91 lines
2.8 KiB
Python
91 lines
2.8 KiB
Python
import os
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import pandas as pd
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import orjson
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from dotenv import load_dotenv
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import sqlite3
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from datetime import datetime
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import pytz
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import requests # Add missing import
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load_dotenv()
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api_key = os.getenv('UNUSUAL_WHALES_API_KEY')
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headers = {
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"Accept": "application/json, text/plain",
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"Authorization": api_key
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}
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def save_json(data):
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directory = "json/sector-flow"
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os.makedirs(directory, exist_ok=True) # Ensure the directory exists
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with open(f"{directory}/data.json", 'wb') as file: # Use binary mode for orjson
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file.write(orjson.dumps(data))
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def safe_round(value):
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"""Attempt to convert a value to float and round it. Return the original value if not possible."""
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try:
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return round(float(value), 2)
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except (ValueError, TypeError):
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return value
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def calculate_neutral_premium(data_item):
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"""Calculate the neutral premium for a data item."""
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call_premium = float(data_item['call_premium'])
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put_premium = float(data_item['put_premium'])
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bearish_premium = float(data_item['bearish_premium'])
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bullish_premium = float(data_item['bullish_premium'])
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total_premiums = bearish_premium + bullish_premium
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observed_premiums = call_premium + put_premium
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neutral_premium = observed_premiums - total_premiums
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return safe_round(neutral_premium)
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def get_sector_data():
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try:
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url ="https://api.unusualwhales.com/api/market/sector-etfs"
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response = requests.get(url, headers=headers)
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data = response.json().get('data',[])
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res_list = []
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processed_data = []
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for item in data:
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symbol = item['ticker']
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bearish_premium = float(item['bearish_premium'])
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bullish_premium = float(item['bullish_premium'])
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neutral_premium = calculate_neutral_premium(item)
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new_item = {
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key if key != 'full_name' else 'name': safe_round(value)
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for key, value in item.items()
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if key != 'in_out_flow'
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}
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new_item['premium_ratio'] = [
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safe_round(bearish_premium),
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neutral_premium,
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safe_round(bullish_premium)
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]
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with open(f"json/quote/{symbol}.json") as file:
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quote_data = orjson.loads(file.read())
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new_item['price'] = round(quote_data.get('price',0),2)
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new_item['changesPercentage'] = round(quote_data.get('changesPercentage',0),2)
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processed_data.append(new_item)
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return processed_data
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except Exception as e:
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print(e)
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return []
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def main():
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sector_data = get_sector_data()
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if len(sector_data) > 0:
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save_json(sector_data)
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if __name__ == '__main__':
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main()
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