386 lines
15 KiB
Python
386 lines
15 KiB
Python
import aiohttp
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import aiofiles
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import ujson
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import sqlite3
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import pandas as pd
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import asyncio
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import pytz
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import os
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from dotenv import load_dotenv
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from datetime import datetime, timedelta, date
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import sqlite3
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headers = {"accept": "application/json"}
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def check_market_hours():
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holidays = [
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"2024-01-01", "2024-01-15", "2024-02-19", "2024-03-29",
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"2024-05-27", "2024-06-19", "2024-07-04", "2024-09-02",
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"2024-11-28", "2024-12-25"
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]
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# Get the current date and time in ET (Eastern Time)
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et_timezone = pytz.timezone('America/New_York')
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current_time = datetime.now(et_timezone)
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current_date_str = current_time.strftime('%Y-%m-%d')
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current_hour = current_time.hour
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current_minute = current_time.minute
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current_day = current_time.weekday() # Monday is 0, Sunday is 6
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# Check if the current date is a holiday or weekend
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is_weekend = current_day >= 5 # Saturday (5) or Sunday (6)
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is_holiday = current_date_str in holidays
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# Determine the market status
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if is_weekend or is_holiday:
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return 0 #Closed
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elif current_hour < 9 or (current_hour == 9 and current_minute < 30):
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return 1 # Pre-Market
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elif 9 <= current_hour < 16 or (current_hour == 16 and current_minute == 0):
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return 0 #"Market hours."
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elif 16 <= current_hour < 24:
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return 2 #"After-market hours."
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else:
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return 0 #"Market is closed."
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load_dotenv()
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benzinga_api_key = os.getenv('BENZINGA_API_KEY')
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fmp_api_key = os.getenv('FMP_API_KEY')
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query_template = """
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SELECT
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marketCap
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FROM
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stocks
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WHERE
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symbol = ?
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"""
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async def save_json(data):
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with open(f"json/dashboard/data.json", 'w') as file:
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ujson.dump(data, file)
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def parse_time(time_str):
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try:
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# Try parsing as full datetime
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return datetime.strptime(time_str, '%Y-%m-%d %H:%M:%S')
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except ValueError:
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try:
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# Try parsing as time only
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time_obj = datetime.strptime(time_str, '%H:%M:%S').time()
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# Combine with today's date
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return datetime.combine(date.today(), time_obj)
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except ValueError:
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# If all else fails, return a default datetime
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return datetime.min
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def remove_duplicates(elements):
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seen = set()
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unique_elements = []
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for element in elements:
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if element['symbol'] not in seen:
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seen.add(element['symbol'])
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unique_elements.append(element)
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return unique_elements
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def weekday():
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today = datetime.today()
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if today.weekday() >= 5: # 5 = Saturday, 6 = Sunday
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yesterday = today - timedelta(2)
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else:
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yesterday = today - timedelta(1)
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return yesterday.strftime('%Y-%m-%d')
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today = datetime.today().strftime('%Y-%m-%d')
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tomorrow = (datetime.today() + timedelta(1))
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yesterday = weekday()
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if tomorrow.weekday() >= 5: # 5 = Saturday, 6 = Sunday
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tomorrow = tomorrow + timedelta(days=(7 - tomorrow.weekday()))
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tomorrow = tomorrow.strftime('%Y-%m-%d')
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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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url = "https://api.benzinga.com/api/v2.1/calendar/earnings"
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res_list = []
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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]":yesterday,"parameters[date_to]":today,"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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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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eps_prior = float(item['eps_prior']) if item['eps_prior'] != '' else 0
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eps_surprise = float(item['eps_surprise']) if item['eps_surprise'] != '' else 0
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eps = float(item['eps']) if item['eps'] != '' else 0
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revenue_prior = float(item['revenue_prior']) if item['revenue_prior'] != '' else 0
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revenue_surprise = float(item['revenue_surprise']) if item['revenue_surprise'] != '' else 0
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revenue = float(item['revenue']) if item['revenue'] != '' else 0
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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:
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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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'marketCap': market_cap,
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'epsPrior':eps_prior,
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'epsSurprise': eps_surprise,
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'eps': eps,
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'revenuePrior': revenue_prior,
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'revenueSurprise': revenue_surprise,
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'revenue': revenue
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})
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except Exception as e:
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print('Recent Earnings:', e)
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pass
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except Exception as e:
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pass
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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.sort(key=lambda x: (-parse_time(x['time']).timestamp(), -x['marketCap']))
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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[0:10]
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async def get_recent_dividends(session):
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url = "https://api.benzinga.com/api/v2.1/calendar/dividends"
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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]":yesterday,"parameters[date_to]":today}
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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())['dividends']
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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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dividend = float(item['dividend']) if item['dividend'] != '' else 0
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dividend_prior = float(item['dividend_prior']) if item['dividend_prior'] != '' else 0
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dividend_yield = round(float(item['dividend_yield'])*100,2) if item['dividend_yield'] != '' else 0
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ex_dividend_date = item['ex_dividend_date'] if item['ex_dividend_date'] != '' else 0
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payable_date = item['payable_date'] if item['payable_date'] != '' else 0
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record_date = item['record_date'] if item['record_date'] != '' else 0
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if symbol in stock_symbols and dividend != 0 and payable_date != 0 and dividend_prior != 0 and ex_dividend_date != 0 and record_date != 0 and dividend_yield != 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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'dividend': dividend,
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'marketCap': market_cap,
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'dividendPrior':dividend_prior,
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'dividendYield': dividend_yield,
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'exDividendDate': ex_dividend_date,
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'payableDate': payable_date,
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'recordDate': record_date,
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'updated': item['updated']
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})
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except Exception as e:
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print('Recent Dividends:', 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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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[0:5]
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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, 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, 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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#Avoid clashing of recent and upcoming earnings
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upcoming_earnings = [item for item in upcoming_earnings if item['symbol'] not in [earning['symbol'] for earning in recent_earnings]]
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try:
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with open(f"json/retail-volume/data.json", 'r') as file:
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retail_tracker = ujson.load(file)[0:5]
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except:
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retail_tracker = []
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try:
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with open(f"json/options-flow/feed/data.json", 'r') as file:
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options_flow = ujson.load(file)
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# Filter the options_flow to include only items with ticker in total_symbol
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options_flow = [item for item in options_flow if item['ticker'] in stock_symbols]
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highest_volume = sorted(options_flow, key=lambda x: int(x['volume']), reverse=True)
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highest_volume = [{key: item[key] for key in ['cost_basis', 'ticker','underlying_type', 'date_expiration', 'put_call', 'volume', 'strike_price']} for item in highest_volume[0:4]]
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highest_premium = sorted(options_flow, key=lambda x: int(x['cost_basis']), reverse=True)
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highest_premium = [{key: item[key] for key in ['cost_basis', 'ticker','underlying_type', 'date_expiration', 'put_call', 'volume', 'strike_price']} for item in highest_premium[0:4]]
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highest_open_interest = sorted(options_flow, key=lambda x: int(x['open_interest']), reverse=True)
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highest_open_interest = [{key: item[key] for key in ['cost_basis', 'ticker','underlying_type', 'date_expiration', 'put_call', 'open_interest', 'strike_price']} for item in highest_open_interest[0:4]]
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options_flow = {'premium': highest_premium, 'volume': highest_volume, 'openInterest':highest_open_interest}
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except Exception as e:
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print(e)
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options_flow = {}
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market_status = check_market_hours()
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print(market_status)
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if market_status == 0:
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try:
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with open(f"json/market-movers/data.json", 'r') as file:
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data = ujson.load(file)
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market_movers = {'gainers': data['gainers']['1D'][:5], 'losers': data['losers']['1D'][:5]}
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except:
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market_movers = {}
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elif market_status == 1:
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try:
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with open(f"json/market-movers/premarket.json", 'r') as file:
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data = ujson.load(file)
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gainers = [{ 'symbol': item['symbol'], 'name': item['name'], 'price': item['price'], 'changesPercentage': item['changesPercentage']} for item in data['gainers'][:5]]
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losers = [{ 'symbol': item['symbol'], 'name': item['name'], 'price': item['price'], 'changesPercentage': item['changesPercentage']} for item in data['losers'][:5]]
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market_movers={'gainers': gainers, 'losers': losers}
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except:
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market_movers = {}
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elif market_status == 2:
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try:
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with open(f"json/market-movers/afterhours.json", 'r') as file:
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data = ujson.load(file)
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gainers = [{ 'symbol': item['symbol'], 'name': item['name'], 'price': item['price'], 'changesPercentage': item['changesPercentage']} for item in data['gainers'][:5]]
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losers = [{ 'symbol': item['symbol'], 'name': item['name'], 'price': item['price'], 'changesPercentage': item['changesPercentage']} for item in data['losers'][:5]]
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market_movers={'gainers': gainers, 'losers': losers}
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except:
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market_movers = {}
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data = {
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'marketMovers': market_movers,
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'marketStatus': market_status,
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'optionsFlow': options_flow,
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'recentEarnings': recent_earnings,
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'upcomingEarnings': upcoming_earnings,
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'recentDividends': recent_dividends,
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}
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if len(data) > 0:
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await save_json(data)
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try:
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con = sqlite3.connect('stocks.db')
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etf_con = sqlite3.connect('etf.db')
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cursor = con.cursor()
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cursor.execute("PRAGMA journal_mode = wal")
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cursor.execute("SELECT DISTINCT symbol FROM stocks")
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stock_symbols = [row[0] for row in cursor.fetchall()]
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etf_cursor = etf_con.cursor()
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etf_cursor.execute("PRAGMA journal_mode = wal")
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etf_cursor.execute("SELECT DISTINCT symbol FROM etfs")
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etf_symbols = [row[0] for row in etf_cursor.fetchall()]
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total_symbols = stock_symbols+etf_symbols
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asyncio.run(run())
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con.close()
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etf_con.close()
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except Exception as e:
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print(e) |