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update cron job

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This commit is contained in:
MuslemRahimi 2025-01-19 12:09:44 +01:00
parent 91f894a6b6
commit 01d979e094
1 changed files with 64 additions and 55 deletions
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109
app/cron_industry.py
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@ -134,70 +134,79 @@ async def run():
'totalDividendYield': 0.0, 'totalDividendYield': 0.0,
'totalNetIncome': 0.0, 'totalNetIncome': 0.0,
'totalRevenue': 0.0, 'totalRevenue': 0.0,
'totalChange1M': 0.0, 'totalChange1D': 0.0,
'totalChange1Y': 0.0, 'totalChange1Y': 0.0,
'peCount': 0, 'peCount': 0,
'dividendCount': 0, 'dividendCount': 0,
'change1MCount': 0, 'change1DCount': 0,
'change1YCount': 0 'change1YCount': 0
})) }))
# Iterate through stock_screener_data to accumulate values # Iterate through stock_screener_data to accumulate values
for stock in stock_screener_data: for stock in stock_screener_data:
sector = stock.get('sector') try:
industry = stock.get('industry') symbol = stock.get('symbol')
market_cap = stock.get('marketCap') sector = stock.get('sector')
dividend_yield = stock.get('dividendYield') industry = stock.get('industry')
net_income = stock.get('netIncome') market_cap = stock.get('marketCap')
revenue = stock.get('revenue') dividend_yield = stock.get('dividendYield')
change_1_month = stock.get('change1M') net_income = stock.get('netIncome')
change_1_year = stock.get('change1Y') revenue = stock.get('revenue')
with open(f"json/quote/{symbol}.json","r") as file:
quote_data = ujson.load(file)
change_1_day = quote_data.get('changesPercentage',None)
change_1_year = stock.get('change1Y')
# Ensure both sector and industry are valid and that market cap is a valid number # Ensure both sector and industry are valid and that market cap is a valid number
if sector and industry and market_cap is not None: if sector and industry and market_cap is not None:
# Update stock count and accumulate market cap # Update stock count and accumulate market cap
sector_industry_data[sector][industry]['numStocks'] += 1 sector_industry_data[sector][industry]['numStocks'] += 1
sector_industry_data[sector][industry]['totalMarketCap'] += float(market_cap) sector_industry_data[sector][industry]['totalMarketCap'] += float(market_cap)
# Accumulate dividend yield if available # Accumulate dividend yield if available
if dividend_yield is not None: if dividend_yield is not None:
sector_industry_data[sector][industry]['totalDividendYield'] += float(dividend_yield) sector_industry_data[sector][industry]['totalDividendYield'] += float(dividend_yield)
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 net_income is not None and revenue is not None:
sector_industry_data[sector][industry]['totalNetIncome'] += float(net_income) sector_industry_data[sector][industry]['totalNetIncome'] += float(net_income)
sector_industry_data[sector][industry]['totalRevenue'] += float(revenue) sector_industry_data[sector][industry]['totalRevenue'] += float(revenue)
# Accumulate 1-month change if available # Accumulate 1-month change if available
if change_1_month is not None: if change_1_day is not None:
sector_industry_data[sector][industry]['totalChange1M'] += float(change_1_month) sector_industry_data[sector][industry]['totalChange1D'] += float(change_1_day)
sector_industry_data[sector][industry]['change1MCount'] += 1 sector_industry_data[sector][industry]['change1DCount'] += 1
# Accumulate 1-year change if available # Accumulate 1-year change if available
if change_1_year is not None: if change_1_year is not None:
sector_industry_data[sector][industry]['totalChange1Y'] += float(change_1_year) sector_industry_data[sector][industry]['totalChange1Y'] += float(change_1_year)
sector_industry_data[sector][industry]['change1YCount'] += 1 sector_industry_data[sector][industry]['change1YCount'] += 1
except Exception as e:
print(e)
# Prepare the final data in the requested format # Prepare the final data in the requested format
overview = {} overview = {}
for sector, industries in sector_industry_data.items(): for sector, industries in sector_industry_data.items():
# Sort industries by stock count in descending order try:
sorted_industries = sorted(industries.items(), key=lambda x: x[1]['numStocks'], reverse=True) # Sort industries by stock count in descending order
sorted_industries = sorted(industries.items(), key=lambda x: x[1]['numStocks'], reverse=True)
# Add sorted industries with averages to the overview for each sector # Add sorted industries with averages to the overview for each sector
overview[sector] = [ overview[sector] = [
{ {
'industry': industry, 'industry': industry,
'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['totalNetIncome'] / data['totalRevenue'])*100,2) if data['totalRevenue'] > 0 else None,
'avgChange1M': round((data['totalChange1M'] / data['change1MCount']),2) if data['change1MCount'] > 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
] ]
except:
pass
# Assign the P/E values from pe_industry to the overview # Assign the P/E values from pe_industry to the overview
async with aiohttp.ClientSession() as session: async with aiohttp.ClientSession() as session:
@ -232,11 +241,11 @@ async def run():
total_dividend_yield = 0 total_dividend_yield = 0
total_net_income = 0 total_net_income = 0
total_revenue = 0 total_revenue = 0
total_change_1m = 0 total_change_1d = 0
total_change_1y = 0 total_change_1y = 0
dividend_count = 0 dividend_count = 0
change_1m_count = 0 change_1d_count = 0
change_1y_count = 0 change_1y_count = 0
for industry, data in industries.items(): for industry, data in industries.items():
@ -245,11 +254,11 @@ async def run():
total_stocks += data['numStocks'] total_stocks += data['numStocks']
total_net_income += data['totalNetIncome'] total_net_income += data['totalNetIncome']
total_revenue += data['totalRevenue'] total_revenue += data['totalRevenue']
total_change_1m += data['totalChange1M'] total_change_1d += data['totalChange1D']
total_change_1y += data['totalChange1Y'] total_change_1y += data['totalChange1Y']
dividend_count += data['dividendCount'] dividend_count += data['dividendCount']
change_1m_count += data['change1MCount'] change_1d_count += data['change1DCount']
change_1y_count += data['change1YCount'] change_1y_count += data['change1YCount']
total_dividend_yield += data['totalDividendYield'] total_dividend_yield += data['totalDividendYield']
@ -260,7 +269,7 @@ async def run():
'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_net_income / total_revenue) * 100, 2) if total_revenue > 0 else None,
'avgChange1M': round((total_change_1m / change_1m_count), 2) if change_1m_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
}) })