backend/app/cron_options_stats.py
2024-12-30 23:45:38 +01:00

126 lines
4.1 KiB
Python

import requests
import orjson
from dotenv import load_dotenv
import os
import sqlite3
import time
load_dotenv()
api_key = os.getenv('UNUSUAL_WHALES_API_KEY')
# Connect to the databases
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 WHERE symbol NOT LIKE '%.%'")
stocks_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()]
con.close()
etf_con.close()
# Combine the lists of stock and ETF symbols
total_symbols = stocks_symbols + etf_symbols
def save_json(data, symbol):
directory = "json/options-stats/companies"
os.makedirs(directory, exist_ok=True) # Ensure the directory exists
with open(f"{directory}/{symbol}.json", 'wb') as file: # Use binary mode for orjson
file.write(orjson.dumps(data))
def safe_round(value):
"""Attempt to convert a value to float and round it. Return the original value if not possible."""
try:
return round(float(value), 2)
except (ValueError, TypeError):
return value
def calculate_neutral_premium(data_item):
"""Calculate the neutral premium for a data item."""
call_premium = float(data_item['call_premium'])
put_premium = float(data_item['put_premium'])
bearish_premium = float(data_item['bearish_premium'])
bullish_premium = float(data_item['bullish_premium'])
total_premiums = bearish_premium + bullish_premium
observed_premiums = call_premium + put_premium
neutral_premium = observed_premiums - total_premiums
return safe_round(neutral_premium)
def prepare_data(data):
for item in data:
symbol = item['ticker']
bearish_premium = float(item['bearish_premium'])
bullish_premium = float(item['bullish_premium'])
neutral_premium = calculate_neutral_premium(item)
new_item = {
key: safe_round(value)
for key, value in item.items()
if key != 'in_out_flow'
}
new_item['premium_ratio'] = [
safe_round(bearish_premium),
neutral_premium,
safe_round(bullish_premium)
]
try:
new_item['open_interest_change'] = new_item['total_open_interest'] - (new_item.get('prev_call_oi',0) + new_item.get('prev_put_oi',0))
except:
new_item['open_interest_change'] = None
if len(new_item) > 0:
save_json(new_item, symbol)
def chunk_symbols(symbols, chunk_size=50):
for i in range(0, len(symbols), chunk_size):
yield symbols[i:i + chunk_size]
chunks = chunk_symbols(total_symbols)
chunk_counter = 0 # To keep track of how many chunks have been processed
for chunk in chunks:
try:
chunk_str = ",".join(chunk)
print(chunk_str)
url = "https://api.unusualwhales.com/api/screener/stocks"
querystring = {"ticker": chunk_str}
headers = {
"Accept": "application/json, text/plain",
"Authorization": api_key
}
response = requests.get(url, headers=headers, params=querystring)
if response.status_code == 200:
data = response.json()['data']
prepare_data(data)
print(f"Chunk processed. Number of results: {len(data)}")
else:
print(f"Error fetching data for chunk {chunk_str}: {response.status_code}")
# Increment the chunk counter
chunk_counter += 1
# If 50 chunks have been processed, sleep for 60 seconds
if chunk_counter == 50:
print("Processed 50 chunks. Sleeping for 60 seconds...")
time.sleep(60) # Sleep for 60 seconds
chunk_counter = 0 # Reset the chunk counter after sleep
except Exception as e:
print(f"Error processing chunk {chunk_str}: {e}")