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update cron job

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This commit is contained in:
MuslemRahimi 2025-01-19 12:24:23 +01:00
parent 01d979e094
commit f91e901c82
1 changed files with 14 additions and 14 deletions
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28
app/cron_industry.py
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@ -132,14 +132,14 @@ async def run():
'numStocks': 0, 'numStocks': 0,
'totalMarketCap': 0.0, 'totalMarketCap': 0.0,
'totalDividendYield': 0.0, 'totalDividendYield': 0.0,
'totalNetIncome': 0.0, 'totalProfitMargin': 0.0,
'totalRevenue': 0.0,
'totalChange1D': 0.0, 'totalChange1D': 0.0,
'totalChange1Y': 0.0, 'totalChange1Y': 0.0,
'peCount': 0, 'peCount': 0,
'dividendCount': 0, 'dividendCount': 0,
'change1DCount': 0, 'change1DCount': 0,
'change1YCount': 0 'change1YCount': 0,
'profitMarginCount': 0,
})) }))
# Iterate through stock_screener_data to accumulate values # Iterate through stock_screener_data to accumulate values
@ -150,8 +150,8 @@ async def run():
industry = stock.get('industry') industry = stock.get('industry')
market_cap = stock.get('marketCap') market_cap = stock.get('marketCap')
dividend_yield = stock.get('dividendYield') dividend_yield = stock.get('dividendYield')
net_income = stock.get('netIncome') profit_margin = stock.get('netProfitMargin')
revenue = stock.get('revenue')
with open(f"json/quote/{symbol}.json","r") as file: with open(f"json/quote/{symbol}.json","r") as file:
quote_data = ujson.load(file) quote_data = ujson.load(file)
change_1_day = quote_data.get('changesPercentage',None) change_1_day = quote_data.get('changesPercentage',None)
@ -169,9 +169,9 @@ async def run():
sector_industry_data[sector][industry]['dividendCount'] += 1 sector_industry_data[sector][industry]['dividendCount'] += 1
# Accumulate net income and revenue for profit margin calculation # Accumulate net income and revenue for profit margin calculation
if net_income is not None and revenue is not None: if profit_margin is not None and profit_margin < 100 and profit_margin > -100:
sector_industry_data[sector][industry]['totalNetIncome'] += float(net_income) sector_industry_data[sector][industry]['totalProfitMargin'] += float(profit_margin)
sector_industry_data[sector][industry]['totalRevenue'] += float(revenue) sector_industry_data[sector][industry]['profitMarginCount'] += 1
# Accumulate 1-month change if available # Accumulate 1-month change if available
if change_1_day is not None: if change_1_day is not None:
@ -200,7 +200,7 @@ async def run():
'numStocks': data['numStocks'], 'numStocks': data['numStocks'],
'totalMarketCap': data['totalMarketCap'], 'totalMarketCap': data['totalMarketCap'],
'avgDividendYield': round((data['totalDividendYield'] / data['dividendCount']),2) if data['dividendCount'] > 0 else None, 'avgDividendYield': round((data['totalDividendYield'] / data['dividendCount']),2) if data['dividendCount'] > 0 else None,
'profitMargin': round((data['totalNetIncome'] / data['totalRevenue'])*100,2) if data['totalRevenue'] > 0 else None, 'profitMargin': round((data['totalProfitMargin'] / data['profitMarginCount']),2) if data['profitMarginCount'] > 0 else None,
'avgChange1D': round((data['totalChange1D'] / data['change1DCount']),2) if data['change1DCount'] > 0 else None, 'avgChange1D': round((data['totalChange1D'] / data['change1DCount']),2) if data['change1DCount'] > 0 else None,
'avgChange1Y': round((data['totalChange1Y'] / data['change1YCount']),2) if data['change1YCount'] > 0 else None 'avgChange1Y': round((data['totalChange1Y'] / data['change1YCount']),2) if data['change1YCount'] > 0 else None
} for industry, data in sorted_industries } for industry, data in sorted_industries
@ -239,27 +239,27 @@ async def run():
total_market_cap = 0 total_market_cap = 0
total_stocks = 0 total_stocks = 0
total_dividend_yield = 0 total_dividend_yield = 0
total_net_income = 0 total_profit_margin = 0
total_revenue = 0
total_change_1d = 0 total_change_1d = 0
total_change_1y = 0 total_change_1y = 0
dividend_count = 0 dividend_count = 0
change_1d_count = 0 change_1d_count = 0
change_1y_count = 0 change_1y_count = 0
profit_margin_count = 0
for industry, data in industries.items(): for industry, data in industries.items():
# Sum up values across industries for the sector summary # Sum up values across industries for the sector summary
total_market_cap += data['totalMarketCap'] total_market_cap += data['totalMarketCap']
total_stocks += data['numStocks'] total_stocks += data['numStocks']
total_net_income += data['totalNetIncome'] total_profit_margin += data['totalProfitMargin']
total_revenue += data['totalRevenue']
total_change_1d += data['totalChange1D'] total_change_1d += data['totalChange1D']
total_change_1y += data['totalChange1Y'] total_change_1y += data['totalChange1Y']
dividend_count += data['dividendCount'] dividend_count += data['dividendCount']
change_1d_count += data['change1DCount'] change_1d_count += data['change1DCount']
change_1y_count += data['change1YCount'] change_1y_count += data['change1YCount']
profit_margin_count += data['profitMarginCount']
total_dividend_yield += data['totalDividendYield'] total_dividend_yield += data['totalDividendYield']
# Calculate averages and profit margin for the sector # Calculate averages and profit margin for the sector
@ -268,7 +268,7 @@ async def run():
'numStocks': total_stocks, 'numStocks': total_stocks,
'totalMarketCap': total_market_cap, 'totalMarketCap': total_market_cap,
'avgDividendYield': round((total_dividend_yield / dividend_count), 2) if dividend_count > 0 else None, 'avgDividendYield': round((total_dividend_yield / dividend_count), 2) if dividend_count > 0 else None,
'profitMargin': round((total_net_income / total_revenue) * 100, 2) if total_revenue > 0 else None, 'profitMargin': round((total_profit_margin / profit_margin_count), 2) if profit_margin_count > 0 else None,
'avgChange1D': round((total_change_1d / change_1d_count), 2) if change_1d_count > 0 else None, 'avgChange1D': round((total_change_1d / change_1d_count), 2) if change_1d_count > 0 else None,
'avgChange1Y': round((total_change_1y / change_1y_count), 2) if change_1y_count > 0 else None 'avgChange1Y': round((total_change_1y / change_1y_count), 2) if change_1y_count > 0 else None
}) })