Reporting

This example demonstrates how to create analysis reports using openseries and the built-in report functionality.

Using the Built-in HTML Report

import yfinance as yf
from openseries import OpenTimeSeries, OpenFrame, report_html
import pandas as pd

# Load sample data for comparison
tickers = ["AAPL", "MSFT", "GOOGL", "SPY"]
names = ["Apple", "Microsoft", "Google", "S&P 500"]

series_list = []
for ticker, name in zip(tickers, names):
     data = yf.Ticker(ticker).history(period="3y")
     series = OpenTimeSeries.from_df(dframe=data['Close'])
     series.set_new_label(lvl_zero=name)
     series_list.append(series)

# Create frame for report
comparison_frame = OpenFrame(constituents=series_list)

# Generate HTML report
# The last asset in the frame is used as the benchmark
figure, filepath = report_html(
     data=comparison_frame,
     output_type="file",
     filename="stock_comparison_report.html"
)

# filepath contains the path to the saved HTML file
print(f"Report saved to: {filepath}")

# The figure object can be used for further customization if needed
# figure.show()  # Display the figure interactively

Embedding Reports in Existing HTML Pages

When you need to embed a report in an existing HTML page, use output_type="div":

# Generate HTML div section for embedding
figure, html_div = report_html(
     data=comparison_frame,
     output_type="div"
)

# html_div contains the responsive HTML div section
# that can be embedded in your existing HTML page
# It includes both desktop and mobile layouts with CSS and JavaScript

# Example: Save to a custom HTML template
html_template = f"""
<!DOCTYPE html>
<html>
<head>
    <title>My Custom Report</title>
</head>
<body>
    <h1>Portfolio Analysis Report</h1>
    {html_div}
</body>
</html>
"""

with open("custom_report.html", "w", encoding="utf-8") as f:
    f.write(html_template)