mirror of
https://github.com/777r1NTR/FX-QUANT-SCAN.git
synced 2026-07-27 17:37:46 +00:00
St.jess777
386 lines
14 KiB
Python
386 lines
14 KiB
Python
import streamlit as st
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import pandas as pd
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import plotly.graph_objects as go
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import plotly.express as px
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import yfinance as yf
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from datetime import datetime, timedelta
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import sys
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import os
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# Import your existing zone locator function
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sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'core'))
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from zone_locator import generate_current_zone_snapshot, TICKER_LIST, ZONE_DEFINITIONS
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def zone_locator():
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# Custom CSS for enhanced styling
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st.markdown("""
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<style>
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.zone-header {
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background: linear-gradient(90deg, #1e40af 0%, #3b82f6 100%);
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color: white;
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padding: 1.5rem;
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border-radius: 10px;
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margin-bottom: 2rem;
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text-align: center;
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}
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.zone-card {
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background: linear-gradient(145deg, #f8fafc 0%, #e2e8f0 100%);
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padding: 1.5rem;
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border-radius: 12px;
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box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
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margin: 1rem 0;
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border-left: 5px solid;
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color: #374151;
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}
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.zone-reset { border-left-color: #A9A9A9; background: linear-gradient(145deg, #f8fafc 0%, #f1f5f9 100%); }
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.zone-clearance { border-left-color: #FF5555; background: linear-gradient(145deg, #fef2f2 0%, #fecaca 100%); }
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.zone-discount { border-left-color: #FF9999; background: linear-gradient(145deg, #fff5f5 0%, #fed7d7 100%); }
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.zone-budget { border-left-color: #ADD8E6; background: linear-gradient(145deg, #eff6ff 0%, #dbeafe 100%); }
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.zone-fair { border-left-color: #90EE90; background: linear-gradient(145deg, #f0fdf4 0%, #dcfce7 100%); }
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.zone-plus { border-left-color: #FFA500; background: linear-gradient(145deg, #fffbeb 0%, #fed7aa 100%); }
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.zone-premium { border-left-color: #FFD700; background: linear-gradient(145deg, #fefce8 0%, #fef08a 100%); }
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.zone-premium-plus { border-left-color: #DA70D6; background: linear-gradient(145deg, #faf5ff 0%, #e9d5ff 100%); }
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.metric-box {
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background: linear-gradient(145deg, #f8fafc 0%, #e2e8f0 100%);
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padding: 1rem;
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border-radius: 8px;
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text-align: center;
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margin: 0.5rem 0;
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border: 2px solid #e2e8f0;
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}
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.zone-legend {
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background: linear-gradient(145deg, #f0f9ff 0%, #e0f2fe 100%);
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padding: 1rem;
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border-radius: 8px;
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margin: 1rem 0;
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color: #374151;
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}
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</style>
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""", unsafe_allow_html=True)
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# Header
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st.markdown("""
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<div class="zone-header">
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<h1>🎯 Zone Locator</h1>
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<p>Identify if currency pairs are cheap, fairly priced, or expensive based on historical zones</p>
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</div>
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""", unsafe_allow_html=True)
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# Control Panel
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st.markdown("## ⚙️ Analysis Controls")
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col1, col2, col3 = st.columns([2, 2, 1])
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with col1:
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selected_pair = st.selectbox(
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"🎯 Select Currency Pair",
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TICKER_LIST,
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help="Choose a currency pair to analyze its current zone position"
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)
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with col2:
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analysis_period = st.selectbox(
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"📅 Analysis Period",
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["1 Month", "3 Months", "6 Months", "1 Year"],
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index=2,
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help="Historical period for zone context visualization"
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)
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with col3:
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refresh_data = st.button("🔄 Refresh Data", type="primary")
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# Zone Legend
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st.markdown("### 📊 Zone Classification Legend")
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zone_info = {
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'Premium+': {'color': '#DA70D6', 'desc': 'Extreme highs, very expensive'},
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'Premium': {'color': '#FFD700', 'desc': 'Historical highs, expensive'},
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'Plus+': {'color': '#FFA500', 'desc': 'Above fair value'},
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'Fair': {'color': '#90EE90', 'desc': 'Balanced pricing'},
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'Budget': {'color': '#ADD8E6', 'desc': 'Good value territory'},
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'Discount': {'color': '#FF9999', 'desc': 'Below fair value'},
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'Clearance': {'color': '#FF5555', 'desc': 'Very cheap levels'},
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'Reset': {'color': '#A9A9A9', 'desc': 'Historical lows, extreme'}
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}
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cols = st.columns(4)
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for i, (zone, info) in enumerate(zone_info.items()):
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with cols[i % 4]:
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st.markdown(f"""
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<div class="zone-legend">
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<div style="background: {info['color']}; height: 4px; margin-bottom: 8px; border-radius: 2px;"></div>
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<strong>{zone}</strong><br>
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<small>{info['desc']}</small>
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</div>
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""", unsafe_allow_html=True)
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st.markdown("---")
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# Get zone data
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try:
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with st.spinner("🔍 Loading zone data..."):
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if refresh_data or 'zone_data' not in st.session_state:
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zone_df = generate_current_zone_snapshot()
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st.session_state.zone_data = zone_df
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else:
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zone_df = st.session_state.zone_data
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if zone_df.empty:
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st.warning("⚠️ No zone data available")
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return
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except Exception as e:
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st.error(f"❌ Error loading zone data: {str(e)}")
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return
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# Find selected pair data
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selected_data = zone_df[zone_df['Ticker'] == selected_pair]
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if selected_data.empty:
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st.warning(f"⚠️ No data available for {selected_pair}")
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return
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current_zone = selected_data.iloc[0]['Current Zone']
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current_price = selected_data.iloc[0]['Current Price']
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# Zone color mapping
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zone_colors = {
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'Premium+': '#DA70D6',
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'Premium': '#FFD700',
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'Plus+': '#FFA500',
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'Fair': '#90EE90',
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'Budget': '#ADD8E6',
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'Discount': '#FF9999',
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'Clearance': '#FF5555',
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'Reset': '#A9A9A9'
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}
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zone_classes = {
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'Premium+': 'zone-premium-plus',
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'Premium': 'zone-premium',
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'Plus+': 'zone-plus',
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'Fair': 'zone-fair',
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'Budget': 'zone-budget',
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'Discount': 'zone-discount',
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'Clearance': 'zone-clearance',
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'Reset': 'zone-reset'
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}
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zone_color = zone_colors.get(current_zone, '#6b7280')
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zone_class = zone_classes.get(current_zone, 'zone-neutral')
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# Current Zone Analysis
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st.markdown("## 📍 Current Zone Analysis")
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col1, col2 = st.columns([1, 2])
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with col1:
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st.markdown(f"""
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<div class="zone-card {zone_class}">
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<div style="font-size: 1.2rem; font-weight: 600; margin-bottom: 0.5rem;">Current Zone</div>
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<div style="font-size: 2rem; font-weight: bold; color: {zone_color};">
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{current_zone}
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</div>
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<div style="font-size: 1.5rem; font-weight: bold; color: #1f2937;">{current_price:.5f}</div>
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<div style="color: #6b7280; font-size: 0.9rem;">
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Updated: {datetime.now().strftime('%H:%M:%S')}
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</div>
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</div>
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""", unsafe_allow_html=True)
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with col2:
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# Zone distribution chart
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zone_counts = zone_df['Current Zone'].value_counts()
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fig_dist = go.Figure(data=[
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go.Bar(
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x=zone_counts.index,
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y=zone_counts.values,
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marker_color=[zone_colors.get(zone, '#6b7280') for zone in zone_counts.index],
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text=zone_counts.values,
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textposition='auto',
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)
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])
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fig_dist.update_layout(
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title="Current Zone Distribution Across All Pairs",
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xaxis_title="Zone",
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yaxis_title="Number of Pairs",
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height=300,
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template="plotly_white"
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)
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st.plotly_chart(fig_dist, use_container_width=True)
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# Zone interpretation
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zone_interpretations = {
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'Reset': {
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'emoji': '⚪',
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'title': 'RESET Zone - Extreme Oversold',
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'description': 'This currency pair is at historical lows. Maximum risk/reward potential.',
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'strategy': 'Consider: Contrarian plays, small position sizing, wait for confirmation',
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'risk': 'Very High - New lows possible, fundamental deterioration likely'
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},
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'Clearance': {
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'emoji': '🔴',
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'title': 'CLEARANCE Zone - Very Cheap',
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'description': 'Significantly below normal levels. Strong oversold conditions.',
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'strategy': 'Consider: Value plays, gradual accumulation, support levels',
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'risk': 'High - Further decline possible, but good risk/reward'
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},
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'Discount': {
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'emoji': '🟡',
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'title': 'DISCOUNT Zone - Below Fair Value',
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'description': 'Trading below historical average. Good value territory.',
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'strategy': 'Consider: Buying opportunities, normal position sizing',
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'risk': 'Medium - Normal volatility, favorable entry levels'
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},
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'Budget': {
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'emoji': '🔵',
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'title': 'BUDGET Zone - Good Value',
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'description': 'Attractive pricing with room for upside to fair value.',
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'strategy': 'Consider: Long positions, trend following, value plays',
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'risk': 'Low-Medium - Good risk/reward balance'
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},
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'Fair': {
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'emoji': '🟢',
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'title': 'FAIR Zone - Balanced Pricing',
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'description': 'Trading around historical average levels. Neutral valuation.',
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'strategy': 'Consider: Momentum strategies, breakout plays, trend following',
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'risk': 'Medium - Normal volatility expected'
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},
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'Plus+': {
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'emoji': '🟠',
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'title': 'PLUS+ Zone - Above Fair Value',
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'description': 'Trading above normal levels. Momentum or early overvaluation.',
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'strategy': 'Consider: Momentum continuation, reduced position sizing',
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'risk': 'Medium-High - Correction risk increasing'
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},
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'Premium': {
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'emoji': '🟡',
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'title': 'PREMIUM Zone - Expensive Territory',
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'description': 'At historically high levels. Strong momentum or overvaluation.',
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'strategy': 'Consider: Trend continuation, tight stops, take profits',
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'risk': 'High - Significant correction risk'
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},
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'Premium+': {
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'emoji': '🟣',
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'title': 'PREMIUM+ Zone - Extreme Highs',
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'description': 'At extreme historical levels. Maximum overvaluation risk.',
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'strategy': 'Consider: Short opportunities, minimal long exposure',
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'risk': 'Very High - Major correction likely'
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}
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}
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interpretation = zone_interpretations.get(current_zone, zone_interpretations['Fair'])
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st.markdown(f"""
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<div class="zone-card {zone_class}">
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<h3>{interpretation['emoji']} {interpretation['title']}</h3>
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<p><strong>{interpretation['description']}</strong></p>
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<p><strong>Strategy Considerations:</strong> {interpretation['strategy']}</p>
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<p><strong>Risk Level:</strong> {interpretation['risk']}</p>
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</div>
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""", unsafe_allow_html=True)
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st.markdown("---")
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# Historical Price Chart
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st.markdown("## 📈 Price Chart with Zone Context")
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try:
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period_map = {
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"1 Month": "1mo",
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"3 Months": "3mo",
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"6 Months": "6mo",
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"1 Year": "1y"
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}
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ticker = yf.Ticker(selected_pair)
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hist_data = ticker.history(period=period_map[analysis_period])
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if not hist_data.empty:
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# Create candlestick chart
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fig = go.Figure()
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fig.add_trace(go.Candlestick(
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x=hist_data.index,
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open=hist_data['Open'],
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high=hist_data['High'],
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low=hist_data['Low'],
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close=hist_data['Close'],
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name=selected_pair,
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increasing_line_color='#059669',
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decreasing_line_color='#dc2626'
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))
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# Add current price line
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fig.add_hline(
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y=current_price,
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line_dash="dash",
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line_color=zone_color,
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annotation_text=f"Current: {current_price:.5f} ({current_zone})"
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)
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fig.update_layout(
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title=f"{selected_pair} - Current Zone: {current_zone}",
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xaxis_title="Date",
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yaxis_title="Price",
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height=500,
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template="plotly_white",
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showlegend=False
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)
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st.plotly_chart(fig, use_container_width=True)
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else:
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st.warning("⚠️ No historical data available for chart")
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except Exception as e:
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st.error(f"❌ Error creating chart: {str(e)}")
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# All Zones Summary
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st.markdown("## 📊 All Pairs Zone Summary")
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# Style the dataframe
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styled_df = zone_df.copy()
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styled_df['Current Price'] = styled_df['Current Price'].round(5)
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st.dataframe(
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styled_df,
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use_container_width=True,
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column_config={
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"Ticker": st.column_config.TextColumn("Currency Pair", width="medium"),
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"Current Zone": st.column_config.TextColumn("Zone", width="medium"),
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"Current Price": st.column_config.NumberColumn("Price", width="medium", format="%.5f")
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}
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)
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# Zone Statistics
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col1, col2, col3 = st.columns(3)
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with col1:
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expensive_zones = zone_df[zone_df['Current Zone'].isin(['Premium+', 'Premium', 'Plus+'])].shape[0]
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st.metric("🔴 Expensive Pairs", expensive_zones)
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with col2:
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fair_zones = zone_df[zone_df['Current Zone'].isin(['Fair', 'Budget'])].shape[0]
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st.metric("🟢 Fair Value Pairs", fair_zones)
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with col3:
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cheap_zones = zone_df[zone_df['Current Zone'].isin(['Discount', 'Clearance', 'Reset'])].shape[0]
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st.metric("🔵 Cheap Pairs", cheap_zones)
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# Footer
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st.markdown("---")
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st.markdown("""
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<div style="text-align: center; color: #6b7280; padding: 1rem;">
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<p><strong>Zone Locator</strong> - Historical zone analysis for informed trading decisions</p>
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</div>
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""", unsafe_allow_html=True)
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if __name__ == "__main__":
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zone_locator() |