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import streamlit as st
import pandas as pd
from src.utils import streamlit_function
from src.utils.logger import get_logger
from src.services.mongo_db_service import retrieve_documents
from src.utils.common_functions import prepare_comparison_df
logger = get_logger()
streamlit_function.config_homepage()
st.title("📊 ESG Report Comparison Dashboard")
METRIC_OPTIONS = {
"Report Metadata": ["report_metadata"],
"Environmental Parameters": [
"Emissions", "Energy Consumption", "Water Withdrawal", "Water Discharge",
"Waste Generation", "Waste Disposal", "Waste Recovery"
],
"Social Parameters": [
"Human Rights Training Coverage", "LTIFR", "Other Safety Incidents",
"Health & Safety Training Coverage", "Grievances Reported",
"Third-party Assessment Coverage", "CSR Beneficiaries", "Female Wage Share",
"Wages by Location", "Well-being Cost", "Worker Well-being Coverage",
"Employee Well-being Coverage", "Turnover Count", "Workforce Gender Diversity"
],
"Governance Parameters": [
"Non-compliance Instances", "Disciplinary Actions", "Consumer Complaints",
"Customer Data Breaches", "Governance Diversity", "Purchase Concentration",
"Sales Concentration", "Related Party Transactions"
],
"Materiality": ["material_topics"]
}
ESG_EXTRACTOR_COLLECTION = "esg_report_extracts"
company_docs = retrieve_documents(collection_name=ESG_EXTRACTOR_COLLECTION)
available_company_data = [doc["_id"] for doc in company_docs if "_id" in doc]
selected_companies = st.multiselect(
"Select up to 3 companies",
options=available_company_data,
max_selections=3
)
def get_all_years(docs) -> list:
years = set()
for doc in docs:
if "esg_reports" in doc and isinstance(doc["esg_reports"], dict):
years.update(doc["esg_reports"].keys())
return sorted(years, reverse=True)
def highlight_missing_values(df):
return df.style.map(lambda v: "background-color: #ffe6e6" if pd.isna(v) or str(v).strip() in ["", "nan", "None", "Not Available","N/A"] else "background-color: #e6ffe6")
def extract_company_name_from_doc(doc, default_name):
return doc.get("report_metadata", {}).get("company_legal_name", default_name)
if selected_companies:
all_years = get_all_years(company_docs)
selected_year = st.selectbox(
"Select a report year (applies to all selected companies)",
options=["-- Select Year --"] + all_years,
key="common_year"
)
if selected_year != "-- Select Year --":
tabs = st.tabs(list(METRIC_OPTIONS.keys()))
metric_categories = list(METRIC_OPTIONS.keys())
for i, tab in enumerate(tabs):
with tab:
st.subheader(metric_categories[i])
metric_keys = METRIC_OPTIONS[metric_categories[i]]
for metric in metric_keys:
st.markdown(f"### {metric}")
comparison_df = prepare_comparison_df(
selected_companies,
selected_year,
metric,
company_docs
)
if comparison_df is not None:
st.dataframe(highlight_missing_values(comparison_df), use_container_width=True)
else:
st.warning(f"No data found for **{metric}** in {selected_year}")
else:
st.info("Please select a year to view report comparisons.")
else:
st.info("Please select at least one company to continue.") |