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import streamlit as st
import pandas as pd
import numpy as np
import datetime
from simple_salesforce import Salesforce
from modules.simulator import simulate_data
from modules.filters import apply_filters
from modules.visuals import display_dashboard, display_charts
# Salesforce Authentication (replace with your Salesforce login credentials)
sf = Salesforce(username='greenenergy@vedavathi.com', password='Vedavathi@04', security_token='jqe4His8AcuFJucZz5NBHfGU')
st.set_page_config(page_title="Vedavathi Smart Pole Monitoring", layout="wide")
st.title("📡 Vedavathi Smart Pole Monitoring - PoC Simulator")
# Sidebar for Simulation Controls
st.sidebar.header("🛠️ Simulation Controls")
num_poles = st.sidebar.slider("Number of Poles", min_value=5, max_value=50, value=10)
simulate_faults = st.sidebar.checkbox("Simulate Random Faults", value=True)
# Simulate Data for Poles
df = simulate_data(num_poles, simulate_faults)
# Sidebar for Filter Data
st.sidebar.header("📂 Filter Data")
alert_filter = st.sidebar.multiselect("Alert Level", ["Green", "Yellow", "Red"], default=["Green", "Yellow", "Red"])
cam_filter = st.sidebar.selectbox("Camera Status", ["All", "Online", "Offline"], index=0)
# Apply Filters
filtered_df = apply_filters(df, alert_filter, cam_filter)
# Display System Summary
display_dashboard(df)
# Pole Monitoring Table
st.subheader("📋 Pole Monitoring Table")
st.dataframe(filtered_df, use_container_width=True)
# Display Charts
display_charts(df)
# Salesforce Integration (e.g., fetch records from Salesforce)
def fetch_salesforce_data():
# Example: Querying Salesforce for related data
query = "SELECT Id, Name, Alert_Level__c, Camera_Status__c FROM Pole__c"
result = sf.query_all(query)
return result['records']
# Fetch Salesforce data
sf_data = fetch_salesforce_data()
# Convert the Salesforce data into a Pandas DataFrame
sf_df = pd.DataFrame(sf_data)
# Display Salesforce Data in a table format
st.subheader("📊 Salesforce Data")
st.dataframe(sf_df[['Name', 'Alert_Level__c', 'Camera_Status__c']], use_container_width=True)
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