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"""UI component functions for the financial dashboard."""
import streamlit as st
import pandas as pd
import sys
import os
# Add parent directory to path for imports
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from utils.formatters import format_financial_value
from components.data_sources import get_profitability_metrics
def display_price_metrics(metrics: dict):
"""Display key price metrics in columns."""
st.markdown('<div class="section-title">📊 Price Metrics</div>', unsafe_allow_html=True)
col1, col2, col3, col4 = st.columns(4)
with col1:
st.metric("Current Price", f"${metrics['current_price']:.2f}",
f"{metrics['price_change']:+.2f}", delta_color="normal")
with col2:
st.metric("Day Change %", f"{metrics['price_change_pct']:+.2f}%",
None, delta_color="normal")
with col3:
st.metric("52W High", f"${metrics['high_52w']:.2f}")
with col4:
st.metric("52W Low", f"${metrics['low_52w']:.2f}")
def display_company_info(profile_info):
"""Display company information."""
st.markdown('<div class="section-title">📋 Company Information</div>', unsafe_allow_html=True)
if profile_info:
info_col1, info_col2 = st.columns(2)
with info_col1:
st.write(f"**Company Name:** {getattr(profile_info, 'name', 'N/A')}")
st.write(f"**Sector:** {getattr(profile_info, 'sector', 'N/A')}")
st.write(f"**Industry:** {getattr(profile_info, 'industry', 'N/A')}")
with info_col2:
st.write(f"**Country:** {getattr(profile_info, 'country', 'N/A')}")
st.write(f"**Exchange:** {getattr(profile_info, 'exchange', 'N/A')}")
st.write(f"**Website:** {getattr(profile_info, 'website', 'N/A')}")
def display_financial_metrics(income_stmt: pd.DataFrame):
"""Display financial metrics from income statement."""
st.markdown('<div class="section-title">💰 Financial Metrics</div>', unsafe_allow_html=True)
latest_income = income_stmt.iloc[0] if len(income_stmt) > 0 else None
if latest_income is not None:
# First row of metrics
fin_col1, fin_col2, fin_col3, fin_col4 = st.columns(4)
with fin_col1:
revenue = latest_income.get('total_revenue', 0)
if pd.notna(revenue) and revenue > 0:
st.metric("Total Revenue", format_financial_value(revenue))
else:
st.metric("Total Revenue", "N/A")
with fin_col2:
net_income = latest_income.get('net_income', 0)
if pd.notna(net_income) and net_income > 0:
st.metric("Net Income", format_financial_value(net_income))
else:
st.metric("Net Income", "N/A")
with fin_col3:
gross_profit = latest_income.get('gross_profit', 0)
if pd.notna(gross_profit) and gross_profit > 0:
st.metric("Gross Profit", format_financial_value(gross_profit))
else:
st.metric("Gross Profit", "N/A")
with fin_col4:
operating_income = latest_income.get('operating_income', 0)
if pd.notna(operating_income) and operating_income > 0:
st.metric("Operating Income", format_financial_value(operating_income))
else:
st.metric("Operating Income", "N/A")
# Second row of metrics
fin_col5, fin_col6, fin_col7, fin_col8 = st.columns(4)
with fin_col5:
eps = latest_income.get('diluted_earnings_per_share', 0)
if pd.notna(eps):
st.metric("EPS (Diluted)", f"${eps:.2f}")
else:
st.metric("EPS (Diluted)", "N/A")
with fin_col6:
ebitda = latest_income.get('ebitda', 0)
if pd.notna(ebitda) and ebitda > 0:
st.metric("EBITDA", format_financial_value(ebitda))
else:
st.metric("EBITDA", "N/A")
with fin_col7:
cogs = latest_income.get('cost_of_revenue', 0)
if pd.notna(cogs) and cogs > 0:
st.metric("Cost of Revenue", format_financial_value(cogs))
else:
st.metric("Cost of Revenue", "N/A")
with fin_col8:
rd_expense = latest_income.get('research_and_development_expense', 0)
if pd.notna(rd_expense) and rd_expense > 0:
st.metric("R&D Expense", format_financial_value(rd_expense))
else:
st.metric("R&D Expense", "N/A")
def display_income_statement(income_stmt: pd.DataFrame):
"""Display formatted income statement table."""
st.markdown("### Income Statement")
if not income_stmt.empty:
display_columns = [
'period_ending',
'total_revenue',
'cost_of_revenue',
'gross_profit',
'operating_income',
'net_income',
'diluted_earnings_per_share',
'ebitda'
]
available_cols = [col for col in display_columns if col in income_stmt.columns]
financial_display = income_stmt[available_cols].copy()
for col in financial_display.columns:
if col != 'period_ending':
financial_display[col] = financial_display[col].apply(
lambda x: format_financial_value(x)
)
st.dataframe(financial_display, use_container_width=True, hide_index=True)
def display_profitability_metrics(income_stmt: pd.DataFrame):
"""Display profitability metrics."""
st.markdown("### Profitability Metrics")
prof_col1, prof_col2 = st.columns(2)
latest_data = income_stmt.iloc[0]
metrics = get_profitability_metrics(latest_data)
with prof_col1:
if "gross_margin" in metrics:
st.metric("Gross Margin", f"{metrics['gross_margin']:.2f}%")
if "net_margin" in metrics:
st.metric("Net Profit Margin", f"{metrics['net_margin']:.2f}%")
with prof_col2:
if "operating_margin" in metrics:
st.metric("Operating Margin", f"{metrics['operating_margin']:.2f}%")
if len(income_stmt) > 1:
prev_revenue = income_stmt.iloc[1].get('total_revenue', 0)
total_rev = latest_data.get('total_revenue', 0)
if prev_revenue and prev_revenue > 0:
revenue_growth = ((total_rev - prev_revenue) / prev_revenue) * 100
st.metric("Revenue Growth (YoY)", f"{revenue_growth:+.2f}%")
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