import aiohttp import aiofiles import ujson import sqlite3 import pandas as pd import asyncio import pytz import time import os from dotenv import load_dotenv from datetime import datetime, timedelta, date import sqlite3 headers = {"accept": "application/json"} load_dotenv() benzinga_api_key = os.getenv('BENZINGA_API_KEY') benzinga_api_key_extra = os.getenv('BENZINGA_API_KEY_EXTRA') query_template = """ SELECT marketCap FROM stocks WHERE symbol = ? """ async def save_json(data): with open(f"json/dashboard/data.json", 'w') as file: ujson.dump(data, file) def parse_time(time_str): try: # Try parsing as full datetime return datetime.strptime(time_str, '%Y-%m-%d %H:%M:%S') except ValueError: try: # Try parsing as time only time_obj = datetime.strptime(time_str, '%H:%M:%S').time() # Combine with today's date return datetime.combine(date.today(), time_obj) except ValueError: # If all else fails, return a default datetime return datetime.min def remove_duplicates(elements): seen = set() unique_elements = [] for element in elements: if element['symbol'] not in seen: seen.add(element['symbol']) unique_elements.append(element) return unique_elements def weekday(): today = datetime.today() one_day = timedelta(1) yesterday = today - one_day while yesterday.weekday() >= 5: # 5 = Saturday, 6 = Sunday yesterday -= one_day return yesterday.strftime('%Y-%m-%d') today = datetime.today().strftime('%Y-%m-%d') tomorrow = (datetime.today() + timedelta(1)) yesterday = weekday() if tomorrow.weekday() >= 5: # 5 = Saturday, 6 = Sunday tomorrow = tomorrow + timedelta(days=(7 - tomorrow.weekday())) tomorrow = tomorrow.strftime('%Y-%m-%d') async def get_upcoming_earnings(session): url = "https://api.benzinga.com/api/v2.1/calendar/earnings" importance_list = ["3","4","5"] res_list = [] for importance in importance_list: querystring = {"token": benzinga_api_key_extra,"parameters[importance]":importance,"parameters[date_from]":tomorrow,"parameters[date_to]":tomorrow,"parameters[date_sort]":"date"} try: async with session.get(url, params=querystring, headers=headers) as response: res = ujson.loads(await response.text())['earnings'] for item in res: try: symbol = item['ticker'] name = item['name'] time = item['time'] eps_prior = float(item['eps_prior']) if item['eps_prior'] != '' else 0 eps_est = float(item['eps_est']) if item['eps_est'] != '' else 0 revenue_est = float(item['revenue_est']) if item['revenue_est'] != '' else 0 revenue_prior = float(item['revenue_prior']) if item['revenue_prior'] != '' else 0 if symbol in stock_symbols and revenue_est != 0 and revenue_prior != 0 and eps_prior != 0 and eps_est != 0: df = pd.read_sql_query(query_template, con, params=(symbol,)) market_cap = float(df['marketCap'].iloc[0]) if df['marketCap'].iloc[0] != '' else 0 res_list.append({ 'symbol': symbol, 'name': name, 'time': time, 'marketCap': market_cap, 'epsPrior':eps_prior, 'epsEst': eps_est, 'revenuePrior': revenue_prior, 'revenueEst': revenue_est }) except Exception as e: print('1 Upcoming Earnings:', e) pass res_list = remove_duplicates(res_list) res_list.sort(key=lambda x: x['marketCap'], reverse=True) res_list = [{k: v for k, v in d.items() if k != 'marketCap'} for d in res_list] except Exception as e: pass return res_list[0:5] async def get_recent_earnings(session): url = "https://api.benzinga.com/api/v2.1/calendar/earnings" importance_list = ["3","4","5"] res_list = [] for importance in importance_list: querystring = {"token": benzinga_api_key_extra,"parameters[importance]":importance,"parameters[date_from]":yesterday,"parameters[date_to]":today,"parameters[date_sort]":"date"} try: async with session.get(url, params=querystring, headers=headers) as response: res = ujson.loads(await response.text())['earnings'] for item in res: try: symbol = item['ticker'] name = item['name'] time = item['time'] eps_prior = float(item['eps_prior']) if item['eps_prior'] != '' else 0 eps_surprise = float(item['eps_surprise']) if item['eps_surprise'] != '' else 0 eps = float(item['eps']) if item['eps'] != '' else 0 revenue_prior = float(item['revenue_prior']) if item['revenue_prior'] != '' else 0 revenue_surprise = float(item['revenue_surprise']) if item['revenue_surprise'] != '' else 0 revenue = float(item['revenue']) if item['revenue'] != '' else 0 if symbol in stock_symbols and revenue != 0 and revenue_prior != 0 and eps_prior != 0 and eps != 0 and revenue_surprise != 0 and eps_surprise != 0: df = pd.read_sql_query(query_template, con, params=(symbol,)) market_cap = float(df['marketCap'].iloc[0]) if df['marketCap'].iloc[0] != '' else 0 res_list.append({ 'symbol': symbol, 'name': name, 'time': time, 'marketCap': market_cap, 'epsPrior':eps_prior, 'epsSurprise': eps_surprise, 'eps': eps, 'revenuePrior': revenue_prior, 'revenueSurprise': revenue_surprise, 'revenue': revenue }) except Exception as e: print('Recent Earnings:', e) pass except Exception as e: pass res_list = remove_duplicates(res_list) #res_list.sort(key=lambda x: x['marketCap'], reverse=True) res_list.sort(key=lambda x: (-parse_time(x['time']).timestamp(), -x['marketCap'])) res_list = [{k: v for k, v in d.items() if k != 'marketCap'} for d in res_list] return res_list[0:5] async def get_latest_bezinga_market_news(session): url = "https://api.benzinga.com/api/v2/news" querystring = {"token": benzinga_api_key,"channels":"News","pageSize":"10","displayOutput":"full"} try: async with session.get(url, params=querystring, headers=headers) as response: res_list = [] res = ujson.loads(await response.text()) for item in res: res_list.append({'date': item['created'], 'text': item['title'], 'url': item['url']}) res_list.sort(key=lambda x: datetime.strptime(x['date'], '%a, %d %b %Y %H:%M:%S %z'), reverse=True) return res_list except Exception as e: #pass print(e) async def run(): async with aiohttp.ClientSession() as session: benzinga_news = await get_latest_bezinga_market_news(session) recent_earnings = await get_recent_earnings(session) upcoming_earnings = await get_upcoming_earnings(session) try: with open(f"json/retail-volume/data.json", 'r') as file: retail_tracker = ujson.load(file)[0:5] except: retail_tracker = [] try: with open(f"json/options-flow/feed/data.json", 'r') as file: options_flow = ujson.load(file) # Filter the options_flow to include only items with ticker in total_symbol options_flow = [item for item in options_flow if item['ticker'] in total_symbols] options_flow = sorted(options_flow, key=lambda x: x['cost_basis'], reverse=True) options_flow = [{key: item[key] for key in ['cost_basis', 'ticker','assetType', 'date_expiration', 'put_call', 'sentiment', 'strike_price']} for item in options_flow[0:4]] except: options_flow = [] try: with open(f"json/wiim/rss-feed/data.json", 'r') as file: wiim_feed = ujson.load(file)[0:5] except: wiim_feed = [] try: with open(f"json/market-movers/data.json", 'r') as file: data = ujson.load(file) market_mover = {'winner': data['gainers']['1D'][0], 'loser': data['losers']['1D'][0], 'active': data['active']['1D'][0]} except: market_mover = {} try: with open(f"json/most-shorted-stocks/data.json", 'r') as file: data = ujson.load(file)[0] shorted_stock = {key: data[key] for key in ['symbol', 'shortOutStandingPercent']} except: shorted_stock = {} quick_info = {**market_mover, 'shorted': shorted_stock} data = { 'quickInfo': quick_info, 'optionsFlow': options_flow, 'retailTracker': retail_tracker, 'wiimFeed': wiim_feed, 'marketNews': benzinga_news, 'recentEarnings': recent_earnings, 'upcomingEarnings': upcoming_earnings } if len(data) > 0: await save_json(data) try: con = sqlite3.connect('stocks.db') etf_con = sqlite3.connect('etf.db') cursor = con.cursor() cursor.execute("PRAGMA journal_mode = wal") cursor.execute("SELECT DISTINCT symbol FROM stocks") stock_symbols = [row[0] for row in cursor.fetchall()] etf_cursor = etf_con.cursor() etf_cursor.execute("PRAGMA journal_mode = wal") etf_cursor.execute("SELECT DISTINCT symbol FROM etfs") etf_symbols = [row[0] for row in etf_cursor.fetchall()] total_symbols = stock_symbols+etf_symbols asyncio.run(run()) con.close() etf_con.close() except Exception as e: print(e)