140 lines
5.5 KiB
Python
Executable File
140 lines
5.5 KiB
Python
Executable File
import sqlite3
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from datetime import datetime, timedelta, date
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import ujson
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import asyncio
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import os
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from dotenv import load_dotenv
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from benzinga import financial_data
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import time
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load_dotenv()
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api_key = os.getenv('BENZINGA_API_KEY')
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fin = financial_data.Benzinga(api_key)
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def calculate_dte(date_expiration):
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expiration_date = datetime.strptime(date_expiration, "%Y-%m-%d")
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return (expiration_date - datetime.today()).days
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def calculate_avg_dte(data):
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active_options = [entry for entry in data if calculate_dte(entry['date_expiration']) >= 0]
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if active_options:
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total_dte = sum(entry['dte'] for entry in active_options)
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return int(total_dte / len(active_options))
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else:
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return 0
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def calculate_put_call_volumes(data):
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put_volume = sum(int(entry['volume']) for entry in data if entry['put_call'] == 'PUT')
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call_volume = sum(int(entry['volume']) for entry in data if entry['put_call'] == 'CALL')
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return put_volume, call_volume
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def options_bubble_data(chunk):
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try:
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company_tickers = ','.join(chunk)
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end_date = date.today()
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start_date = end_date - timedelta(90)
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end_date_str = end_date.strftime('%Y-%m-%d')
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start_date_str = start_date.strftime('%Y-%m-%d')
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res_list = []
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for page in range(0, 100):
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try:
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data = fin.options_activity(company_tickers=company_tickers, page=page, pagesize=500, date_from=start_date_str, date_to=end_date_str)
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data = ujson.loads(fin.output(data))['option_activity']
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res_list += data
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except:
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break
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res_filtered = [{key: value for key, value in item.items() if key in ['ticker','date', 'date_expiration', 'put_call', 'volume', 'open_interest']} for item in res_list]
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for option_type in ['CALL', 'PUT']:
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for item in res_filtered:
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if item['put_call'].upper() == option_type:
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item['dte'] = calculate_dte(item['date_expiration'])
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if item['ticker'] in ['BRK.A', 'BRK.B']:
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item['ticker'] = f"BRK-{item['ticker'][-1]}"
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#Save raw data for each ticker for options page stack bar chart
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for ticker in chunk:
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ticker_filtered_data = [entry for entry in res_filtered if entry['ticker'] == ticker]
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if len(ticker_filtered_data) != 0:
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#sum up calls and puts for each day for the plot
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summed_data = {}
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for entry in ticker_filtered_data:
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volume = int(entry['volume'])
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open_interest = int(entry['open_interest'])
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put_call = entry['put_call']
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if entry['date'] not in summed_data:
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summed_data[entry['date']] = {'CALL': {'volume': 0, 'open_interest': 0}, 'PUT': {'volume': 0, 'open_interest': 0}}
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summed_data[entry['date']][put_call]['volume'] += volume
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summed_data[entry['date']][put_call]['open_interest'] += open_interest
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result_list = [{'date': date, 'CALL': summed_data[date]['CALL'], 'PUT': summed_data[date]['PUT']} for date in summed_data]
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#reverse the list
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result_list = result_list[::-1]
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with open(f"json/options-flow/company/{ticker}.json", 'w') as file:
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ujson.dump(result_list, file)
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#Save bubble data for each ticker for overview page
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for ticker in chunk:
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bubble_data = {}
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for time_period, days in {'oneDay': 1, 'oneWeek': 7, 'oneMonth': 30, 'threeMonth': 90}.items():
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start_date = end_date - timedelta(days=days) #end_date is today
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filtered_data = [item for item in res_filtered if start_date <= datetime.strptime(item['date'], '%Y-%m-%d').date() <= end_date]
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ticker_filtered_data = [entry for entry in filtered_data if entry['ticker'] == ticker]
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put_volume, call_volume = calculate_put_call_volumes(ticker_filtered_data)
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avg_dte = calculate_avg_dte(ticker_filtered_data)
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bubble_data[time_period] = {'putVolume': put_volume, 'callVolume': call_volume, 'avgDTE': avg_dte}
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if all(all(value == 0 for value in data.values()) for data in bubble_data.values()):
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bubble_data = {}
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#don't save the json
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else:
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with open(f"json/options-bubble/{ticker}.json", 'w') as file:
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ujson.dump(bubble_data, file)
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except ValueError as ve:
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print(ve)
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except Exception as e:
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print(e)
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try:
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stock_con = sqlite3.connect('stocks.db')
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stock_cursor = stock_con.cursor()
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stock_cursor.execute("SELECT DISTINCT symbol FROM stocks")
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stock_symbols = [row[0] for row in stock_cursor.fetchall()]
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etf_con = sqlite3.connect('etf.db')
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etf_cursor = etf_con.cursor()
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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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stock_con.close()
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etf_con.close()
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total_symbols = stock_symbols + etf_symbols
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total_symbols = [item.replace("BRK-B", "BRK.B") for item in total_symbols]
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chunk_size = len(total_symbols) // 20 # Divide the list into N chunks
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chunks = [total_symbols[i:i + chunk_size] for i in range(0, len(total_symbols), chunk_size)]
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for chunk in chunks:
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options_bubble_data(chunk)
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except Exception as e:
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print(e)
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