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bugfixing congress

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This commit is contained in:
MuslemRahimi 2024-11-19 07:49:34 +01:00
parent f5dc885817
commit 32ce0e4565
1 changed files with 20 additions and 15 deletions
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35
app/cron_congress_trading.py
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@ -239,41 +239,45 @@ def create_politician_db(data, stock_symbols, stock_raw_data, etf_symbols, etf_r
# Convert defaultdict to list
grouped_data_list = list(grouped_data.values())
keys_to_keep = {'dateRecieved', 'id', 'transactionDate', 'representative', 'assetType', 'type', 'disclosureDate', 'symbol', 'name', 'amount'}
#keys_to_keep = {'dateRecieved', 'id', 'transactionDate', 'representative', 'assetType', 'type', 'disclosureDate', 'symbol', 'name', 'amount'}
for item in tqdm(grouped_data_list):
try:
item = [{key: entry[key] for key in entry if key in keys_to_keep} for entry in item]
#item = [{key: entry[key] for key in entry if key in keys_to_keep} for entry in item]
# Sort items by 'transactionDate'
item = sorted(item, key=lambda x: x['transactionDate'], reverse=True)
# Calculate top sectors
sector_list = []
industry_list = []
for holding in item:
for item2 in item:
try:
symbol = holding['symbol']
# Try to get 'symbol' first; if it doesn't exist, use 'ticker'
symbol = item2.get('symbol') or item2.get('ticker')
if not symbol:
continue # Skip if neither 'symbol' nor 'ticker' is present
ticker_data = stock_screener_data_dict.get(symbol, {})
# Extract specified columns data for each ticker
sector = ticker_data.get('sector',None)
industry = ticker_data.get('industry',None)
sector = ticker_data.get('sector', None)
industry = ticker_data.get('industry', None)
except:
sector = None
industry = None
if sector:
sector_list.append(sector)
if industry:
industry_list.append(industry)
# Append data to relevant lists if values are present
if sector:
sector_list.append(sector)
if industry:
industry_list.append(industry)
except Exception as e:
print(e)
# Get the top 3 most common sectors and industries
sector_counts = Counter(sector_list)
industry_counts = Counter(industry_list)
main_sectors = [item2[0] for item2 in sector_counts.most_common(3)]
main_industries = [item2[0] for item2 in industry_counts.most_common(3)]
# Prepare the data to save in the file
result = {
@ -386,6 +390,7 @@ async def run():
return
try:
connector = aiohttp.TCPConnector(limit=100) # Adjust the limit as needed
async with aiohttp.ClientSession(connector=connector) as session:
for i in tqdm(range(0, len(total_symbols), chunk_size)):