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import asyncio
from collections import Counter
from datetime import datetime, timedelta
from typing import List, Optional, Dict
import aiohttp
import pandas as pd
from src.api.insiders.insider_trade import InsiderTrade
from src.api.insiders.trading_report import TradingReport
from src.api.insiders.transaction_types import TransactionType
from src.telegram_bot.config import Config
from src.telegram_bot.logger import main_logger as logger
class InsiderTradingAggregator:
"""Async aggregator for insider trading data from multiple APIs"""
def __init__(self, session_timeout: int = 30):
# API configurations
self.apis = {
'fmp': {
'base_url': 'https://financialmodelingprep.com/stable',
'api_key': Config.FMP_API_KEY,
'rate_limit': 250, # Daily limit
'requests_per_minute': 10
},
'sec_api': {
'base_url': 'https://api.sec-api.io',
'api_key': Config.SEC_API_KEY,
'rate_limit': 100,
'requests_per_minute': 5
},
'eod': {
'base_url': 'https://eodhistoricaldata.com/api',
'api_key': None,
'rate_limit': 1000,
'requests_per_minute': 20
},
'tradefeeds': {
'base_url': 'https://api.tradefeeds.com',
'api_key': None,
'rate_limit': 500,
'requests_per_minute': 15
}
}
# Rate limiting tracking
self.request_counts = {api: 0 for api in self.apis.keys()}
self.last_reset = datetime.now()
self.session_timeout = session_timeout
# Semaphores for rate limiting per minute
self.semaphores = {
api: asyncio.Semaphore(config['requests_per_minute'])
for api, config in self.apis.items()
}
def set_api_key(self, api_name: str, api_key: str) -> None:
"""Set API key for a specific service"""
if api_name in self.apis:
self.apis[api_name]['api_key'] = api_key
logger.info(f"API key set for {api_name}")
else:
logger.error(f"Unknown API: {api_name}")
def _check_rate_limit(self, api_name: str) -> bool:
"""Check if we're within daily rate limits"""
if datetime.now() - self.last_reset > timedelta(days=1):
self.request_counts = {api: 0 for api in self.apis.keys()}
self.last_reset = datetime.now()
return self.request_counts[api_name] < self.apis[api_name]['rate_limit']
async def _make_request(self, session: aiohttp.ClientSession, api_name: str,
endpoint: str, params: Dict = None) -> Optional[Dict]:
"""Make async rate-limited request to an API"""
if not self._check_rate_limit(api_name):
logger.warning(f"Daily rate limit reached for {api_name}")
return None
if not self.apis[api_name]['api_key']:
logger.warning(f"No API key set for {api_name}, skipping request.")
return None
# Rate limiting with semaphore
async with self.semaphores[api_name]:
try:
url = f"{self.apis[api_name]['base_url']}/{endpoint}"
if params is None:
params = {}
# Add API key to parameters
if api_name == 'fmp':
params['apikey'] = self.apis[api_name]['api_key']
elif api_name in ['sec_api', 'eod', 'tradefeeds']:
params['token'] = self.apis[api_name]['api_key']
async with session.get(url, params=params) as response:
response.raise_for_status()
self.request_counts[api_name] += 1
return await response.json()
except aiohttp.ClientError as e:
logger.error(f"Request failed for {api_name} ({url}): {e}")
return None
# BUG FIX: Removed the unnecessary sleep. The semaphore already handles rate limiting.
# This was a major performance bottleneck.
# await asyncio.sleep(60 / self.apis[api_name]['requests_per_minute'])
'''
async def _make_post_request(self, session: aiohttp.ClientSession, api_name: str,
endpoint: str, payload: Dict) -> Optional[Dict]:
"""Make an async rate-limited POST request to an API."""
if not self._check_rate_limit(api_name):
logger.warning(f"Daily rate limit reached for {api_name}")
return None
if not self.apis[api_name]['api_key']:
logger.warning(f"No API key set for {api_name}, skipping request.")
return None
async with self.semaphores[api_name]:
try:
url = f"{self.apis[api_name]['base_url']}/{endpoint}"
# Set Authorization header per SEC API docs (no "Bearer" prefix)
headers = {
'Authorization': self.apis[api_name]['api_key'],
'Content-Type': 'application/json'
}
async with session.post(url, json=payload, headers=headers) as response:
response.raise_for_status()
self.request_counts[api_name] += 1
return await response.json()
except aiohttp.ClientError as e:
logger.error(f"POST request failed for {api_name} ({url}): {e}")
return None
'''
async def _make_post_request(self, session: aiohttp.ClientSession, api_name: str,
endpoint: str, payload: Dict) -> Optional[Dict]:
"""Make an async rate-limited POST request to an API."""
if not self._check_rate_limit(api_name):
logger.warning(f"Daily rate limit reached for {api_name}")
return None
if not self.apis[api_name]['api_key']:
logger.warning(f"No API key set for {api_name}, skipping request.")
return None
async with self.semaphores[api_name]:
try:
# Build the full URL
url = f"{self.apis[api_name]['base_url']}/{endpoint}"
# Add API key as query parameter (SEC API supports this method)
url_with_token = f"{url}?token={self.apis[api_name]['api_key']}"
# Make POST request with JSON payload
async with session.post(url_with_token, json=payload) as response:
response.raise_for_status()
self.request_counts[api_name] += 1
return await response.json()
except aiohttp.ClientError as e:
logger.error(f"POST request failed for {api_name} ({url}): {e}")
return None
async def get_fmp_insider_trades(self, session: aiohttp.ClientSession,
symbol: str, limit: int = 100, filter_days: int = 30) -> List[InsiderTrade]:
"""
Get insider trades from Financial Modeling Prep API
Get insider trades from FMP by iterating day-by-day for a specific period.
NOTE: This method is inefficient and makes many API calls.
"""
if filter_days > 14:
logger.warning(f"FMP date range capped at 14 days. Reducing from {filter_days} to 14.")
filter_days = 14
all_trades = []
today = datetime.now()
date_range = [today - timedelta(days=i) for i in range(filter_days)]
# Outer Loop: Iterate through each day in the specified range.
for single_date in date_range:
page = 0
date_str = single_date.strftime('%Y-%m-%d')
# Inner Loop: Handle pagination for the current day.
while True:
endpoint = "insider-trading/latest"
params = {
'symbol': symbol,
'date': date_str,
'page': page,
'limit': limit
}
logger.info(f"Requesting FMP data for {symbol} on {date_str}, page {page}...")
data = await self._make_request(session, 'fmp', endpoint, params)
# If no data is returned for this page, we're done with this date.
if not data:
break
for trade in data:
try:
disposition = (trade.get('acquistionOrDisposition') or '').upper()
trans_type = TransactionType.BUY.value if disposition == 'A' else TransactionType.SELL.value
shares = int(trade.get('securitiesTransacted', 0) or 0)
price = float(trade.get('price', 0) or 0)
insider_trade = InsiderTrade(
symbol=trade.get('symbol', ''),
company_name=trade.get('companyName', ''),
insider_name=trade.get('reportingName', ''),
position=trade.get('typeOfOwner', ''),
transaction_date=trade.get('transactionDate', ''),
transaction_type=trans_type,
shares=shares,
price=price,
value=float(shares * price),
form_type=trade.get('formType', ''),
source='FMP',
filing_date=trade.get('filingDate', ''),
ownership_type=trade.get('directOrIndirectOwnership', '')
)
all_trades.append(insider_trade)
except (ValueError, TypeError) as e:
logger.warning(f"Error parsing FMP trade data for {symbol}: {e} -> {trade}")
continue
# Increment the page to fetch the next set of results for the same day.
page += 1
await asyncio.sleep(0.2) # Courteous delay
logger.info(
f"Retrieved {len(all_trades)} trades from FMP for {symbol} by iterating through {len(date_range)} days.")
return all_trades
'''
async def get_sec_api_insider_trades(self, session: aiohttp.ClientSession,
symbol: str, limit: int = 100) -> List[InsiderTrade]:
"""Get insider trades from SEC-API"""
trades = []
endpoint = "insider-transactions"
params = {'ticker': symbol, 'limit': limit}
data = await self._make_request(session, 'sec_api', endpoint, params)
if not data or 'transactions' not in data:
return trades
for trade in data['transactions']:
try:
insider_trade = InsiderTrade(
symbol=trade.get('ticker', ''),
company_name=trade.get('companyName', ''),
insider_name=trade.get('personName', ''),
position=trade.get('position', ''),
transaction_date=trade.get('transactionDate', ''),
transaction_type=trade.get('transactionType', ''),
shares=int(trade.get('sharesTraded', 0) or 0),
price=float(trade.get('pricePerShare', 0) or 0),
value=float(trade.get('transactionValue', 0) or 0),
form_type=trade.get('formType', ''),
source='SEC-API',
filing_date=trade.get('filingDate', '')
)
trades.append(insider_trade)
except (ValueError, TypeError) as e:
logger.warning(f"Error parsing SEC-API trade data for {symbol}: {e} -> {trade}")
continue
logger.info(f"Retrieved {len(trades)} trades from SEC-API for {symbol}")
return trades
async def get_sec_api_insider_trades(self, session: aiohttp.ClientSession,
symbol: str, limit: int = 50,
filter_days: int = 30) -> List[InsiderTrade]:
"""Get insider trades from SEC-API using a POST request with proper query structure."""
all_trades = []
# Ensure the limit does not exceed the API's maximum
if limit > 50:
limit = 50
# Date range for filtering
to_date = datetime.now()
from_date = to_date - timedelta(days=filter_days)
start_index = 0
while True:
# Construct query payload according to SEC API documentation
query_payload = {
"query": {
"query_string": {
"query": f'issuer.tradingSymbol:"{symbol}" AND periodOfReport:[{from_date.strftime("%Y-%m-%d")} TO {to_date.strftime("%Y-%m-%d")}]'
}
},
"from": str(start_index),
"size": str(limit),
"sort": [{"filedAt": {"order": "desc"}}]
}
endpoint = "insider-trading"
logger.info(f"Requesting SEC-API data for {symbol}, starting at index {start_index}...")
data = await self._make_post_request(session, 'sec_api', endpoint, query_payload)
if not data or 'transactions' not in data or not data['transactions']:
break
for filing in data['transactions']:
# Parse both non-derivative and derivative transactions
transactions_list = filing.get('nonDerivativeTable', {}).get('transactions', []) + \
filing.get('derivativeTable', {}).get('transactions', [])
for transaction in transactions_list:
try:
# Map transaction codes to buy/sell
trans_code = transaction.get('coding', {}).get('code', '')
if trans_code in ('A', 'P'): # Acquisition or Purchase
trans_type = TransactionType.BUY.value
elif trans_code in ('D', 'S'): # Disposition or Sale
trans_type = TransactionType.SELL.value
else:
continue # Skip other transaction types
shares = transaction.get('amounts', {}).get('shares')
price_per_share = transaction.get('amounts', {}).get('pricePerShare')
if shares is None or price_per_share is None:
continue
shares = int(shares)
price_per_share = float(price_per_share)
insider_trade = InsiderTrade(
symbol=filing.get('issuer', {}).get('tradingSymbol', symbol),
company_name=filing.get('issuer', {}).get('name', ''),
insider_name=filing.get('reportingOwner', {}).get('name', ''),
position=filing.get('reportingOwner', {}).get('relationship', {}).get('officerTitle',
'Insider'),
transaction_date=transaction.get('transactionDate', {}).get('value', ''),
transaction_type=trans_type,
shares=shares,
price=price_per_share,
value=float(shares * price_per_share),
form_type=filing.get('documentType', ''),
source='SEC-API',
filing_date=filing.get('filedAt', '')
)
all_trades.append(insider_trade)
except (ValueError, TypeError, AttributeError) as e:
logger.warning(f"Error parsing SEC-API transaction for {symbol}: {e}")
continue
start_index += limit
# Stop if we got fewer results than requested (last page)
if len(data['transactions']) < limit:
break
logger.info(f"Retrieved {len(all_trades)} trades from SEC-API for {symbol}.")
return all_trades
'''
async def get_sec_api_insider_trades(self, session: aiohttp.ClientSession,
symbol: str, limit: int = 50,
filter_days: int = 30) -> List[InsiderTrade]:
"""Get insider trades from SEC-API using a POST request with proper query structure."""
all_trades = []
if limit > 50:
limit = 50
to_date = datetime.now()
from_date = to_date - timedelta(days=filter_days)
start_index = 0
while True:
# Use simple query string format as shown in official Python SDK
query_payload = {
"query": f'issuer.tradingSymbol:"{symbol}" AND periodOfReport:[{from_date.strftime("%Y-%m-%d")} TO {to_date.strftime("%Y-%m-%d")}]',
"from": str(start_index),
"size": str(limit),
"sort": [{"filedAt": {"order": "desc"}}]
}
endpoint = "insider-trading"
logger.info(f"Requesting SEC-API data for {symbol}, starting at index {start_index}...")
data = await self._make_post_request(session, 'sec_api', endpoint, query_payload)
if not data or 'transactions' not in data or not data['transactions']:
break
for filing in data['transactions']:
# Check if nonDerivativeTable exists and has transactions
non_deriv_trans = filing.get('nonDerivativeTable', {}).get('transactions', [])
deriv_trans = filing.get('derivativeTable', {}).get('transactions', [])
transactions_list = non_deriv_trans + deriv_trans
for transaction in transactions_list:
try:
trans_code = transaction.get('coding', {}).get('code', '')
if trans_code in ('A', 'P'):
trans_type = TransactionType.BUY.value
elif trans_code in ('D', 'S'):
trans_type = TransactionType.SELL.value
else:
continue
shares = transaction.get('amounts', {}).get('shares')
price_per_share = transaction.get('amounts', {}).get('pricePerShare')
if shares is None or price_per_share is None:
continue
shares = float(shares)
price_per_share = float(price_per_share)
insider_trade = InsiderTrade(
symbol=filing.get('issuer', {}).get('tradingSymbol', symbol),
company_name=filing.get('issuer', {}).get('name', ''),
insider_name=filing.get('reportingOwner', {}).get('name', ''),
position=filing.get('reportingOwner', {}).get('relationship', {}).get('officerTitle',
'Insider'),
transaction_date=transaction.get('transactionDate', ''),
transaction_type=trans_type,
shares=int(shares),
price=price_per_share,
value=shares * price_per_share,
form_type=filing.get('documentType', ''),
source='SEC-API',
filing_date=filing.get('filedAt', '')
)
all_trades.append(insider_trade)
except (ValueError, TypeError, AttributeError) as e:
logger.warning(f"Error parsing SEC-API transaction for {symbol}: {e}")
continue
start_index += limit
if len(data['transactions']) < limit:
break
logger.info(f"Retrieved {len(all_trades)} trades from SEC-API for {symbol}.")
return all_trades
async def get_eod_insider_trades(self, session: aiohttp.ClientSession,
symbol: str) -> List[InsiderTrade]:
"""Get insider trades from EOD Historical Data"""
trades = []
# NOTE: This endpoint hardcodes the US exchange.
endpoint = f"insider-transactions/{symbol}.US"
data = await self._make_request(session, 'eod', endpoint)
if not data:
return trades
# EOD data can be a dictionary of lists, so we iterate through its values.
data_to_iterate = data.values() if isinstance(data, dict) else data
for trade in data_to_iterate:
try:
insider_trade = InsiderTrade(
symbol=symbol,
company_name='', # EOD does not provide company name in this endpoint
insider_name=trade.get('ownerName', ''),
position=trade.get('ownerPosition', ''),
transaction_date=trade.get('date', ''),
transaction_type=trade.get('transactionType', ''),
shares=int(trade.get('transactionAmount', 0) or 0),
price=float(trade.get('transactionPrice', 0) or 0),
value=float(trade.get('transactionAmount', 0) or 0) * float(trade.get('transactionPrice', 0) or 0),
form_type='Form 4',
source='EOD'
)
trades.append(insider_trade)
except (ValueError, TypeError) as e:
logger.warning(f"Error parsing EOD trade data for {symbol}: {e} -> {trade}")
continue
logger.info(f"Retrieved {len(trades)} trades from EOD for {symbol}")
return trades
async def get_tradefeeds_insider_trades(self, session: aiohttp.ClientSession,
symbol: str, limit: int = 100) -> List[InsiderTrade]:
"""Get insider trades from Tradefeeds API"""
trades = []
endpoint = "insider_transactions"
params = {'symbol': symbol, 'limit': limit}
data = await self._make_request(session, 'tradefeeds', endpoint, params)
if not data or 'data' not in data:
return trades
for trade in data['data']:
try:
shares = int(trade.get('sharesTraded', 0) or 0)
price = float(trade.get('averagePrice', 0) or 0)
insider_trade = InsiderTrade(
symbol=trade.get('symbol', ''),
company_name=trade.get('companyName', ''),
insider_name=trade.get('insiderName', ''),
position=trade.get('relationship', ''),
transaction_date=trade.get('transactionDate', ''),
transaction_type=trade.get('transactionCode', ''),
shares=shares,
price=price,
value=shares * price,
form_type='Form 4',
source='Tradefeeds'
)
trades.append(insider_trade)
except (ValueError, TypeError) as e:
logger.warning(f"Error parsing Tradefeeds trade data for {symbol}: {e} -> {trade}")
continue
logger.info(f"Retrieved {len(trades)} trades from Tradefeeds for {symbol}")
return trades
async def get_factored_ai_insider_trades(self, session: aiohttp.ClientSession,
symbol: str) -> List[InsiderTrade]:
"""Get insider trades from Factored.AI (S&P 500 companies only)"""
trades = []
try:
url = f"https://raw.githubusercontent.com/Factored-AI/insider-trading/main/data/{symbol}_insider_trades.json"
async with session.get(url) as response:
if response.status == 200:
data = await response.json()
for trade in data:
try:
shares = int(trade.get('shares', 0) or 0)
price = float(trade.get('price', 0) or 0)
insider_trade = InsiderTrade(
symbol=symbol,
company_name=trade.get('company_name', ''),
insider_name=trade.get('insider_name', ''),
position=trade.get('position', ''),
transaction_date=trade.get('transaction_date', ''),
transaction_type=trade.get('transaction_type', ''),
shares=shares,
price=price,
value=shares * price,
form_type='Form 4',
source='Factored.AI'
)
trades.append(insider_trade)
except (ValueError, TypeError) as e:
logger.warning(f"Error parsing Factored.AI trade data for {symbol}: {e} -> {trade}")
continue
logger.info(f"Retrieved {len(trades)} trades from Factored.AI for {symbol}")
else:
logger.info(f"No Factored.AI data found for {symbol} (status: {response.status})")
except aiohttp.ClientError as e:
logger.error(f"Failed to retrieve data from Factored.AI for {symbol}: {e}")
return trades
def deduplicate_trades(self, trades: List[InsiderTrade]) -> List[InsiderTrade]:
"""Advanced deduplication based on multiple factors"""
if not trades:
return []
# First pass: remove exact hash duplicates
unique_trades_map = {trade.hash: trade for trade in trades}
unique_trades = list(unique_trades_map.values())
# Second pass: group similar trades (same person, date, similar values)
# BUG FIX: The original nested loop was inefficient and could miss duplicates.
# This approach of sorting and grouping is more robust.
unique_trades.sort(key=lambda t: (t.insider_name.lower(), t.transaction_date, t.value))
if not unique_trades:
return []
final_trades = [unique_trades[0]]
for i in range(1, len(unique_trades)):
prev_trade = final_trades[-1]
curr_trade = unique_trades[i]
# Check for similarity
if (prev_trade.insider_name.lower() == curr_trade.insider_name.lower() and
prev_trade.transaction_date == curr_trade.transaction_date and
abs(prev_trade.value - curr_trade.value) < 1000): # Within $1000 tolerance
# Keep the trade with more complete information or from a preferred source
if len(curr_trade.company_name) > len(prev_trade.company_name):
final_trades[-1] = curr_trade # Replace previous with current
else:
final_trades.append(curr_trade)
logger.info(f"Deduplication: {len(trades)} -> {len(final_trades)} trades")
return final_trades
def filter_trades_by_period(self, trades: List[InsiderTrade],
days: int = 7, end_date: Optional[datetime] = None) -> List[InsiderTrade]:
"""Filter trades by time period (default: last 7 days)"""
if end_date is None:
end_date = datetime.now()
start_date = end_date - timedelta(days=days)
filtered_trades = []
for trade in trades:
trade_date = trade.transaction_date_dt
if trade_date and start_date <= trade_date <= end_date:
filtered_trades.append(trade)
logger.info(f"Filtered {len(filtered_trades)} trades from last {days} days")
return filtered_trades
async def get_all_insider_trades(self, symbol: str, limit_per_api: int = 100,
filter_days: int = 7) -> List[InsiderTrade]:
"""Aggregate insider trades from all available APIs with async processing"""
timeout = aiohttp.ClientTimeout(total=self.session_timeout)
async with aiohttp.ClientSession(timeout=timeout) as session:
# Create tasks for all API calls
tasks = [
#self.get_fmp_insider_trades(session, symbol, limit_per_api),
self.get_sec_api_insider_trades(session, symbol, limit_per_api),
#self.get_eod_insider_trades(session, symbol),
#self.get_tradefeeds_insider_trades(session, symbol, limit_per_api),
#self.get_factored_ai_insider_trades(session, symbol)
]
# Execute all tasks concurrently
results = await asyncio.gather(*tasks, return_exceptions=True)
# Combine results, filtering out exceptions
all_trades = []
api_names = ['FMP', 'SEC-API', 'EOD', 'Tradefeeds', 'Factored.AI']
for i, result in enumerate(results):
if isinstance(result, Exception):
logger.error(f"Error fetching from {api_names[i]} for {symbol}: {result}")
elif result:
all_trades.extend(result)
# Deduplicate trades
unique_trades = self.deduplicate_trades(all_trades)
# Filter by period
if filter_days > 0:
unique_trades = self.filter_trades_by_period(unique_trades, filter_days)
logger.info(f"Total unique trades found for {symbol}: {len(unique_trades)}")
return unique_trades
def generate_trading_report(self, trades: List[InsiderTrade],
period_days: int = 7) -> Optional[TradingReport]:
"""Generate comprehensive trading report"""
if not trades:
return None
# Basic statistics
symbol = trades[0].symbol
# BUG FIX: Get the most common company name to avoid issues with inconsistent API data
company_name_counter = Counter(t.company_name for t in trades if t.company_name)
company_name = company_name_counter.most_common(1)[0][0] if company_name_counter else "N/A"
total_trades = len(trades)
# Separate buy/sell trades
buy_trades = [t for t in trades if 'buy' in t.transaction_type.lower() or t.transaction_type.lower() == 'a']
sell_trades = [t for t in trades if 'sell' in t.transaction_type.lower() or t.transaction_type.lower() == 'd']
total_value_bought = sum(abs(t.value) for t in buy_trades)
total_value_sold = sum(abs(t.value) for t in sell_trades)
net_value = total_value_bought - total_value_sold
# Top insiders by activity
insider_stats = {}
for trade in trades:
name = trade.insider_name
if name not in insider_stats:
insider_stats[name] = {'count': 0, 'value': 0}
insider_stats[name]['count'] += 1
insider_stats[name]['value'] += abs(trade.value)
top_insiders = sorted(
[(name, stats['count'], stats['value']) for name, stats in insider_stats.items()],
key=lambda x: x[2], reverse=True
)[:5]
# Period calculation
trade_dates = [t.transaction_date_dt for t in trades if t.transaction_date_dt]
period_start = min(trade_dates) if trade_dates else datetime.now() - timedelta(days=period_days)
period_end = max(trade_dates) if trade_dates else datetime.now()
return TradingReport(
symbol=symbol,
company_name=company_name,
total_trades=total_trades,
buy_trades=len(buy_trades),
sell_trades=len(sell_trades),
total_value_bought=total_value_bought,
total_value_sold=total_value_sold,
net_value=net_value,
top_insiders=top_insiders,
period_start=period_start,
period_end=period_end,
trades=trades
)
'''
def format_telegram_message(self, report: TradingReport) -> str:
"""Generate formatted Telegram message from trading report"""
if not report:
return "❌ No insider trading data found for the specified period."
trend_emoji = "📈" if report.net_value > 0 else "📉" if report.net_value < 0 else "➡️"
message = f"🔍 **INSIDER TRADING REPORT** 🔍\n\n"
message += f"🏢 **Company:** {report.company_name} (${report.symbol})\n"
message += f"📅 **Period:** {report.period_start.strftime('%Y-%m-%d')} to {report.period_end.strftime('%Y-%m-%d')}\n\n"
message += "📊 **SUMMARY**\n"
message += f"• Total Trades: {report.total_trades}\n"
message += f"• Buy Trades: {report.buy_trades} 🟢\n"
message += f"• Sell Trades: {report.sell_trades} 🔴\n\n"
message += "💰 **FINANCIAL IMPACT**\n"
message += f"• Total Bought: ${report.total_value_bought:,.2f}\n"
message += f"• Total Sold: ${report.total_value_sold:,.2f}\n"
message += f"• Net Position: {trend_emoji} ${report.net_value:,.2f}\n\n"
message += "👥 **TOP INSIDERS BY ACTIVITY**\n"
message += "```\n"
message += "┌──────────────────────────┬────────┬──────────────┐\n"
message += "│ Name │ Trades │ Total Value │\n"
message += "├──────────────────────────┼────────┼──────────────┤\n"
for name, count, value in report.top_insiders:
display_name = (name[:23] + '..') if len(name) > 25 else name
message += f"│ {display_name:<24} │ {count:<6} │ ${value: >10,.0f} │\n"
message += "└──────────────────────────┴────────┴──────────────┘\n```\n"
if report.trades:
message += "\n📋 **RECENT SIGNIFICANT TRADES**\n"
top_trades = sorted(report.trades, key=lambda x: abs(x.value), reverse=True)[:5]
message += "```\n"
message += "┌───────────────────┬──────┬──────────┬──────────┬─────────────┐\n"
message += "│ Insider Name │ Type │ Date │ Shares │ Total Value │\n"
message += "├───────────────────┼──────┼──────────┼──────────┼─────────────┤\n"
for trade in top_trades:
insider_name = (trade.insider_name[:16] + '..') if len(trade.insider_name) > 18 else trade.insider_name
trans_type = "BUY" if "buy" in trade.transaction_type.lower() or "a" == trade.transaction_type.lower() else "SELL"
type_display = f"{'🟢' if trans_type == 'BUY' else '🔴'}{trans_type}"
date_str = trade.transaction_date_dt.strftime(
'%Y-%m-%d') if trade.transaction_date_dt else trade.transaction_date[:10]
message += f"│ {insider_name:<17} │ {type_display:<4} │ {date_str:<8} │ {trade.shares:>8,d} │ ${abs(trade.value):>10,.0f} │\n"
message += "└───────────────────┴──────┴──────────┴──────────┴─────────────┘\n```\n"
sources = sorted(list(set(t.source for t in report.trades)))
message += f"\n🔗 **Sources:** {', '.join(sources)}\n"
message += f"⏰ Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
return message
'''
def format_telegram_message(self, report: TradingReport) -> str:
"""Generate formatted Telegram message from trading report"""
if not report:
return "❌ No insider trading data found for the specified period."
trend_emoji = "📈" if report.net_value > 0 else "📉" if report.net_value < 0 else "➡️"
message = f"🔍 *INSIDER TRADING REPORT* 🔍\n\n"
message += f"🏢 *Company:* {report.company_name} (${report.symbol})\n"
message += f"📅 *Period:* {report.period_start.strftime('%Y-%m-%d')} to {report.period_end.strftime('%Y-%m-%d')}\n\n"
message += "📊 *SUMMARY*\n"
message += f"• Total Trades: {report.total_trades}\n"
message += f"• Buy Trades: {report.buy_trades} 🟢\n"
message += f"• Sell Trades: {report.sell_trades} 🔴\n\n"
message += "💰 *FINANCIAL IMPACT*\n"
message += f"• Total Bought: ${report.total_value_bought:,.2f}\n"
message += f"• Total Sold: ${report.total_value_sold:,.2f}\n"
message += f"• Net Position: {trend_emoji} ${report.net_value:,.2f}\n\n"
message += "👥 *TOP INSIDERS BY ACTIVITY*\n"
for i, (name, count, value) in enumerate(report.top_insiders, 1):
display_name = (name[:35] + '...') if len(name) > 38 else name
message += f"`{i}.` {display_name}\n"
message += f" └ Trades: {count} | Value: ${value:,.0f}\n"
if report.trades:
message += "\n📋 *RECENT SIGNIFICANT TRADES*\n"
top_trades = sorted(report.trades, key=lambda x: abs(x.value), reverse=True)[:5]
for trade in top_trades:
insider_name = (trade.insider_name[:30] + '...') if len(trade.insider_name) > 33 else trade.insider_name
trans_type = "BUY" if "buy" in trade.transaction_type.lower() or "a" == trade.transaction_type.lower() else "SELL"
emoji = '🟢' if trans_type == 'BUY' else '🔴'
date_str = trade.transaction_date_dt.strftime(
'%Y-%m-%d') if trade.transaction_date_dt else trade.transaction_date[:10]
message += f"\n{emoji} *{trans_type}* | {insider_name}\n"
message += f"`Date: {date_str}`\n"
message += f"`Shares: {trade.shares:,d}`\n"
message += f"`Value: ${abs(trade.value):,.0f}`\n"
sources = sorted(list(set(t.source for t in report.trades)))
message += f"\n🔗 *Sources:* {', '.join(sources)}\n"
message += f"⏰ Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
return message
# BUG FIX: This method was combined with the one below it, causing a SyntaxError.
# It has been properly separated now.
def format_telegram_message_ultra_compact(self, report: TradingReport) -> str:
"""Ultra compact format for high-frequency monitoring"""
if not report or not report.trades:
return f"▫️ ${report.symbol}: No activity"
trend = "📈" if report.net_value > 0 else "📉" if report.net_value < 0 else "➡️"
# Get biggest trade
biggest_trade = max(report.trades, key=lambda x: abs(x.value))
message = f"🚨 **${report.symbol}** | {trend} Net: ${report.net_value:,.0f} | {report.total_trades} trades"
trans_type = "BUY" if "buy" in biggest_trade.transaction_type.lower() else "SELL"
# Get last name for brevity
insider_short = biggest_trade.insider_name.split()[-1]
message += f"\n Lgst: {trans_type} ${abs(biggest_trade.value):,.0f} by {insider_short}"
return message
# BUG FIX: This method was missing its definition and was tangled with the above method.
def format_telegram_message_short(self, report: TradingReport) -> str:
"""Generate short Telegram message for quick updates"""
if not report:
return f"❌ No insider trading activity found."
trend_emoji = "📈" if report.net_value > 0 else "📉" if report.net_value < 0 else "➡️"
message = f"🚨 **${report.symbol} Insider Alert** 🚨\n\n"
message += f"{trend_emoji} Net Value: **${report.net_value:,.0f}**\n"
message += f"📊 Total Trades: {report.total_trades} ({report.buy_trades}B / {report.sell_trades}S)\n\n"
if report.top_insiders:
top_insider_name = report.top_insiders[0][0]
top_insider_value = report.top_insiders[0][2]
# Truncate long names
display_name = (top_insider_name[:25] + '...') if len(top_insider_name) > 28 else top_insider_name
message += f"👤 Top Insider: {display_name}\n"
message += f"💰 Total Activity: ${top_insider_value:,.0f}"
else:
message += "👤 No top insider data available."
return message
async def get_multiple_symbols_report(self, symbols: List[str],
filter_days: int = 7) -> Dict[str, TradingReport]:
"""Get reports for multiple symbols concurrently"""
tasks = [self.get_all_insider_trades(symbol, filter_days=filter_days) for symbol in symbols]
results = await asyncio.gather(*tasks, return_exceptions=True)
reports = {}
for i, result in enumerate(results):
symbol = symbols[i]
if isinstance(result, Exception):
logger.error(f"Error processing {symbol}: {result}")
reports[symbol] = None
else:
reports[symbol] = self.generate_trading_report(result, filter_days)
return reports
def trades_to_dataframe(self, trades: List[InsiderTrade]) -> pd.DataFrame:
"""Convert list of InsiderTrade objects to pandas DataFrame"""
if not trades:
return pd.DataFrame()
data = [trade.__dict__ for trade in trades]
df = pd.DataFrame(data)
# Convert date column with error handling
df['Transaction Date'] = pd.to_datetime(df['Transaction Date'], errors='coerce')
return df
# Example usage functions
async def example_single_symbol():
"""Example: Get report for single symbol"""
aggregator = InsiderTradingAggregator()
# Set your API keys here (use environment variables in a real app)
# aggregator.set_api_key('fmp', 'your_fmp_api_key')
# aggregator.set_api_key('sec_api', 'your_sec_api_key')
symbol = 'AAPL'
logger.info(f"--- Running single symbol example for ${symbol} ---")
trades = await aggregator.get_all_insider_trades(symbol, filter_days=30)
report = aggregator.generate_trading_report(trades)
if report:
telegram_msg = aggregator.format_telegram_message(report)
print("\n--- Full Telegram Message ---")
print(telegram_msg)
else:
print(f"No recent trades found for {symbol}")
async def example_multiple_symbols():
"""Example: Get reports for multiple symbols"""
aggregator = InsiderTradingAggregator()
symbols = ['AAPL', 'GOOGL', 'MSFT', 'TSLA']
logger.info(f"\n--- Running multiple symbols example for {', '.join(symbols)} ---")
reports = await aggregator.get_multiple_symbols_report(symbols, filter_days=30)
for symbol, report in reports.items():
print(f"\n--- Report for ${symbol} ---")
if report and report.total_trades > 0:
short_msg = aggregator.format_telegram_message_short(report)
print(short_msg)
else:
print(f"No recent trades found for {symbol}")
async def main():
await example_single_symbol()
print("\n" + "=" * 50)
await example_multiple_symbols()
if __name__ == "__main__":
# In some environments (like Windows), this policy is needed for aiohttp
# asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
asyncio.run(main())
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