update dashboard
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MuslemRahimi
parent
bdb4b829bc
commit
020480d2bd
@ -250,20 +250,23 @@ def create_politician_db(data, stock_symbols, stock_raw_data, etf_symbols, etf_r
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# Calculate top sectors
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sector_list = []
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industry_list = []
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for item2 in item:
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symbol = item2['symbol']
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ticker_data = stock_screener_data_dict.get(symbol, {})
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for holding in item:
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try:
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symbol = holding['symbol']
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ticker_data = stock_screener_data_dict.get(symbol, {})
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# Extract specified columns data for each ticker
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sector = ticker_data.get('sector',None)
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industry = ticker_data.get('industry',None)
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# Extract specified columns data for each ticker
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sector = ticker_data.get('sector',None)
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industry = ticker_data.get('industry',None)
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# Append data to relevant lists if values are present
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if sector:
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sector_list.append(sector)
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if industry:
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industry_list.append(industry)
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# Append data to relevant lists if values are present
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if sector:
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sector_list.append(sector)
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if industry:
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industry_list.append(industry)
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except:
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pass
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# Get the top 3 most common sectors and industries
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sector_counts = Counter(sector_list)
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@ -375,7 +378,7 @@ async def run():
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crypto_con.close()
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total_symbols = crypto_symbols +etf_symbols + stock_symbols
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chunk_size = 100
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chunk_size = 200
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politician_list = []
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except Exception as e:
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@ -384,7 +387,7 @@ async def run():
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try:
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connector = aiohttp.TCPConnector(limit=100) # Adjust the limit as needed
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connector = aiohttp.TCPConnector(limit=200) # Adjust the limit as needed
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async with aiohttp.ClientSession(connector=connector) as session:
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for i in tqdm(range(0, len(total_symbols), chunk_size)):
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try:
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@ -392,7 +395,7 @@ async def run():
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data = await get_congress_data(symbols_chunk,session)
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politician_list +=data
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print('sleeping')
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await asyncio.sleep(30)
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await asyncio.sleep(10)
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except Exception as e:
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print(e)
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pass
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@ -109,56 +109,71 @@ if tomorrow.weekday() >= 5: # 5 = Saturday, 6 = Sunday
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tomorrow = tomorrow.strftime('%Y-%m-%d')
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async def get_upcoming_earnings(session, end_date):
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url = "https://api.benzinga.com/api/v2.1/calendar/earnings"
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importance_list = ["1","2","3","4","5"]
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res_list = []
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for importance in importance_list:
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querystring = {"token": benzinga_api_key,"parameters[importance]":importance,"parameters[date_from]":today,"parameters[date_to]":end_date,"parameters[date_sort]":"date"}
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try:
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async with session.get(url, params=querystring, headers=headers) as response:
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res = ujson.loads(await response.text())['earnings']
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res = [e for e in res if datetime.strptime(e['date'], "%Y-%m-%d").date() != date.today() or datetime.strptime(e['time'], "%H:%M:%S").time() >= datetime.strptime("16:00:00", "%H:%M:%S").time()]
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for item in res:
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try:
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symbol = item['ticker']
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name = item['name']
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time = item['time']
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is_today = True if item['date'] == datetime.today().strftime('%Y-%m-%d') else False
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eps_prior = float(item['eps_prior']) if item['eps_prior'] != '' else 0
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eps_est = float(item['eps_est']) if item['eps_est'] != '' else 0
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revenue_est = float(item['revenue_est']) if item['revenue_est'] != '' else 0
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revenue_prior = float(item['revenue_prior']) if item['revenue_prior'] != '' else 0
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if symbol in stock_symbols and revenue_est != 0 and revenue_prior != 0 and eps_prior != 0 and eps_est != 0:
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df = pd.read_sql_query(query_template, con, params=(symbol,))
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market_cap = float(df['marketCap'].iloc[0]) if df['marketCap'].iloc[0] != '' else 0
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res_list.append({
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'symbol': symbol,
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'name': name,
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'time': time,
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'isToday': is_today,
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'marketCap': market_cap,
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'epsPrior':eps_prior,
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'epsEst': eps_est,
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'revenuePrior': revenue_prior,
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'revenueEst': revenue_est
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})
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except Exception as e:
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print('Upcoming Earnings:', e)
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pass
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except Exception as e:
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print(e)
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pass
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try:
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res_list = remove_duplicates(res_list)
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res_list.sort(key=lambda x: x['marketCap'], reverse=True)
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#res_list = [{k: v for k, v in d.items() if k != 'marketCap'} for d in res_list]
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return res_list[:10]
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except Exception as e:
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print(e)
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return []
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async def get_upcoming_earnings(session, end_date, filter_today=False):
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url = "https://api.benzinga.com/api/v2.1/calendar/earnings"
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importance_list = ["1", "2", "3", "4", "5"]
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res_list = []
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today = date.today().strftime('%Y-%m-%d')
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for importance in importance_list:
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querystring = {
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"token": benzinga_api_key,
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"parameters[importance]": importance,
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"parameters[date_from]": today,
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"parameters[date_to]": end_date,
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"parameters[date_sort]": "date"
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}
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try:
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async with session.get(url, params=querystring, headers=headers) as response:
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res = ujson.loads(await response.text())['earnings']
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# Apply the time filter if filter_today is True
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if filter_today:
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res = [
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e for e in res if
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datetime.strptime(e['date'], "%Y-%m-%d").date() != date.today() or
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datetime.strptime(e['time'], "%H:%M:%S").time() >= datetime.strptime("16:00:00", "%H:%M:%S").time()
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]
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for item in res:
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try:
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symbol = item['ticker']
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name = item['name']
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time = item['time']
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is_today = item['date'] == today
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eps_prior = float(item['eps_prior']) if item['eps_prior'] != '' else 0
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eps_est = float(item['eps_est']) if item['eps_est'] != '' else 0
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revenue_est = float(item['revenue_est']) if item['revenue_est'] != '' else 0
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revenue_prior = float(item['revenue_prior']) if item['revenue_prior'] != '' else 0
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if symbol in stock_symbols and revenue_est and revenue_prior and eps_prior and eps_est:
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df = pd.read_sql_query(query_template, con, params=(symbol,))
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market_cap = float(df['marketCap'].iloc[0]) if df['marketCap'].iloc[0] != '' else 0
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res_list.append({
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'symbol': symbol,
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'name': name,
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'time': time,
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'isToday': is_today,
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'marketCap': market_cap,
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'epsPrior': eps_prior,
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'epsEst': eps_est,
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'revenuePrior': revenue_prior,
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'revenueEst': revenue_est
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})
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except Exception as e:
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print('Upcoming Earnings:', e)
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pass
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except Exception as e:
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print(e)
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pass
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try:
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res_list = remove_duplicates(res_list)
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res_list.sort(key=lambda x: x['marketCap'], reverse=True)
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return res_list[:10]
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except Exception as e:
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print(e)
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return []
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async def get_recent_earnings(session):
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@ -263,9 +278,16 @@ async def get_recent_dividends(session):
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async def run():
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async with aiohttp.ClientSession() as session:
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recent_earnings = await get_recent_earnings(session)
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upcoming_earnings = await get_upcoming_earnings(session, today)
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upcoming_earnings = await get_upcoming_earnings(session, today, filter_today=True)
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# If results are less than 5, try without the time filter.
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if len(upcoming_earnings) < 5:
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upcoming_earnings = await get_upcoming_earnings(session, tomorrow)
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upcoming_earnings = await get_upcoming_earnings(session, today, filter_today=False)
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# If still less than 5 results, try fetching for tomorrow.
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if len(upcoming_earnings) < 5:
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upcoming_earnings = await get_upcoming_earnings(session, tomorrow)
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recent_dividends = await get_recent_dividends(session)
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