added daily graphing on click

backend/myapp/current_stock_holdings_day.py

@@ -0,0 +1,70 @@
+import json
+from django.http import JsonResponse
+from django.conf import settings
+from pathlib import Path
+import yfinance as yf
+
+def get_stock_holdings_day(request):
+    # 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)
+
+    # Process transactions to determine current holdings
+    holdings = {}
+    for transaction in transactions_data:
+        ticker = transaction["Ticker Symbol"]
+        shares = float(transaction["No. of Shares"])
+        transaction_type = transaction["Transaction Type"]
+
+        if ticker not in holdings:
+            holdings[ticker] = 0.0
+
+        holdings[ticker] += shares if transaction_type == "BUY" else -shares
+
+    # Filter out stocks where holdings are zero or negative
+    holdings = {k: v for k, v in holdings.items() if v > 0}
+
+    # Fetch live data for remaining stocks
+    live_data = {}
+    for ticker, shares in holdings.items():
+        try:
+            stock = yf.Ticker(ticker)
+            stock_info = stock.info
+
+            # Determine the correct fields based on the ticker
+            name_field = "longName" if ticker == "VUAG.L" else "shortName"
+            price_field = "previousClose" if ticker == "VUAG.L" else "currentPrice"
+
+            # Fetch the relevant data
+            name = stock_info.get(name_field)
+            current_price = stock_info.get(price_field) or stock_info.get("previousClose")
+            average_cost = stock_info.get("previousClose")
+            total_investment = average_cost * shares
+            current_value = shares * current_price if current_price is not None else None
+            value_held = round((shares * current_price if current_price is not None else None),2)
+
+            profit_loss_percentage = round((((current_value - total_investment) / total_investment * 100) if current_value is not None else None),2)
+
+
+            live_data[ticker] = {
+                "ticker": ticker,
+                "name": name,
+                "shares_held": round(shares,4),
+                "current_price": current_price,
+                "value_held": value_held,
+                "profit_loss_percentage": profit_loss_percentage
+            }
+        except Exception as e:
+            print(f"Error fetching data for {ticker}: {e}")
+            live_data[ticker] = {
+                "ticker": ticker,
+                "error": str(e)
+        }
+
+    sorting_data = sorted(live_data.items(), key=lambda x: x[1].get('value_held', 0), reverse=True)
+    live_data = {k: v for k, v in sorting_data}
+
+    return JsonResponse(live_data)

backend/myapp/graph_stock_holdings_day.py

@@ -0,0 +1,35 @@
+import json
+from django.http import JsonResponse
+from django.conf import settings
+from pathlib import Path
+import yfinance as yf
+import pytz
+from datetime import datetime, timedelta
+
+# Your timezone, for example, 'UTC'
+timezone = pytz.timezone('EST')
+
+def get_stock_history(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")
+
+    # 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]
+
+    # 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
+    } for date, row in historical_prices.iterrows()]
+
+    return JsonResponse(historical_values, safe=False)

backend/myapp/tester.py

@@ -1,4 +1,4 @@
 import yfinance as yf
 
-ticker = yf.Ticker("VUAG.L")
+ticker = yf.Ticker("AAPL")
 print(ticker.info)

backend/myapp/urls.py

@@ -1,12 +1,16 @@
 from django.urls import path
 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 .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('historic_holdings/', get_historic_stock_holdings, name='all_holdings'),
     path('graph_portfolio/<int:days>/', get_portfolio_value, name='graph_portfolio'),
 ]

frontend/src/StockHoldings.js

@@ -6,16 +6,30 @@ function StockHoldings({ onStockSelect, timeFrame }) {
 
   // Function to fetch data from your API
   const fetchStockHoldings = async () => {
-    try {
-      const response = await fetch('http://localhost:8000/api/stock_holdings/');
-      if (!response.ok) {
-        throw new Error(`HTTP error! status: ${response.status}`);
+    if (timeFrame === 'All') {
+      try {
+        const response = await fetch(`http://localhost:8000/api/stock_holdings/`);
+        if (!response.ok) {
+          throw new Error(`HTTP error! status: ${response.status}`);
+        }
+        const data = await response.json();
+        console.log(data);
+        setHoldings(Object.values(data));
+      } catch (error) {
+        console.error('Fetching data failed:', error);
+      }
+    } else {
+      try {
+        const response = await fetch('http://localhost:8000/api/stock_holdings_day/');
+        if (!response.ok) {
+          throw new Error(`HTTP error! status: ${response.status}`);
+        }
+        const data = await response.json();
+        console.log(data);
+        setHoldings(Object.values(data)); 
+      } catch (error) {
+        console.error('Fetching data failed:', error);
       }
-      const data = await response.json();
-      console.log(data); // Check the structure of the fetched data
-      setHoldings(Object.values(data)); // Convert the object to an array and update state
-    } catch (error) {
-      console.error('Fetching data failed:', error);
     }
   };
 
@@ -30,7 +44,7 @@ function StockHoldings({ onStockSelect, timeFrame }) {
     fetchStockHoldings();
     const interval = setInterval(fetchStockHoldings, 2000);
     return () => clearInterval(interval);
-  }, []);
+  }, [timeFrame]);
 
   // Function to load images
   const loadImage = async (ticker) => {
@@ -70,7 +84,7 @@ function StockHoldings({ onStockSelect, timeFrame }) {
     fetchStockHoldings();
     const interval = setInterval(fetchStockHoldings, 2000);
     return () => clearInterval(interval);
-  }, []);
+  }, [timeFrame]);
 
   return (
     <div className="stock-holdings">