update cron job
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MuslemRahimi
parent
91f894a6b6
commit
01d979e094
@ -134,70 +134,79 @@ async def run():
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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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'totalChange1M': 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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'change1MCount': 0,
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'change1DCount': 0,
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'change1YCount': 0
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}))
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# Iterate through stock_screener_data to accumulate values
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for stock in stock_screener_data:
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sector = stock.get('sector')
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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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change_1_month = stock.get('change1M')
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change_1_year = stock.get('change1Y')
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# Ensure both sector and industry are valid and that market cap is a valid number
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if sector and industry and market_cap is not None:
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# Update stock count and accumulate market cap
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sector_industry_data[sector][industry]['numStocks'] += 1
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sector_industry_data[sector][industry]['totalMarketCap'] += float(market_cap)
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try:
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symbol = stock.get('symbol')
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sector = stock.get('sector')
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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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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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change_1_year = stock.get('change1Y')
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# Accumulate dividend yield if available
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if dividend_yield is not None:
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sector_industry_data[sector][industry]['totalDividendYield'] += float(dividend_yield)
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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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# Accumulate 1-month change if available
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if change_1_month is not None:
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sector_industry_data[sector][industry]['totalChange1M'] += float(change_1_month)
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sector_industry_data[sector][industry]['change1MCount'] += 1
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# Accumulate 1-year change if available
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if change_1_year is not None:
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sector_industry_data[sector][industry]['totalChange1Y'] += float(change_1_year)
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sector_industry_data[sector][industry]['change1YCount'] += 1
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# Ensure both sector and industry are valid and that market cap is a valid number
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if sector and industry and market_cap is not None:
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# Update stock count and accumulate market cap
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sector_industry_data[sector][industry]['numStocks'] += 1
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sector_industry_data[sector][industry]['totalMarketCap'] += float(market_cap)
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# Accumulate dividend yield if available
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if dividend_yield is not None:
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sector_industry_data[sector][industry]['totalDividendYield'] += float(dividend_yield)
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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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# Accumulate 1-month change if available
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if change_1_day is not None:
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sector_industry_data[sector][industry]['totalChange1D'] += float(change_1_day)
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sector_industry_data[sector][industry]['change1DCount'] += 1
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# Accumulate 1-year change if available
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if change_1_year is not None:
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sector_industry_data[sector][industry]['totalChange1Y'] += float(change_1_year)
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sector_industry_data[sector][industry]['change1YCount'] += 1
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except Exception as e:
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print(e)
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# Prepare the final data in the requested format
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overview = {}
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for sector, industries in sector_industry_data.items():
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# Sort industries by stock count in descending order
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sorted_industries = sorted(industries.items(), key=lambda x: x[1]['numStocks'], reverse=True)
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# Add sorted industries with averages to the overview for each sector
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overview[sector] = [
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{
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'industry': industry,
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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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'avgChange1M': round((data['totalChange1M'] / data['change1MCount']),2) if data['change1MCount'] > 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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]
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try:
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# Sort industries by stock count in descending order
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sorted_industries = sorted(industries.items(), key=lambda x: x[1]['numStocks'], reverse=True)
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# Add sorted industries with averages to the overview for each sector
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overview[sector] = [
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{
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'industry': industry,
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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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'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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]
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except:
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pass
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# Assign the P/E values from pe_industry to the overview
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async with aiohttp.ClientSession() as session:
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@ -232,11 +241,11 @@ async def run():
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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_change_1m = 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_1m_count = 0
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change_1d_count = 0
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change_1y_count = 0
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for industry, data in industries.items():
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@ -245,11 +254,11 @@ async def run():
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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_change_1m += data['totalChange1M']
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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_1m_count += data['change1MCount']
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change_1d_count += data['change1DCount']
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change_1y_count += data['change1YCount']
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total_dividend_yield += data['totalDividendYield']
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@ -260,7 +269,7 @@ async def run():
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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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'avgChange1M': round((total_change_1m / change_1m_count), 2) if change_1m_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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