additional of full portfolio graphing api

backend/myapp/graph_all_holdings.py

@@ -0,0 +1,127 @@
+import json
+import holidays
+from pathlib import Path
+from datetime import datetime, timedelta
+from django.conf import settings
+import pytz
+import yfinance as yf
+from django.core.cache import cache
+from django.http import JsonResponse
+from django.utils.timezone import make_aware
+
+# Set your timezone, e.g., 'EST'
+timezone = pytz.timezone('EST')
+
+def load_transactions():
+    json_file_path = Path(settings.BASE_DIR) / 'data' / 'investments_data.json'
+    try:
+        with open(json_file_path, 'r') as file:
+            return json.load(file)
+    except Exception as e:
+        print(f"Error loading transactions: {e}")
+        return []
+
+def calculate_holdings_over_period(days):
+    transactions_data = load_transactions()
+    end_date = make_aware(datetime.now(), timezone)
+    start_date = end_date - timedelta(days=days)
+    current_holdings = {}
+    daily_holdings = {end_date: {}}
+
+    # Calculate current holdings
+    for transaction in transactions_data:
+        ticker = transaction["Ticker Symbol"]
+        shares = float(transaction["No. of Shares"])
+        transaction_type = transaction["Transaction Type"]
+        transaction_date = make_aware(datetime.strptime(transaction["Date"], '%d-%m-%Y'), timezone)
+        if transaction_date <= end_date:
+            current_holdings.setdefault(ticker, 0)
+            current_holdings[ticker] += shares if transaction_type == "BUY" else -shares
+
+    # Calculate daily holdings
+    for single_date in reversed([start_date + timedelta(n) for n in range(days)]):
+        daily_holdings[single_date] = current_holdings.copy()
+        for transaction in transactions_data:
+            transaction_date = make_aware(datetime.strptime(transaction["Date"], '%d-%m-%Y'), timezone)
+            if start_date < transaction_date <= single_date:
+                ticker = transaction["Ticker Symbol"]
+                shares = float(transaction["No. of Shares"])
+                transaction_type = transaction["Transaction Type"]
+                if transaction_type == "BUY":
+                    daily_holdings[single_date][ticker] -= shares
+                elif transaction_type == "SELL":
+                    daily_holdings[single_date][ticker] += shares
+
+    return daily_holdings
+
+def fetch_historical_prices_with_cache(ticker, start_date, end_date):
+    start_date_str = start_date.strftime('%Y-%m-%d')
+    end_date_str = end_date.strftime('%Y-%m-%d')
+    cache_key = f"{ticker}_{start_date_str}_{end_date_str}".replace(' ', '_').replace(':', '')
+
+    cached_data = cache.get(cache_key)
+    if cached_data is not None:
+        return cached_data
+
+    try:
+        stock = yf.Ticker(ticker)
+        historical_data = stock.history(start=start_date_str, end=end_date_str)
+        price_data = historical_data['Close']
+        if price_data.empty:
+            raise ValueError(f"No data for {ticker} from {start_date_str} to {end_date_str}")
+        cache.set(cache_key, price_data, timeout=86400)  # Cache for 1 day
+        return price_data
+    except Exception as e:
+        print(f"Error fetching historical data for {ticker}: {e}")
+        return None
+
+def is_market_open(date):
+    # Check if the date is a weekend
+    if date.weekday() >= 5:
+        return False
+
+    # Check for market holidays
+    us_holidays = holidays.US(years=date.year)
+    if date in us_holidays:
+        return False
+
+    return True
+
+def calculate_portfolio_value_over_period(days):
+    daily_holdings = calculate_holdings_over_period(days)
+    portfolio_value = {}
+    interval = '1d'
+
+    if days <= 7:
+        interval = '1h'  # hourly data for up to 7 days
+    elif days == 1:
+        interval = '1m'  # minute data for a single day
+
+    for single_date in daily_holdings:
+        if not is_market_open(single_date):
+            continue
+
+        daily_value = 0
+        for ticker, shares in daily_holdings[single_date].items():
+            if shares > 0:
+                price_data = fetch_historical_prices_with_cache(ticker, single_date, single_date + timedelta(days=1))
+                if price_data is not None:
+                    # Find the price for the specific part of the day
+                    price = price_data.get(single_date.strftime('%Y-%m-%d'))
+                    if price is not None:
+                        daily_value += price * shares
+
+        if daily_value > 0:
+            portfolio_value[single_date] = daily_value
+
+    return dict(sorted(portfolio_value.items()))
+
+def get_portfolio_value(request, days):
+    try:
+        days = int(days)
+    except ValueError:
+        return JsonResponse({"error": "Invalid number of days provided."}, status=400)
+
+    portfolio_values = calculate_portfolio_value_over_period(days)
+    formatted_data = [{"date": date.strftime('%Y-%m-%d'), "value": value} for date, value in portfolio_values.items()]
+    return JsonResponse(formatted_data, safe=False)

backend/myapp/urls.py

@@ -2,9 +2,11 @@
 from .current_stock_holdings import get_stock_holdings
 from .graph_stock_holdings import get_stock_history
 from .historic_stock_holdings import get_historic_stock_holdings
+from .graph_all_holdings import get_portfolio_value
 
 urlpatterns = [
     path('stock_holdings/', get_stock_holdings, name='stock_holdings'),
     path('graph_stock/<str:ticker>/', get_stock_history, name='graph_stock'),
-    path('historic_holdings/', get_historic_stock_holdings, name='all_holdings')
+    path('historic_holdings/', get_historic_stock_holdings, name='all_holdings'),
+    path('graph_portfolio/<int:days>/', get_portfolio_value, name='graph_portfolio'),
 ]