Basic info from only yahoo

src/main.py

@@ -0,0 +1,72 @@
+import yfinance as yf
+import pandas as pd
+import matplotlib.pyplot as plt
+from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
+import tkinter as tk
+import sys
+
+window = tk.Tk()
+window.title("Stock Info")
+
+fig = plt.Figure(figsize=(8, 6))
+ax = fig.add_subplot(111)
+stock_symbol = input("Please provide the ticker symbol for the stock: ")  # Example stock symbol
+# Check if the stock symbol is valid
+try:
+    stock = yf.Ticker(stock_symbol)
+    info = stock.info
+    print(f"Stock symbol '{stock_symbol}' is valid.")
+
+    # Retrieve stock data from Yahoo Finance
+    stock_data = yf.download(stock_symbol, start="2023-01-01", end="2023-05-31")
+
+    window_size = float(input("Enter the window size for the SMA: "))
+
+    # Calculate the SMA for the specified window size
+    stock_data['SMA'] = stock_data['Close'].rolling(window=window_size).mean()
+
+    # Reset the index to make the date column accessible
+    stock_data.reset_index(inplace=True)
+
+    print(info.get('longName') or info.get('shortName'))
+except:
+    print(f"Ticker symbol '{stock_symbol}' is not valid.")
+    sys.exit(1)
+
+
+# Graph
+# Plot the closing price and SMA
+ax.plot(stock_data['Date'], stock_data['Close'], label='Closing Price')
+ax.plot(stock_data['Date'], stock_data['SMA'], label=f'SMA {window_size}')
+
+# Determine the trend based on the SMA relationship
+for i in range(window_size, len(stock_data)):
+    if stock_data['SMA'].iloc[i] > stock_data['SMA'].iloc[i - 1]:
+        ax.scatter(stock_data['Date'].iloc[i], stock_data['Close'].iloc[i], color='green', marker='^')
+    else:
+        ax.scatter(stock_data['Date'].iloc[i], stock_data['Close'].iloc[i], color='red', marker='v')
+
+ax.set_xlabel('Date')
+ax.set_ylabel('Price')
+ax.set_title(f'Stock Price with SMA {window_size} Trend')
+ax.legend()
+
+# Create a FigureCanvasTkAgg widget
+canvas = FigureCanvasTkAgg(fig, master=window)
+canvas.draw()
+
+# Place the canvas in the Tkinter window
+canvas.get_tk_widget().pack()
+
+
+# Info
+keywords = ['symbol', 'name', 'price', 'marketCap', 'dividendYield', 'trailingPE', 'forwardPE', 'previousClose', 'open', 'dayLow', 'dayHigh', 'regularMarketPreviousClose', 'regularMarketOpen', 'regularMarketDayLow', 'regularMarketDayHigh', 'dividendRate', 'beta', 'volume', 'regularMarketVolume', 'averageVolume', 'averageVolume10days', 'bid', 'ask', 'bidSize', 'askSize', 'fiftyTwoWeekLow', 'fiftyTwoWeekHigh', 'trailingAnnualDividendRate', 'trailingAnnualDividendYield', 'currency', 'enterpriseValue', 'profitMargins', 'floatShares', 'sharesOutstanding', 'sharesShort', 'sharesShortPriorMonth', 'heldPercentInsiders', 'heldPercentInstitutions', 'shortRatio', 'bookValue', 'priceToBook', 'earningsQuarterlyGrowth', 'netIncomeToCommon', 'trailingEps', 'forwardEps', 'pegRatio', 'enterpriseToRevenue', 'enterpriseToEbitda', '52WeekChange', 'SandP52WeekChange', 'exchange', 'currentPrice', 'targetHighPrice', 'targetLowPrice', 'targetMeanPrice', 'targetMedianPrice', 'recommendationMean', 'recommendationKey', 'numberOfAnalystOpinions', 'totalCash', 'totalCashPerShare', 'ebitda', 'totalDebt', 'quickRatio', 'currentRatio', 'totalRevenue', 'debtToEquity', 'revenuePerShare', 'returnOnAssets', 'returnOnEquity', 'grossProfits', 'freeCashflow', 'operatingCashflow', 'earningsGrowth', 'revenueGrowth', 'grossMargins', 'ebitdaMargins', 'operatingMargins', 'trailingPegRatio']
+
+# Create labels for filtered info
+for key, value in info.items():
+    if any(keyword in key.lower() for keyword in keywords):
+        label_text = f"{key}: {value}"
+        label = tk.Label(window, text=label_text)
+        label.pack()
+
+window.mainloop()

src/stock_data.json

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