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Update app.py
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app.py
CHANGED
@@ -6,6 +6,7 @@ import requests
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from io import BytesIO
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import streamlit as st
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import streamlit.components.v1 as components
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# Load data from Excel URL with error handling
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def load_data(url):
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@@ -94,23 +95,36 @@ def calculate_impact(df, center):
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# Return the new statistics
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return latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before
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# Display the
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def
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"
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"Download Speed": f"{avg_download_before:.2f} Mbps",
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"Upload Speed": f"{avg_upload_before:.2f} Mbps"
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},
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"After Data Center": {
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"Latency": f"{latency_reduction:.2f} ms",
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"Download Speed": f"{download_increase:.2f} Mbps",
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"Upload Speed": f"{upload_increase:.2f} Mbps"
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}
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}
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# Main function to run the application
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def main():
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@@ -137,7 +151,7 @@ def main():
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# Calculate the impact of adding the data center
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latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before = calculate_impact(df, center)
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if latency_reduction is not None:
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-
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if __name__ == "__main__":
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main()
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from io import BytesIO
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import streamlit as st
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import streamlit.components.v1 as components
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import plotly.express as px
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# Load data from Excel URL with error handling
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def load_data(url):
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# Return the new statistics
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return latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before
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# Display the 3D bar chart for impact
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def display_3d_bar_chart(latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before):
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if latency_reduction is None:
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st.write("No data to display in the chart.")
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return
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# Create data for plotting
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metrics = ['Latency (ms)', 'Download Speed (Mbps)', 'Upload Speed (Mbps)']
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before = [avg_latency_before, avg_download_before, avg_upload_before]
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after = [latency_reduction, download_increase, upload_increase]
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impact_data = pd.DataFrame({
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'Metric': metrics,
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'Before': before,
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'After': after
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})
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# Create a 3D bar chart using Plotly
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fig = px.bar(
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impact_data,
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x='Metric',
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y=['Before', 'After'],
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barmode='group',
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title="Impact of Data Center on Latency and Bandwidth",
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labels={"value": "Speed / Latency", "Metric": "Metric"},
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height=400
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)
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# Display the chart in the Streamlit app
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st.plotly_chart(fig)
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# Main function to run the application
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def main():
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# Calculate the impact of adding the data center
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latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before = calculate_impact(df, center)
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if latency_reduction is not None:
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display_3d_bar_chart(latency_reduction, download_increase, upload_increase, avg_latency_before, avg_download_before, avg_upload_before)
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if __name__ == "__main__":
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main()
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