setting up API communication for stock graphing

backend/myapp/current_stock_holdings.py

@@ -0,0 +1,75 @@
+import json
+from django.http import JsonResponse
+from django.conf import settings
+from pathlib import Path
+import yfinance as yf
+
+def get_stock_holdings(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 = {}
+    latest_average_costs = {}
+    for transaction in transactions_data:
+        ticker = transaction["Ticker Symbol"]
+        shares = float(transaction["No. of Shares"])
+        transaction_type = transaction["Transaction Type"]
+        avg_cost = float(transaction["Average Cost per Share USD"])
+
+
+        if ticker not in holdings:
+            holdings[ticker] = 0.0
+
+        holdings[ticker] += shares if transaction_type == "BUY" else -shares
+        latest_average_costs[ticker] = avg_cost  # Update with the latest average cost
+
+
+    # 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 = latest_average_costs[ticker]
+            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.py

@@ -0,0 +1,63 @@
+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
+
+# 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)
+
+     # 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)
+
+    # Sort transactions by date
+    transactions.sort(key=lambda x: datetime.strptime(x["Date"], '%d-%m-%Y'))
+
+    # Get the first purchase date and last sale/current date
+    start_date = datetime.strptime(transactions[0]["Date"], '%d-%m-%Y')
+    end_date = datetime.now()
+
+    stock = yf.Ticker(ticker)
+    historical_prices = stock.history(start=start_date.strftime('%Y-%m-%d'), end=end_date.strftime('%Y-%m-%d'))
+
+    historical_values = []
+    current_shares = 0
+
+    # Before the loop, sort transactions by date
+    transactions.sort(key=lambda x: datetime.strptime(x["Date"], '%d-%m-%Y'))
+
+    for date, row in historical_prices.iterrows():
+        date = date.to_pydatetime().replace(tzinfo=None)  # Make date timezone naive
+        current_shares = 0  # Reset current shares for each date
+
+        # Accumulate shares up to the current date
+        for transaction in transactions:
+            transaction_date = datetime.strptime(transaction["Date"], '%d-%m-%Y')
+
+            if transaction_date <= date:
+                shares = float(transaction["No. of Shares"])
+                if transaction["Transaction Type"] == "BUY":
+                    current_shares += shares
+                elif transaction["Transaction Type"] == "SELL":
+                    current_shares -= shares
+
+        # Calculate value for the current date
+        value = current_shares * row['Close']
+        historical_values.append({"date": date.strftime('%Y-%m-%d'), "value": value})
+
+    return JsonResponse(historical_values, safe=False)

backend/myapp/urls.py

@@ -1,6 +1,8 @@
 from django.urls import path
-from .views import get_stock_holdings
+from .current_stock_holdings import get_stock_holdings
+from .graph_stock_holdings import get_stock_history
 
 urlpatterns = [
     path('stock_holdings/', get_stock_holdings, name='stock_holdings'),
-]
+    path('graph_stock/<str:ticker>/', get_stock_history, name='graph_stock'),
+]

backend/myapp/views.py

@@ -2,83 +2,10 @@
 from django.http import JsonResponse
 from django.conf import settings
 from pathlib import Path
-from rest_framework import viewsets
 import yfinance as yf
+import pytz
+from datetime import datetime
 
+# Your timezone, for example, 'UTC'
+timezone = pytz.timezone('EST')
 
-def load_transactions(request):
-    json_file_path = Path(settings.BASE_DIR) / 'data' / 'investments_data.json'
-    with open(json_file_path, 'r') as file:
-        data = json.load(file)
-    return JsonResponse(data, safe=False)
-
-def get_stock_holdings(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 = {}
-    latest_average_costs = {}
-    for transaction in transactions_data:
-        ticker = transaction["Ticker Symbol"]
-        shares = float(transaction["No. of Shares"])
-        transaction_type = transaction["Transaction Type"]
-        avg_cost = float(transaction["Average Cost per Share USD"])
-
-
-        if ticker not in holdings:
-            holdings[ticker] = 0.0
-
-        holdings[ticker] += shares if transaction_type == "BUY" else -shares
-        latest_average_costs[ticker] = avg_cost  # Update with the latest average cost
-
-
-    # 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 = latest_average_costs[ticker]
-            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)