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Enhanced Email Format. Improved Unique Filling Retrieval

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Chris
2025-09-21 08:58:06 -04:00
parent afb2c79a4c
commit 1c577e31fb
1 changed files with 65 additions and 23 deletions
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88
HedgeAnalyzer.py
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@@ -6,6 +6,7 @@ from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart from email.mime.multipart import MIMEMultipart
from dotenv import load_dotenv from dotenv import load_dotenv
import os import os
import uuid
# Load environment variables # Load environment variables
load_dotenv() load_dotenv()
@@ -27,20 +28,32 @@ query_api = QueryApi(api_key=SEC_API_KEY)
# Point72 CIK # Point72 CIK
CIK = '0001603466' CIK = '0001603466'
# Query for latest two 13F-HR filings # Query for latest 13F-HR filings
query = { query = {
"query": f'cik:{CIK} formType:"13F-HR"', "query": f'cik:{CIK} formType:"13F-HR"',
"sort": [{"filedAt": {"order": "desc"}}], "sort": [{"filedAt": {"order": "desc"}}],
"size": 2 "size": 10 # Fetch more to ensure we get distinct periods
} }
response = query_api.get_filings(query) response = query_api.get_filings(query)
filings = response.get('filings', []) filings = response.get('filings', [])
if len(filings) < 2: # Filter unique periodOfReport and select the two most recent
raise Exception(f"Not enough filings found for comparison: {len(filings)} found") filings = sorted(filings, key=lambda x: x['periodOfReport'], reverse=True)
unique_filings = []
seen_periods = set()
for filing in filings:
period = filing['periodOfReport']
if period not in seen_periods:
unique_filings.append(filing)
seen_periods.add(period)
if len(unique_filings) == 2:
break
latest = filings[0] if len(unique_filings) < 2:
prev = filings[1] raise Exception(f"Not enough unique filings found: {len(unique_filings)} found")
latest = unique_filings[0]
prev = unique_filings[1]
# Fetch holdings # Fetch holdings
latest_holdings = latest.get('holdings', []) latest_holdings = latest.get('holdings', [])
@@ -69,6 +82,10 @@ for col in required_cols:
if col not in latest_df.columns or col not in prev_df.columns: if col not in latest_df.columns or col not in prev_df.columns:
raise KeyError(f"Column {col} missing in holdings data") raise KeyError(f"Column {col} missing in holdings data")
# Format value with commas and dollar sign
latest_df['value_formatted'] = latest_df['value'].apply(lambda x: f"${x:,.0f}")
prev_df['value_formatted'] = prev_df['value'].apply(lambda x: f"${x:,.0f}")
# Set index for comparison # Set index for comparison
key_col = 'cusip' key_col = 'cusip'
latest_df = latest_df.set_index(key_col) latest_df = latest_df.set_index(key_col)
@@ -83,28 +100,53 @@ removals = prev_df[~prev_df.index.isin(latest_df.index)]
# Changes >10% # Changes >10%
both = latest_df.index.intersection(prev_df.index) both = latest_df.index.intersection(prev_df.index)
changes = latest_df.loc[both].join(prev_df.loc[both], lsuffix='_new', rsuffix='_old') changes = latest_df.loc[both].join(prev_df.loc[both], lsuffix='_new', rsuffix='_old')
# Ensure share columns are numeric
changes['shrsOrPrnAmt_new'] = pd.to_numeric(changes['shrsOrPrnAmt_new'], errors='coerce') changes['shrsOrPrnAmt_new'] = pd.to_numeric(changes['shrsOrPrnAmt_new'], errors='coerce')
changes['shrsOrPrnAmt_old'] = pd.to_numeric(changes['shrsOrPrnAmt_old'], errors='coerce') changes['shrsOrPrnAmt_old'] = pd.to_numeric(changes['shrsOrPrnAmt_old'], errors='coerce')
# Calculate share change
changes['share_change'] = changes['shrsOrPrnAmt_new'] - changes['shrsOrPrnAmt_old'] changes['share_change'] = changes['shrsOrPrnAmt_new'] - changes['shrsOrPrnAmt_old']
changes = changes[changes['share_change'].notna()] # Remove rows with NaN changes changes = changes[changes['share_change'].notna()]
changes = changes[abs(changes['share_change']) / changes['shrsOrPrnAmt_old'].replace(0, 1) > 0.1] changes = changes[abs(changes['share_change']) / changes['shrsOrPrnAmt_old'].replace(0, 1) > 0.1]
changes['share_change'] = changes['share_change'].apply(lambda x: f"{x:,.0f}")
# Summary # HTML table styling
html_style = """
<style>
table {
border-collapse: collapse;
width: 100%;
font-family: Arial, sans-serif;
}
th, td {
border: 1px solid #ddd;
padding: 8px;
text-align: left;
}
th {
background-color: #f2f2f2;
font-weight: bold;
}
tr:nth-child(even) {background-color: #f9f9f9;}
tr:hover {background-color: #f5f5f5;}
</style>
"""
# Convert DataFrames to HTML tables
def df_to_html(df, columns, title):
if df.empty:
return f"<h3>{title} (0)</h3><p>None</p>"
df_subset = df[columns].reset_index(drop=True)
return f"<h3>{title} ({len(df)})</h3>{df_subset.to_html(index=False, border=0, classes='table')}"
# Summary as HTML
summary = f""" summary = f"""
Point72 13F Changes {prev['periodOfReport']} to {latest['periodOfReport']} <html>
<head>{html_style}</head>
Additions ({len(additions)}): <body>
{additions[['nameOfIssuer', 'shrsOrPrnAmt', 'value']].to_string() if not additions.empty else 'None'} <h2>Point72 13F Changes {prev['periodOfReport']} to {latest['periodOfReport']}</h2>
{df_to_html(additions, ['nameOfIssuer', 'shrsOrPrnAmt', 'value_formatted'], 'Additions')}
Removals ({len(removals)}): {df_to_html(removals, ['nameOfIssuer', 'shrsOrPrnAmt', 'value_formatted'], 'Removals')}
{removals[['nameOfIssuer', 'shrsOrPrnAmt', 'value']].to_string() if not removals.empty else 'None'} {df_to_html(changes, ['nameOfIssuer_new', 'share_change'], 'Changes')}
</body>
Changes ({len(changes)}): </html>
{changes[['nameOfIssuer_new', 'share_change']].to_string() if not changes.empty else 'None'}
""" """
# Email # Email
@@ -112,7 +154,7 @@ msg = MIMEMultipart()
msg['From'] = EMAIL_SENDER msg['From'] = EMAIL_SENDER
msg['To'] = EMAIL_RECIPIENT msg['To'] = EMAIL_RECIPIENT
msg['Subject'] = f'Point72 13F Update {latest["periodOfReport"]}' msg['Subject'] = f'Point72 13F Update {latest["periodOfReport"]}'
msg.attach(MIMEText(summary, 'plain')) msg.attach(MIMEText(summary, 'html'))
server = SMTP(SMTP_SERVER, SMTP_PORT) server = SMTP(SMTP_SERVER, SMTP_PORT)
server.starttls() server.starttls()