bugfixing options flow
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MuslemRahimi
parent
d6f04a5afb
commit
fe5d1f390e
@ -7,99 +7,106 @@ import asyncio
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from datetime import datetime, timedelta
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import concurrent.futures
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from GetStartEndDate import GetStartEndDate
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from dotenv import load_dotenv
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import os
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# Load environment variables
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load_dotenv()
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api_key = os.getenv('BENZINGA_API_KEY')
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# Initialize Benzinga API client
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fin = financial_data.Benzinga(api_key)
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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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# Database connection and fetching stock/ETF symbols
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def get_symbols(db_path, table_name):
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con = sqlite3.connect(db_path)
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cursor = con.cursor()
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cursor.execute(f"SELECT DISTINCT symbol FROM {table_name}")
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symbols = [row[0] for row in cursor.fetchall()]
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con.close()
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return symbols
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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_symbols = get_symbols('stocks.db', 'stocks')
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etf_symbols = get_symbols('etf.db', 'etfs')
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# Get start and end dates
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start_date_1d, end_date_1d = GetStartEndDate().run()
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start_date = start_date_1d.strftime("%Y-%m-%d")
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end_date = end_date_1d.strftime("%Y-%m-%d")
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#print(start_date,end_date)
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# Process a page of option activity
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def process_page(page):
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try:
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data = fin.options_activity(date_from=start_date, date_to=end_date, page=page, pagesize=1000)
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data = ujson.loads(fin.output(data))['option_activity']
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return data
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except Exception as e:
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print(e)
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print(f"Error on page {page}: {e}")
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return []
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# Fetch and process pages concurrently
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def fetch_options_data(max_pages=130, max_workers=6):
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res_list = []
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with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
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future_to_page = {executor.submit(process_page, page): page for page in range(max_pages)}
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for future in concurrent.futures.as_completed(future_to_page):
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page = future_to_page[future]
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try:
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page_data = future.result()
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res_list.extend(page_data)
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except Exception as e:
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print(f"Exception on page {page}: {e}")
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break
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return res_list
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# Assuming fin, stock_symbols, and etf_symbols are defined elsewhere
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res_list = []
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# Adjust max_workers to control the degree of parallelism
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max_workers = 6
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# Fetch pages concurrently
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with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
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future_to_page = {executor.submit(process_page, page): page for page in range(130)}
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for future in concurrent.futures.as_completed(future_to_page):
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page = future_to_page[future]
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# Clean and filter the fetched data
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def clean_and_filter_data(res_list):
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filtered_list = []
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for item in res_list:
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try:
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page_list = future.result()
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res_list += page_list
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if item.get('underlying_price', ''):
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ticker = item['ticker']
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ticker = 'BRK-A' if ticker == 'BRK.A' else 'BRK-B' if ticker == 'BRK.B' else ticker
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asset_type = 'stock' if ticker in stock_symbols else 'etf' if ticker in etf_symbols else ''
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if not asset_type:
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continue
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# Standardize item fields
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item.update({
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'underlying_type': asset_type.lower(),
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'put_call': 'Calls' if item['put_call'] == 'CALL' else 'Puts',
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'ticker': ticker,
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'price': round(float(item['price']), 2),
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'strike_price': round(float(item['strike_price']), 2),
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'cost_basis': round(float(item['cost_basis']), 2),
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'underlying_price': round(float(item['underlying_price']), 2),
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'option_activity_type': item['option_activity_type'].capitalize(),
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'sentiment': item['sentiment'].capitalize(),
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'execution_estimate': item['execution_estimate'].replace('_', ' ').title(),
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'tradeCount': item.get('trade_count', 0)
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})
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filtered_list.append({key: value for key, value in item.items() if key not in ['description_extended', 'updated']})
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except Exception as e:
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print(f"Exception occurred: {e}")
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break
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print(f"Error processing item: {e}")
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continue
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return filtered_list
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# res_list now contains the aggregated results from all pages
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#print(res_list)
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def custom_key(item):
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return item['time']
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# Main execution flow
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if __name__ == "__main__":
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# Fetch and process option data
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options_data = fetch_options_data()
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res_list = [{key: value for key, value in item.items() if key not in ['description_extended','updated']} for item in res_list]
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filtered_list = []
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for item in res_list:
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try:
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if item['underlying_price'] != '':
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ticker = item['ticker']
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if ticker == 'BRK.A':
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ticker = 'BRK-A'
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elif ticker == 'BRK.B':
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ticker = 'BRK-B'
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# Clean and filter the data
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filtered_data = clean_and_filter_data(options_data)
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put_call = 'Calls' if item['put_call'] == 'CALL' else 'Puts'
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# Sort the data by time
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sorted_data = sorted(filtered_data, key=lambda x: x['time'], reverse=True)
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asset_type = 'stock' if ticker in stock_symbols else ('etf' if ticker in etf_symbols else '')
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# Write the final data to a JSON file
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output_file = "json/options-flow/feed/data.json"
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with open(output_file, 'w') as file:
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ujson.dump(sorted_data, file)
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item['underlying_type'] = asset_type.lower()
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item['put_call'] = put_call
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item['ticker'] = ticker
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item['price'] = round(float(item['price']), 2)
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item['strike_price'] = round(float(item['strike_price']), 2)
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item['cost_basis'] = round(float(item['cost_basis']), 2)
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item['underlying_price'] = round(float(item['underlying_price']), 2)
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item['option_activity_type'] = item['option_activity_type'].capitalize()
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item['sentiment'] = item['sentiment'].capitalize()
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item['execution_estimate'] = item['execution_estimate'].replace('_', ' ').title()
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item['tradeCount'] = item['trade_count']
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filtered_list.append(item)
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except:
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pass
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filtered_list = sorted(filtered_list, key=custom_key, reverse =True)
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with open(f"json/options-flow/feed/data.json", 'w') as file:
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ujson.dump(filtered_list, file)
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stock_con.close()
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etf_con.close()
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print(f"Data successfully written to {output_file}")
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