app.py

import streamlit as st
import pandas as pd
import os
from modules.simulator import simulate_data
from modules.filters import apply_filters
from modules.visuals import display_dashboard, display_charts
from simple_salesforce import Salesforce, SalesforceLogin
from dotenv import load_dotenv


# Load environment variables
load_dotenv()

# Set this as the first Streamlit command
st.set_page_config(page_title="Vedavathi Smart Pole Monitoring", layout="wide")

# Connect to Salesforce
sf = Salesforce(
    username=os.getenv("SF_USERNAME"),
    password=os.getenv("SF_PASSWORD"),
    security_token=os.getenv("SF_TOKEN"),
    domain="login"  # or "test" for sandbox
)

# Function to fetch Pole data
def fetch_pole_data():
    query = """
        SELECT Id, Name, Site__c, Date__c, Latitude__c, Longitude__c,
               Solar_Generation__c, Wind_Generation__c, Power_Required__c,
               Power_Sufficient__c, Camera_Status__c, Tilt_Angle__c, Vibration__c, Anomalies__c
        FROM Pole__c
        LIMIT 100
    """
    result = sf.query(query)
    records = result["records"]
    df = pd.DataFrame(records).drop(columns=["attributes"])
    return df

# Get and transform data
df = fetch_pole_data()
df = df.rename(columns={
    "Name": "Pole ID",
    "Site__c": "Site",
    "Date__c": "Date",
    "Latitude__c": "Latitude",
    "Longitude__c": "Longitude",
    "Solar_Generation__c": "Solar Gen (kWh)",
    "Wind_Generation__c": "Wind Gen (kWh)",
    "Power_Required__c": "Power Required (kWh)",
    "Power_Sufficient__c": "Power Sufficient",
    "Camera_Status__c": "Camera Status",
    "Tilt_Angle__c": "Tilt (°)",
    "Vibration__c": "Vibration (g)",
    "Anomalies__c": "Anomalies"
})

# Format date
if "Date" in df.columns:
    df["Date"] = pd.to_datetime(df["Date"]).dt.date

# Display the expander with the table
with st.expander("📋 Pole Monitoring Table", expanded=True):
    st.dataframe(df, use_container_width=True)


# View poles
with st.expander("Pole__c"):
    df_poles = fetch_data("Pole__c", fields="Id, Name")  # Update fields after checking above
    st.dataframe(df_poles)

# View sensor data
with st.expander("SensorData__c"):
    df_sensors = fetch_data("SensorData__c", fields="Id, Pole__c")  # Adjust if needed
    st.dataframe(df_sensors)

# View alerts
with st.expander("Alert__c"):
    df_alerts = fetch_data("Alert__c", fields="Id, Pole__c, Alert_Level__c")  # Adjust if needed
    st.dataframe(df_alerts)