update options stats
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MuslemRahimi
parent
9fa5f2c5c5
commit
1b8294d048
@ -1,56 +1,14 @@
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from __future__ import print_function
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import asyncio
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import aiohttp
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import time
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import intrinio_sdk as intrinio
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from intrinio_sdk.rest import ApiException
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from datetime import datetime, timedelta
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import ast
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import orjson
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from tqdm import tqdm
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import aiohttp
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from concurrent.futures import ThreadPoolExecutor
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import sqlite3
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from dotenv import load_dotenv
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import os
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import re
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load_dotenv()
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api_key = os.getenv('INTRINIO_API_KEY')
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intrinio.ApiClient().set_api_key(api_key)
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#intrinio.ApiClient().allow_retries(True)
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current_date = datetime.now().date()
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source = ''
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show_stats = ''
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stock_price_source = ''
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model = ''
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show_extended_price = ''
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after = datetime.today().strftime('%Y-%m-%d')
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before = '2100-12-31'
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include_related_symbols = False
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page_size = 5000
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MAX_CONCURRENT_REQUESTS = 50 # Adjust based on API rate limits
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BATCH_SIZE = 1500
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def get_expiration_date(option_symbol):
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# Define regex pattern to match the symbol structure
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match = re.match(r"([A-Z]+)(\d{6})([CP])(\d+)", option_symbol)
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if not match:
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raise ValueError(f"Invalid option_symbol format: {option_symbol}")
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ticker, expiration, option_type, strike_price = match.groups()
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# Convert expiration to datetime
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date_expiration = datetime.strptime(expiration, "%y%m%d").date()
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return date_expiration
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from statistics import mean
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# Database connection and symbol retrieval
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@ -84,13 +42,6 @@ def get_tickers_from_directory():
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print(f"An error occurred: {e}")
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return []
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def get_contracts_from_directory(symbol):
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directory = f"json/all-options-contracts/{symbol}/"
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try:
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return [file.replace(".json", "") for file in os.listdir(directory) if file.endswith(".json")]
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except:
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return []
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def save_json(data, symbol):
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directory = "json/options-stats/companies"
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os.makedirs(directory, exist_ok=True)
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@ -105,147 +56,28 @@ def safe_round(value):
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return value
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async def get_price_batch_realtime(symbol, contract_list):
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# API Configuration
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api_url = "https://api-v2.intrinio.com/options/prices/realtime/batch"
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headers = {
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"Authorization": f"Bearer {api_key}" # Replace with your actual API key
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}
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params = {
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"source": source,
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"show_stats": show_stats,
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"stock_price_source": stock_price_source,
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"model": model,
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"show_extended_price": show_extended_price
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}
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body = {
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"contracts": contract_list
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}
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# Make API request
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async with aiohttp.ClientSession() as session:
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async with session.post(api_url, headers=headers, params=params, json=body) as response:
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response_data = await response.json()
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contracts_data = response_data.get('contracts', [])
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res_dict = {
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'total_premium': 0, 'call_premium': 0, 'put_premium': 0,
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'volume': 0, 'call_volume': 0, 'put_volume': 0,
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'gex': 0,
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'total_open_interest': 0, 'call_open_interest': 0, 'put_open_interest': 0,
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'iv_list': [],
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'time': None
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}
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for item in contracts_data:
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try:
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price_data = item.get('price', {})
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stats_data = item.get('stats', {})
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option_data = item.get('option', {})
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option_type = option_data.get('type', '').lower()
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volume = int(price_data.get('volume', 0)) if price_data.get('volume') is not None else 0
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open_interest = int(price_data.get('open_interest', 0)) if price_data.get('open_interest') is not None else 0
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last_price = price_data.get('last', 0) or 0
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premium = int(volume * last_price * 100)
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implied_volatility = stats_data.get('implied_volatility')
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gamma = stats_data.get('gamma', 0) or 0
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delta = stats_data.get('delta', 0) or 0
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# Update metrics
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res_dict['gex'] += gamma * open_interest * 100
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res_dict['total_premium'] += premium
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res_dict['volume'] += volume
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res_dict['total_open_interest'] += open_interest
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if option_type == 'call':
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res_dict['call_premium'] += premium
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res_dict['call_volume'] += volume
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res_dict['call_open_interest'] += open_interest
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else:
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res_dict['put_premium'] += premium
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res_dict['put_volume'] += volume
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res_dict['put_open_interest'] += open_interest
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if implied_volatility is not None:
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res_dict['iv_list'].append(implied_volatility)
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# Handle timestamp
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if 'ask_timestamp' in price_data and price_data['ask_timestamp']:
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timestamp_str = price_data['ask_timestamp']
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try:
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dt = datetime.datetime.fromisoformat(timestamp_str.replace('Z', '+00:00'))
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res_dict['time'] = dt.strftime("%Y-%m-%d")
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except:
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res_dict['time'] = timestamp_str[:10] # Fallback to string slicing
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except Exception as e:
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print(f"Error processing contract: {e}")
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continue
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return res_dict
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async def main():
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total_symbols = get_tickers_from_directory()
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if len(total_symbols) < 3000:
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total_symbols = get_total_symbols()
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print(f"Number of tickers: {len(total_symbols)}")
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total_symbols = get_total_symbols()
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for symbol in tqdm(total_symbols):
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try:
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contract_list = get_contracts_from_directory(symbol)
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if len(contract_list) > 0:
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# Initialize aggregated results dictionary
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aggregated_results = {
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'total_premium': 0, 'call_premium': 0, 'put_premium': 0,
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'volume': 0, 'call_volume': 0, 'put_volume': 0,
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'gex': 0,
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'total_open_interest': 0, 'call_open_interest': 0, 'put_open_interest': 0,
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'iv_list': [],
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'time': None
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}
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# Load previous data and calculate changes
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with open(f"json/options-historical-data/companies/{symbol}.json", "r") as file:
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data = orjson.loads(file.read())
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# Process batches of 250 contracts
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for i in range(0, len(contract_list), 250):
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batch = contract_list[i:i+250]
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batch_results = await get_price_batch_realtime(symbol, batch)
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# Keys to compute the average for
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keys_to_average = [key for key in data[0] if key != "date"]
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# Aggregate results
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for key in ['total_premium', 'call_premium', 'put_premium',
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'volume', 'call_volume', 'put_volume',
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'gex',
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'total_open_interest', 'call_open_interest', 'put_open_interest']:
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aggregated_results[key] += batch_results[key]
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# Compute averages and round to 2 decimal places
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averages = {
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key: round(mean(d[key] for d in data if d.get(key) is not None), 2)
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for key in keys_to_average
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}
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aggregated_results['iv_list'].extend(batch_results['iv_list'])
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aggregated_results['time'] = batch_results['time']
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save_json(averages, symbol)
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# Calculate final metrics
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aggregated_results['iv'] = round((sum(aggregated_results['iv_list']) / len(aggregated_results['iv_list'])*100), 2) if aggregated_results['iv_list'] else 0
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aggregated_results['putCallRatio'] = round(aggregated_results['put_volume'] / aggregated_results['call_volume'], 2) if aggregated_results['call_volume'] > 0 else 0
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# Load previous data and calculate changes
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with open(f"json/options-historical-data/companies/{symbol}.json", "r") as file:
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past_data = orjson.loads(file.read())
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index = next((i for i, item in enumerate(past_data) if item['date'] == aggregated_results['time']), 0)
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previous_open_interest = past_data[index]['total_open_interest']
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iv_rank = past_data[index]['iv_rank']
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aggregated_results['changesPercentageOI'] = round((aggregated_results['total_open_interest']/previous_open_interest-1)*100, 2)
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aggregated_results['changeOI'] = aggregated_results['total_open_interest'] - previous_open_interest
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#we don't aggregate this result
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aggregated_results['ivRank'] = iv_rank
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# Remove the temporary iv_list before saving
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del aggregated_results['iv_list']
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# Save aggregated results
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save_json(aggregated_results, symbol)
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except Exception as e:
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print(f"Error processing {symbol}: {e}")
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except:
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pass
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if __name__ == "__main__":
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asyncio.run(main())
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@ -73,12 +73,11 @@ def run_market_flow():
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if week <= 4 and 8 <= hour < 20:
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run_command(["python3", "cron_market_flow.py"])
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def run_options_stats():
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def run_unusual_activity():
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now = datetime.now(ny_tz)
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week = now.weekday()
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hour = now.hour
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if week <= 4 and 9 <= hour <= 16:
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run_command(["python3", "cron_options_stats.py"])
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run_command(["python3", "cron_unusual_activity.py"])
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def run_dark_pool_level():
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@ -103,6 +102,7 @@ def run_options_jobs():
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run_command(["python3", "cron_options_historical_volume.py"])
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run_command(["python3", "cron_options_hottest_contracts.py"])
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run_command(["python3", "cron_implied_volatility.py"])
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run_command(["python3", "cron_options_stats.py"])
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run_command(["python3", "cron_options_oi.py"])
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'''
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run_command(["python3", "cron_options_gex_dex.py"])
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@ -422,7 +422,7 @@ schedule.every(3).hours.do(run_threaded, run_press_releases).tag('press_release_
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schedule.every(5).minutes.do(run_threaded, run_push_notifications).tag('push_notifications_job')
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schedule.every(30).minutes.do(run_threaded, run_options_stats).tag('options_stats_job')
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schedule.every(10).minutes.do(run_threaded, run_unusual_activity).tag('unusual_activity_job')
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schedule.every(5).minutes.do(run_threaded, run_market_flow).tag('market_flow_job')
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schedule.every(5).minutes.do(run_threaded, run_list).tag('stock_list_job')
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