update cron job
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01d979e094
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@ -132,14 +132,14 @@ async def run():
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'numStocks': 0,
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'totalMarketCap': 0.0,
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'totalDividendYield': 0.0,
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'totalNetIncome': 0.0,
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'totalRevenue': 0.0,
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'totalProfitMargin': 0.0,
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'totalChange1D': 0.0,
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'totalChange1Y': 0.0,
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'peCount': 0,
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'dividendCount': 0,
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'change1DCount': 0,
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'change1YCount': 0
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'change1YCount': 0,
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'profitMarginCount': 0,
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}))
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# Iterate through stock_screener_data to accumulate values
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@ -150,8 +150,8 @@ async def run():
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industry = stock.get('industry')
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market_cap = stock.get('marketCap')
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dividend_yield = stock.get('dividendYield')
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net_income = stock.get('netIncome')
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revenue = stock.get('revenue')
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profit_margin = stock.get('netProfitMargin')
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with open(f"json/quote/{symbol}.json","r") as file:
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quote_data = ujson.load(file)
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change_1_day = quote_data.get('changesPercentage',None)
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@ -169,9 +169,9 @@ async def run():
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sector_industry_data[sector][industry]['dividendCount'] += 1
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# Accumulate net income and revenue for profit margin calculation
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if net_income is not None and revenue is not None:
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sector_industry_data[sector][industry]['totalNetIncome'] += float(net_income)
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sector_industry_data[sector][industry]['totalRevenue'] += float(revenue)
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if profit_margin is not None and profit_margin < 100 and profit_margin > -100:
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sector_industry_data[sector][industry]['totalProfitMargin'] += float(profit_margin)
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sector_industry_data[sector][industry]['profitMarginCount'] += 1
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# Accumulate 1-month change if available
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if change_1_day is not None:
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@ -200,7 +200,7 @@ async def run():
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'numStocks': data['numStocks'],
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'totalMarketCap': data['totalMarketCap'],
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'avgDividendYield': round((data['totalDividendYield'] / data['dividendCount']),2) if data['dividendCount'] > 0 else None,
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'profitMargin': round((data['totalNetIncome'] / data['totalRevenue'])*100,2) if data['totalRevenue'] > 0 else None,
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'profitMargin': round((data['totalProfitMargin'] / data['profitMarginCount']),2) if data['profitMarginCount'] > 0 else None,
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'avgChange1D': round((data['totalChange1D'] / data['change1DCount']),2) if data['change1DCount'] > 0 else None,
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'avgChange1Y': round((data['totalChange1Y'] / data['change1YCount']),2) if data['change1YCount'] > 0 else None
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} for industry, data in sorted_industries
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@ -239,27 +239,27 @@ async def run():
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total_market_cap = 0
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total_stocks = 0
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total_dividend_yield = 0
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total_net_income = 0
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total_revenue = 0
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total_profit_margin = 0
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total_change_1d = 0
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total_change_1y = 0
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dividend_count = 0
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change_1d_count = 0
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change_1y_count = 0
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profit_margin_count = 0
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for industry, data in industries.items():
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# Sum up values across industries for the sector summary
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total_market_cap += data['totalMarketCap']
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total_stocks += data['numStocks']
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total_net_income += data['totalNetIncome']
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total_revenue += data['totalRevenue']
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total_profit_margin += data['totalProfitMargin']
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total_change_1d += data['totalChange1D']
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total_change_1y += data['totalChange1Y']
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dividend_count += data['dividendCount']
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change_1d_count += data['change1DCount']
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change_1y_count += data['change1YCount']
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profit_margin_count += data['profitMarginCount']
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total_dividend_yield += data['totalDividendYield']
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# Calculate averages and profit margin for the sector
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@ -268,7 +268,7 @@ async def run():
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'numStocks': total_stocks,
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'totalMarketCap': total_market_cap,
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'avgDividendYield': round((total_dividend_yield / dividend_count), 2) if dividend_count > 0 else None,
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'profitMargin': round((total_net_income / total_revenue) * 100, 2) if total_revenue > 0 else None,
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'profitMargin': round((total_profit_margin / profit_margin_count), 2) if profit_margin_count > 0 else None,
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'avgChange1D': round((total_change_1d / change_1d_count), 2) if change_1d_count > 0 else None,
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'avgChange1Y': round((total_change_1y / change_1y_count), 2) if change_1y_count > 0 else None
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})
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