Clock Observatory")
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# -------------------------------
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# Show Last Updated Timestamp
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# -------------------------------
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try:
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file_stats = os.stat("climate_data.json")
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last_updated = datetime.fromtimestamp(file_stats.st_mtime).strftime("%Y-%m-%d %H:%M:%S")
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except:
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st.caption("🕒 Last updated time not available")
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# -------------------------------
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# Refresh Button
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# -------------------------------
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if st.button("🔁 Refresh Data"):
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with st.spinner("Refreshing data..."):
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st.experimental_rerun()
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# -------------------------------
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# Load Climate Data from JSON
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# -------------------------------
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try:
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with open("climate_data.json", "r") as f:
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clock = json.load(f)
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except Exception as e:
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st.error("❌ Failed to load climate data.")
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st.stop()
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# -------------------------------
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# 1️⃣ CO₂ Budget Depletion Projection
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# -------------------------------
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st.header("1️⃣ CO₂ Budget Depletion Projection")
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co2_data = clock.get("co2", {})
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co2_remaining = float(co2_data.get("remaining", 0))
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co2_rate = float(co2_data.get("rate", 0))
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years = list(range(datetime.now().year, datetime.now().year + 10))
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remaining_budget = [max(co2_remaining - i * co2_rate, 0) for i in range(10)]
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co2_df = pd.DataFrame({"Year": years, "Remaining CO₂ Budget (Gt)": remaining_budget})
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co2_chart = alt.Chart(co2_df).mark_line(point=True).encode(
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x='Year:O',
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y='Remaining CO₂ Budget (Gt):Q',
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tooltip=['Year', 'Remaining CO₂ Budget (Gt)']
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).properties(width=700)
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st.altair_chart(co2_chart, use_container_width=True)
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# -------------------------------
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# 2️⃣ Global Energy Mix Donut Chart
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# -------------------------------
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st.header("2️⃣ Global Energy Mix – Renewables vs Others")
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renew_data = clock.get("renewables", {})
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renew_percent = float(renew_data.get("percentage", 0))
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energy_df = pd.DataFrame({
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"Type": ["Renewables", "Other"],
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"Percentage": [renew_percent, 100 - renew_percent]
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})
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energy_chart = alt.Chart(energy_df).mark_arc(innerRadius=50).encode(
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theta="Percentage:Q",
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color="Type:N",
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tooltip=["Type", "Percentage"]
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).properties(width=400, height=400)
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st.altair_chart(energy_chart, use_container_width=True)
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# -------------------------------
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# 3️⃣ Lifeline Metrics Bar Chart
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# -------------------------------
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st.header("3️⃣ Lifeline Metrics – Positive Contributions")
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lifelines = clock.get("lifelines", [])
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lifeline_df = pd.DataFrame([
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{"Label": item.get("label", ""), "Value": float(item.get("value", 0))}
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for item in lifelines
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])
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lifeline_chart = alt.Chart(lifeline_df).mark_bar().encode(
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x=alt.X("Label:N", sort="-y"),
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y="Value:Q",
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tooltip=["Label", "Value"]
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).properties(width=700)
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st.altair_chart(lifeline_chart, use_container_width=True)
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# -------------------------------
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# 4️⃣ Time Left to 1.5°C Threshold
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# -------------------------------
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st.header("4️⃣ Time Left to 1.5°C Threshold")
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deadline = clock.get("deadline", {})
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time_parts = deadline.get("time_left", "0:0:0:0:0").split(":")
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try:
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years, months, days = int(time_parts[0]), int(time_parts[1]), int(time_parts[2])
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st.success(f"⏳ Estimated time before 1.5°C threshold: {years} years, {months} months, {days} days")
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except:
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st.warning("⚠️ Could not parse climate deadline.")
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# -------------------------------
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# 5️⃣ CO₂ Budget Simulator with Slider
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# -------------------------------
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st.header("5️⃣ CO₂ Budget Simulator – What If We Reduce Emissions?")
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st.markdown("📉 Use the slider below to simulate reduced annual emissions and visualize its impact.")
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new_rate = st.slider(
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"New Annual CO₂ Emission Rate (Gt/year)",
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min_value=10.0,
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max_value=45.0,
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value=co2_rate,
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step=0.5
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)
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sim_years = []
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sim_budget = []
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current_budget = co2_remaining
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year = datetime.now().year
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while current_budget > 0 and len(sim_years) < 20:
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sim_years.append(year)
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sim_budget.append(current_budget)
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current_budget -= new_rate
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year += 1
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sim_df = pd.DataFrame({
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"Year": sim_years,
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"Projected CO₂ Budget (Gt)": sim_budget
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})
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sim_chart = alt.Chart(sim_df).mark_line(point=True).encode(
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x="Year:O",
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y="Projected CO₂ Budget (Gt):Q",
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tooltip=["Year", "Projected CO₂ Budget (Gt)"]
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).properties(width=700)
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st.altair_chart(sim_chart, use_container_width=True)
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# -------------------------------
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# Footer
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# -------------------------------
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st.markdown("---")
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st.caption("Made by Sanidhya and Group Members | Data from Climate Clock API (cached sample)")
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