FinData Explorer: A Step-by-Step Tutorial Using BeautifulSoup, yfinance, matplotlib, ipywidgets, and fpdf for Financial Data Extraction, Interactive Visualization, and Dynamic PDF Report Generation

!pip install fpdf beautifulsoup4 yfinance ipywidgets

import requests
from bs4 import BeautifulSoup
from fpdf import FPDF
import yfinance as yf
import matplotlib.pyplot as plt
import ipywidgets as widgets
from IPython.display import display, FileLink

def generate_report(b):
    symbol = symbol_text.value.upper().strip()
    start_date = start_date_picker.value
    end_date = end_date_picker.value
   
    output_area.clear_output()  # Clear previous outputs
   
    if not (symbol and start_date and end_date):
        with output_area:
            print("Please provide valid inputs for stock symbol and both dates.")
        return
   
    with output_area:
        print(f"Generating report for {symbol} from {start_date} to {end_date}...")
   
    # 1. Retrieve current price using yfinance
    try:
        stock = yf.Ticker(symbol)
        current_price = stock.info.get('regularMarketPrice', 'N/A')
    except Exception as e:
        current_price = "Error retrieving price"
        with output_area:
            print("Error retrieving current price:", e)
   
    # 2. Fetch historical data using yfinance
    try:
        hist = stock.history(start=start_date, end=end_date)
    except Exception as e:
        hist = None
        with output_area:
            print("Error fetching historical data:", e)
   
    # 3. Plot historical closing prices
    if hist is not None and not hist.empty:
        plt.figure(figsize=(10, 5))
        plt.plot(hist.index, hist['Close'], marker='o', linestyle='-', label="Close Price")
        plt.title(f"{symbol} Historical Closing Prices")
        plt.xlabel("Date")
        plt.ylabel("Close Price (USD)")
        plt.grid(True)
        plt.xticks(rotation=45)
        plt.tight_layout()
        graph_filename = "graph.png"
        plt.savefig(graph_filename)
        plt.show()
    else:
        graph_filename = None
        with output_area:
            print("No historical data available for the selected date range.")
   
    # 4. Create a PDF report using FPDF
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", "B", 16)
    pdf.cell(0, 10, f"Financial Report for {symbol}", ln=True, align="C")
    pdf.ln(10)
   
    pdf.set_font("Arial", size=12)
    pdf.cell(0, 10, f"Current Price: {current_price}", ln=True)
    pdf.cell(0, 10, f"Date Range: {start_date} to {end_date}", ln=True)
    pdf.ln(10)
   
    if graph_filename:
        pdf.cell(0, 10, "Historical Closing Prices:", ln=True)
        # Adjust the image width to fit the page layout
        pdf.image(graph_filename, w=180)
   
    pdf_filename = "financial_report.pdf"
    pdf.output(pdf_filename)
   
    # 5. Display the download link for the PDF report
    with output_area:
        print(f"PDF Report generated: {pdf_filename}")
        display(FileLink(pdf_filename))

# Create UI widgets
symbol_text = widgets.Text(
    value="AAPL",
    description="Stock Symbol:",
    placeholder="e.g., AAPL"
)
start_date_picker = widgets.DatePicker(
    description='Start Date'
)
end_date_picker = widgets.DatePicker(
    description='End Date'
)
generate_button = widgets.Button(
    description="Generate Report",
    button_style='success'
)
output_area = widgets.Output()


generate_button.on_click(generate_report)


display(widgets.VBox([symbol_text, start_date_picker, end_date_picker, generate_button, output_area]))