full functioning daily view

backend/myapp/graph_stock_holdings.py

@@ -36,7 +36,7 @@ def get_stock_history(request, ticker):
     historical_prices = stock.history(start=start_date.strftime('%Y-%m-%d'), end=end_date.strftime('%Y-%m-%d'))
 
     # Check if data is sparse and fetch hourly data if necessary
-    if len(historical_prices) < 10:
+    if len(historical_prices) < 80:
         historical_prices = stock.history(period="1mo", interval="1h")
 
     historical_values = []

backend/myapp/graph_stock_holdings_day.py

@@ -9,27 +9,65 @@
 # Your timezone, for example, 'UTC'
 timezone = pytz.timezone('EST')
 
-def get_stock_history(request, ticker):
+def get_current_shares_held(ticker):
+    if not ticker:
+        return JsonResponse({"error": "Ticker symbol is required."}, status=400)
+
+    # Define the path to the JSON file
+    json_file_path = Path(settings.BASE_DIR) / 'data' / 'investments_data.json'
+
+    # Open the JSON file and load its content
+    with open(json_file_path, 'r') as file:
+        transactions_data = json.load(file)
+
+    transactions = [t for t in transactions_data if t['Ticker Symbol'] == ticker]
+
+    if not transactions:
+        return JsonResponse({"error": "No transactions found for given ticker."}, status=404)
+
+    current_shares = 0.0
+
+    # Calculate the current number of shares held
+    for transaction in transactions:
+        shares = float(transaction["No. of Shares"])
+        if transaction["Transaction Type"] == "BUY":
+            current_shares += shares
+        elif transaction["Transaction Type"] == "SELL":
+            current_shares -= shares
+
+    return current_shares
+
+def get_stock_history_day(request, ticker):
     if not ticker:
         return JsonResponse({"error": "Ticker symbol is required."}, status=400)
 
     stock = yf.Ticker(ticker)
-    # Fetch data for the last 24 hours with granular intervals (e.g., 5 minutes)
-    end_date = datetime.now(tz=timezone)
-    start_date = end_date - timedelta(days=1)
-    historical_prices = stock.history(start=start_date.strftime('%Y-%m-%d'), end=end_date.strftime('%Y-%m-%d'), interval="5m")
+    # Get today's date and yesterday's date in the specified timezone
+    today = datetime.now(tz=timezone).date()
+    yesterday = today - timedelta(days=1)
+
+    # Fetch today's data
+    today_data = stock.history(period='1d', interval='1m', start=today, end=today + timedelta(days=1))
+
+    if today_data.empty:  # If today's data is empty, assume the market is closed
+        # Fetch previous day's data
+        historical_prices = stock.history(period='1d', interval='1m', start=yesterday, end=today)
+    else:
+        historical_prices = today_data
 
+    shares_held = get_current_shares_held(ticker)
+
     # Fetch the previous day's closing price
     previous_day_data = stock.history(period="2d", interval="1d")
     if len(previous_day_data) < 2:
         return JsonResponse({"error": "Previous day's data not available"}, status=404)
     previous_close = previous_day_data['Close'].iloc[-2]
+    previous_close_paid = shares_held * previous_close
 
-    # Convert data to the desired timezone and format for response
     historical_values = [{
-        "datetime": date.tz_convert(timezone).strftime('%Y-%m-%d %H:%M:%S'),
-        "value": row['Close'],
-        "value_paid": previous_close
+        "date": date.tz_convert(timezone).strftime('%Y-%m-%d %H:%M:%S'),
+        "value": row['Close'] * shares_held,  # Current value of shares held
+        "value_paid": previous_close_paid  # Value based on previous day's close
     } for date, row in historical_prices.iterrows()]
 
-    return JsonResponse(historical_values, safe=False)
+    return JsonResponse(historical_values, safe=False)

backend/myapp/urls.py

@@ -2,15 +2,15 @@
 from .current_stock_holdings import get_stock_holdings
 from .current_stock_holdings_day import get_stock_holdings_day
 from .graph_stock_holdings import get_stock_history
-from .graph_stock_holdings_day import get_stock_history
+from .graph_stock_holdings_day import get_stock_history_day
 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('stock_holdings_day/', get_stock_holdings_day, name='stock_holdings_day'),
     path('graph_stock/<str:ticker>/', get_stock_history, name='graph_stock'),
-    path('graph_stock_day/<str:ticker>/', get_stock_history, name='graph_stock_day'),
+    path('graph_stock_day/<str:ticker>/', get_stock_history_day, name='graph_stock_day'),
     path('historic_holdings/', get_historic_stock_holdings, name='all_holdings'),
     path('graph_portfolio/<int:days>/', get_portfolio_value, name='graph_portfolio'),
 ]

frontend/src/StockGraphing.js

@@ -2,16 +2,23 @@ import React, { useState, useEffect } from 'react';
 import { Line } from 'react-chartjs-2';
 import 'chart.js/auto';
 
-function StockGraph({ ticker }) { // Use destructuring to get the ticker prop
+function StockGraph({ ticker, timeFrame }) { // Use destructuring to get the ticker prop
     const [stockData, setStockData] = useState([]);
 
     useEffect(() => {
         // Ensure the ticker value is included in the fetch URL
-        fetch(`http://localhost:8000/api/graph_stock/${ticker}/`)
-            .then(response => response.json())
-            .then(data => setStockData(data))
-            .catch(error => console.error('Error fetching data:', error));
-    }, [ticker]); // Include ticker in the dependency array
+        if (timeFrame == 'All') {
+            fetch(`http://localhost:8000/api/graph_stock/${ticker}/`)
+                .then(response => response.json())
+                .then(data => setStockData(data))
+                .catch(error => console.error('Error fetching data:', error));
+        } else {
+            fetch(`http://localhost:8000/api/graph_stock_day/${ticker}/`)
+                .then(response => response.json())
+                .then(data => setStockData(data))
+                .catch(error => console.error('Error fetching data:', error));
+        }
+    }, [ticker]);
 
     const chartData = {
         labels: stockData.map(data => data.date),