Update dividend.py
Browse files- dividend.py +17 -73
dividend.py
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# dividend.py
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import yfinance as yf
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import
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import pandas.api.types as ptypes
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import datetime
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# --- CSS for this module ---
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STYLE_BLOCK = """
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<style>
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.styled-table {
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border-collapse: collapse;
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margin: 10px 0;
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font-size: 0.9em;
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font-family: sans-serif;
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width: 100%;
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box-shadow: 0 0 10px rgba(0,0,0,0.1);
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}
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.styled-table th, .styled-table td {
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padding: 8px 10px;
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border: 1px solid #ddd;
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}
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.styled-table tbody tr:nth-child(even) {
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background-color: #f9f9f9;
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}
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.card {
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width: 95%;
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margin: 10px auto;
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padding: 15px;
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border: 1px solid #ddd;
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border-radius: 8px;
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background: #fafafa;
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box-shadow: 0 2px 5px rgba(0,0,0,0.1);
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}
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.card h2 {
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margin-top:0;
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}
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</style>
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"""
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def format_large_number(num):
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if not isinstance(num, (int, float)):
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return num
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sign = '-' if num < 0 else ''
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num = abs(float(num))
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if num >= 1_000_000_000_000:
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return f"{sign}{num / 1_000_000_000_000:.2f} LCr"
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elif num >= 10_000_000:
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return f"{sign}{num / 10_000_000:.2f} Cr"
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elif num >= 100_000:
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return f"{sign}{num / 100_000:.2f} Lac"
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else:
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return f"{sign}{num:,.0f}"
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def fetch_dividend(symbol):
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yfsymbol =
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try:
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ticker = yf.Ticker(yfsymbol)
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df = ticker.dividends.to_frame('Dividend')
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if df.empty:
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else:
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# Format numeric columns
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for col in df.columns:
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if ptypes.is_numeric_dtype(df[col]):
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df[col] = df[col].apply(format_large_number)
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content_html = f"<div class='card'><h2>Dividend History</h2>{df.to_html(classes='styled-table', border=0)}</div>"
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except Exception as e:
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content_html = f"<h1>Error</h1><p>{str(e)}</p>"
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# dividend.py
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import yfinance as yf
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from common import make_table, wrap_html, format_large_number, html_error
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def fetch_dividend(symbol):
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yfsymbol = symbol + ".NS"
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try:
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ticker = yf.Ticker(yfsymbol)
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df = ticker.dividends.to_frame('Dividend')
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if df.empty:
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return wrap_html(f"<h1>No dividend history available for {symbol}</h1>")
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df_formatted = df.copy()
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for col in df_formatted.columns:
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df_formatted[col] = df_formatted[col].apply(
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lambda x: format_large_number(x) if isinstance(x, (int, float)) else x
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)
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df_formatted.index = [str(i.date()) if hasattr(i, "date") else str(i) for i in df_formatted.index]
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table_html = make_table(df_formatted)
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return wrap_html(table_html, title=f"{symbol} - Dividend History")
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except Exception as e:
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return wrap_html(html_error(f"Failed to fetch dividend history: {e}"))
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