backend/app/cron_list.py
2024-10-29 22:33:13 +01:00

133 lines
6.3 KiB
Python

import orjson
import sqlite3
import asyncio
import aiohttp
from tqdm import tqdm
# Load stock screener data
with open(f"json/stock-screener/data.json", 'rb') as file:
stock_screener_data = orjson.loads(file.read())
stock_screener_data_dict = {item['symbol']: item for item in stock_screener_data}
async def save_json(category, data, category_type='market-cap'):
with open(f"json/{category_type}/list/{category}.json", 'wb') as file:
file.write(orjson.dumps(data))
async def get_quote_data(symbol):
"""Get quote data for a symbol from JSON file"""
try:
with open(f"json/quote/{symbol}.json", 'r') as file:
return orjson.loads(file.read())
except FileNotFoundError:
return None
async def process_category(cursor, category, condition, category_type='market-cap'):
"""
Process stocks for a specific category (market cap or sector)
Args:
cursor: Database cursor
category: Category name
condition: SQL WHERE condition
category_type: Either 'market-cap' or 'sector'
"""
base_query = """
SELECT DISTINCT s.symbol, s.name, s.exchangeShortName, s.marketCap, s.sector
FROM stocks s
WHERE {}
"""
full_query = base_query.format(condition)
cursor.execute(full_query)
raw_data = cursor.fetchall()
result_list = []
for row in raw_data:
symbol = row[0]
quote_data = await get_quote_data(symbol)
if quote_data:
item = {
'symbol': symbol,
'name': row[1],
'price': round(quote_data.get('price'),2),
'changesPercentage': round(quote_data.get('changesPercentage'),2),
'marketCap': quote_data.get('marketCap'),
'sector': row[4], # Include sector information
'revenue': None,
}
# Add screener data if available
if symbol in stock_screener_data_dict:
item['revenue'] = stock_screener_data_dict[symbol].get('revenue')
if item['marketCap'] > 0:
result_list.append(item)
# Sort by market cap and save
sorted_result = sorted(result_list, key=lambda x: x['marketCap'] if x['marketCap'] else 0, reverse=True)
# Add rank to each item
for rank, item in enumerate(sorted_result, 1):
item['rank'] = rank
await save_json(category, sorted_result, category_type)
print(f"Processed and saved {len(sorted_result)} stocks for {category}")
return sorted_result
async def run():
"""Main function to run the analysis for all categories"""
market_cap_conditions = {
'mega-cap-stocks': "marketCap >= 200e9 AND (exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX')",
'large-cap-stocks': "marketCap < 200e9 AND marketCap >= 10e9 AND (exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX')",
'mid-cap-stocks': "marketCap < 10e9 AND marketCap >= 2e9 AND (exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX')",
'small-cap-stocks': "marketCap < 2e9 AND marketCap >= 300e6 AND (exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX')",
'micro-cap-stocks': "marketCap < 300e6 AND marketCap >= 50e6 AND (exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX')",
'nano-cap-stocks': "marketCap < 50e6 AND (exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX')"
}
sector_conditions = {
'financial': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Financials' OR sector = 'Financial Services')",
'healthcare': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Healthcare')",
'technology': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Technology')",
'industrials': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Industrials')",
'consumer-cyclical': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Consumer Cyclical')",
'real-estate': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Real Estate')",
'basic-materials': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Basic Materials')",
'communication-services': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Communication Services')",
'energy': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Energy')",
'consumer-defensive': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Consumer Defensive')",
'utilities': "(exchangeShortName = 'NYSE' OR exchangeShortName = 'NASDAQ' OR exchangeShortName = 'AMEX') AND (sector = 'Utilities')"
}
try:
con = sqlite3.connect('stocks.db')
cursor = con.cursor()
cursor.execute("PRAGMA journal_mode = wal")
# Process market cap categories
for category, condition in market_cap_conditions.items():
await process_category(cursor, category, condition, 'market-cap')
await asyncio.sleep(1) # Small delay between categories
# Process sector categories
for category, condition in sector_conditions.items():
await process_category(cursor, category, condition, 'sector')
await asyncio.sleep(1) # Small delay between categories
except Exception as e:
print(e)
raise
finally:
con.close()
if __name__ == "__main__":
try:
loop = asyncio.get_event_loop()
loop.run_until_complete(run())
except Exception as e:
print(e)
finally:
loop.close()