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PropAPIS for Real Estate Investors

Automate property analysis, identify undervalued opportunities, and scale your investment portfolio with real-time data from 20+ platforms.

Why Investors Choose PropAPIS​

Whether acquiring your first rental property or managing a 500+ unit portfolio, data is your competitive advantage. PropAPIS gives you institutional-grade market intelligence at a fraction of the cost.

Key Benefits​

  • Automated Deal Sourcing: Find undervalued properties across 20+ platforms before competitors
  • Investment Analytics: Calculate NOI, cap rates, cash-on-cash returns in seconds
  • Portfolio Valuation: Track portfolio value weekly instead of quarterly
  • Market Intelligence: Identify high-growth markets and emerging opportunities
  • Real-Time Alerts: Get notified when properties matching your criteria hit the market

Common Challenges and Solutions​

Finding Deals Before Competitors​

The Problem: By the time you see a property on Zillow, 50+ other investors have already seen it. Best deals receive multiple offers within hours.

The Solution: Automated monitoring across Zillow, Realtor.com, Redfin with real-time alerts.

from propapis import PropAPIS

api = PropAPIS(api_key='your_api_key')

# Find undervalued properties
def find_undervalued_deals(market):
    listings = api.platforms.zillow.search_listings(
        location=market,
        status='active',
        property_type='Single Family',
        max_results=500
    )

    undervalued = []
    for prop in listings:
        # Compare listing price to estimates
        zestimate = prop.zestimate
        list_price = prop.price

        if zestimate and list_price < zestimate * 0.85:
            discount = ((zestimate - list_price) / zestimate) * 100
            undervalued.append({
                'address': prop.address,
                'price': list_price,
                'zestimate': zestimate,
                'discount': discount
            })

    return sorted(undervalued, key=lambda x: x['discount'], reverse=True)

# Find deals in Austin
deals = find_undervalued_deals('Austin, TX')
for deal in deals[:5]:
    print(f"{deal['address']}")
    print(f"  Listed: ${deal['price']:,} | Est: ${deal['zestimate']:,}")
    print(f"  Discount: {deal['discount']:.1f}%")

Analyzing Investment Returns​

The Problem: Manual spreadsheets take hours per property. Cannot analyze 50+ properties weekly.

The Solution: Automated financial analysis with real-time data.

def calculate_investment_metrics(address):
    # Get property data
    prop = api.platforms.zillow.get_property(address)

    # Investment metrics
    purchase_price = prop.price
    rent_estimate = prop.rent_zestimate

    # Assumptions
    down_payment_pct = 0.25
    interest_rate = 0.065
    loan_term_years = 30

    # Calculate metrics
    down_payment = purchase_price * down_payment_pct
    loan_amount = purchase_price - down_payment

    # Monthly payment (P&I)
    monthly_rate = interest_rate / 12
    n_payments = loan_term_years * 12
    monthly_payment = loan_amount * (monthly_rate * (1 + monthly_rate)**n_payments) / ((1 + monthly_rate)**n_payments - 1)

    # Annual metrics
    annual_rent = rent_estimate * 12
    annual_debt_service = monthly_payment * 12

    # NOI (simplified)
    operating_expenses = annual_rent * 0.30  # 30% rule
    noi = annual_rent - operating_expenses

    # Returns
    cap_rate = (noi / purchase_price) * 100
    cash_flow = noi - annual_debt_service
    cash_on_cash = (cash_flow / down_payment) * 100

    return {
        'address': prop.address,
        'purchase_price': purchase_price,
        'annual_rent': annual_rent,
        'noi': noi,
        'cap_rate': cap_rate,
        'cash_on_cash': cash_on_cash,
        'monthly_cash_flow': cash_flow / 12
    }

# Analyze property
metrics = calculate_investment_metrics('123 Main St, Austin, TX')
print(f"Cap Rate: {metrics['cap_rate']:.2f}%")
print(f"Cash-on-Cash: {metrics['cash_on_cash']:.2f}%")
print(f"Monthly Cash Flow: ${metrics['monthly_cash_flow']:,.0f}")

Portfolio Monitoring​

The Problem: Cannot track 50+ properties manually. Portfolio value unknown until appraisal.

The Solution: Automated portfolio valuation tracking.

# Define portfolio
portfolio = [
    '123 Main St, Austin, TX',
    '456 Oak Ave, Nashville, TN',
    '789 Pine Rd, Denver, CO'
]

# Track portfolio value
total_value = 0
total_equity = 0

for address in portfolio:
    prop = api.platforms.zillow.get_property(address)

    current_value = prop.zestimate
    purchase_price = 450000  # From records
    loan_balance = 360000    # From records

    equity = current_value - loan_balance
    appreciation = current_value - purchase_price

    total_value += current_value
    total_equity += equity

    print(f"{address}")
    print(f"  Value: ${current_value:,} (${appreciation:+,} gain)")
    print(f"  Equity: ${equity:,}")

print(f"\nPortfolio Value: ${total_value:,}")
print(f"Total Equity: ${total_equity:,}")

Market Selection​

The Problem: Which markets offer best returns? Where to invest next?

The Solution: Compare markets across multiple metrics.

# Compare markets
markets = ['Austin, TX', 'Nashville, TN', 'Denver, CO', 'Phoenix, AZ']

for market in markets:
    data = api.platforms.zillow.get_market_trends(location=market)

    print(f"\n{market}")
    print(f"  Median Price: ${data.median_price:,}")
    print(f"  YoY Growth: {data.yoy_change:+.1f}%")
    print(f"  Avg Days on Market: {data.avg_dom:.0f}")
    print(f"  Months Supply: {data.months_supply:.1f}")

    # Investment score (higher is better)
    score = data.yoy_change - (data.avg_dom / 10)
    print(f"  Investment Score: {score:.1f}")

Use Case Examples​

Buy and Hold Investor​

Screen 1000+ properties per month, analyze top 50, make offers on best 10 deals.

Fix and Flip Investor​

Find distressed properties, calculate ARV using sold comps, estimate renovation profit.

Wholesale Investor​

Identify off-market opportunities, calculate equity positions, find motivated sellers.

BRRRR Investor​

Find value-add properties, estimate post-renovation value, calculate refinance potential.

Multi-Family Investor​

Analyze 5+ unit properties, calculate per-unit economics, compare cap rates across markets.

Quick Start​

from propapis import PropAPIS

api = PropAPIS(api_key='your_api_key')

# Find investment properties
listings = api.platforms.zillow.search_listings(
    location='Austin, TX',
    min_bedrooms=3,
    max_price=400000,
    property_type='Single Family'
)

for prop in listings[:10]:
    cap_rate = (prop.rent_zestimate * 12 / prop.price) * 100
    print(f"{prop.address} - ${prop.price:,} | Cap Rate: {cap_rate:.2f}%")

For detailed API documentation, see our API Reference.

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