remove esg endpoints
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MuslemRahimi
parent
7a19524d59
commit
56910ab841
@ -100,17 +100,17 @@ class StockDatabase:
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urls = [
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f"https://financialmodelingprep.com/api/v3/profile/{symbol}?apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/quote/{symbol}?apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/income-statement/{symbol}?period=quarter&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/income-statement-growth/{symbol}?period=quarter&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v4/esg-environmental-social-governance-data-ratings?symbol={symbol}&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v4/esg-environmental-social-governance-data?symbol={symbol}&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/income-statement/{symbol}?period=annual&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/income-statement-growth/{symbol}?period=annual&apikey={api_key}",
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#f"https://financialmodelingprep.com/api/v4/esg-environmental-social-governance-data-ratings?symbol={symbol}&apikey={api_key}",
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#f"https://financialmodelingprep.com/api/v4/esg-environmental-social-governance-data?symbol={symbol}&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_dividend/{symbol}?limit=400&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v4/historical/employee_count?symbol={symbol}&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/balance-sheet-statement/{symbol}?period=quarter&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/balance-sheet-statement-growth/{symbol}?period=quarter&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/cash-flow-statement/{symbol}?period=quarter&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/cash-flow-statement-growth/{symbol}?period=quarter&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/ratios/{symbol}?period=quarter&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/balance-sheet-statement/{symbol}?period=annual&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/balance-sheet-statement-growth/{symbol}?period=annual&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/cash-flow-statement/{symbol}?period=annual&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/cash-flow-statement-growth/{symbol}?period=annual&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/ratios/{symbol}?period=annual&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_split/{symbol}?apikey={api_key}",
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f"https://financialmodelingprep.com/api/v4/stock_peers?symbol={symbol}&apikey={api_key}",
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f"https://financialmodelingprep.com/api/v4/institutional-ownership/institutional-holders/symbol-ownership-percent?date={quarter_date}&symbol={symbol}&page=0&apikey={api_key}",
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@ -124,7 +124,7 @@ class StockDatabase:
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# Check if 'income' and 'income_growth' data already exist for the symbol
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try:
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self.cursor.execute("SELECT income, income_growth, balance, balance_growth, cashflow, cashflow_growth, ratios, stock_peers, esg_data, esg_ratings FROM stocks WHERE symbol = ?", (symbol,))
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self.cursor.execute("SELECT income, income_growth, balance, balance_growth, cashflow, cashflow_growth, ratios, stock_peersFROM stocks WHERE symbol = ?", (symbol,))
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existing_data = self.cursor.fetchone()
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income_exists = existing_data and existing_data[0] is not None
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income_growth_exists = existing_data and existing_data[1] is not None
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@ -176,12 +176,7 @@ class StockDatabase:
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elif 'stock_peers/' in url and stock_peers_exists:
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print(f"Skipping stock_peers for {symbol} as it already exists.")
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continue
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elif 'esg-environmental-social-governance-data' in url and esg_data_exists:
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print(f"Skipping esg_data for {symbol} as it already exists.")
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continue
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elif 'esg-environmental-social-governance-data-ratings?' in url and esg_ratings_exists:
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print(f"Skipping esg_ratings for {symbol} as it already exists.")
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continue
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async with session.get(url) as response:
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@ -284,16 +279,7 @@ class StockDatabase:
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elif isinstance(parsed_data, list) and "cash-flow-statement-growth/" in url:
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# Handle list response, save as JSON object
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fundamental_data['cashflow_growth'] = ujson.dumps(parsed_data)
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elif isinstance(parsed_data, list) and "esg-environmental-social-governance-data?" in url:
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# Handle list response, save as JSON object
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fundamental_data['esg_data'] = ujson.dumps(parsed_data[0])
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data_dict = {'ESGScore': parsed_data[0]['ESGScore']}
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fundamental_data.update(data_dict)
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elif isinstance(parsed_data, list) and "esg-environmental-social-governance-data-ratings?" in url:
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# Handle list response, save as JSON object
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fundamental_data['esg_ratings'] = ujson.dumps(parsed_data[0])
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elif "stock_dividend" in url:
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# Handle list response, save as JSON object
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fundamental_data['stock_dividend'] = ujson.dumps(parsed_data)
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@ -58,16 +58,6 @@ async def get_data(ticker):
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except:
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forward_pe = None
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if data['esg_data'] == None:
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company_esg_score = {'ESGScore': 'n/a', 'socialScore': 'n/a', 'environmentalScore': 'n/a', 'governanceScore': 'n/a'}
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company_esg_rating = {'ESGRiskRating': 'n/a', 'industry': 'n/a'}
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else:
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company_esg_score = ujson.loads(data['esg_data'])
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if data['esg_ratings'] == None:
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company_esg_rating = {'ESGRiskRating': 'n/a', 'industry': 'n/a'}
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else:
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company_esg_rating = ujson.loads(data['esg_ratings'])
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if data['stock_split'] == None:
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company_stock_split = []
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else:
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@ -92,28 +82,12 @@ async def get_data(ticker):
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'previousClose': company_quote['price'], #This is true because I update my db before the market opens hence the price will be the previousClose price.
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'website': company_profile[0]['website'],
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'description': company_profile[0]['description'],
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'esgScore': company_esg_score['ESGScore'],
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'socialScore': company_esg_score['socialScore'],
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'environmentalScore': company_esg_score['environmentalScore'],
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'governanceScore': company_esg_score['governanceScore'],
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'esgRiskRating': company_esg_rating['ESGRiskRating'],
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'fullTimeEmployees': company_profile[0]['fullTimeEmployees'],
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'stockSplits': company_stock_split,
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}
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]
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if data['esg_data'] == None:
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company_esg_score = {'ESGScore': 'n/a', 'socialScore': 'n/a', 'environmentalScore': 'n/a', 'governanceScore': 'n/a'}
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company_esg_rating = {'ESGRiskRating': 'n/a', 'industry': 'n/a'}
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else:
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company_esg_score = ujson.loads(data['esg_data'])
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if data['esg_ratings'] == None:
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company_esg_rating = {'ESGRiskRating': 'n/a', 'industry': 'n/a'}
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else:
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company_esg_rating = ujson.loads(data['esg_ratings'])
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final_res = {k: v for d in [res_profile] for dict in d for k, v in dict.items()}
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return final_res
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@ -56,7 +56,7 @@ async def get_stock_screener(con,symbols):
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#Stock Screener Data
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cursor.execute("SELECT symbol, name, avgVolume, change_1W, change_1M, change_3M, change_6M, change_1Y, change_3Y, sma_50, sma_200, ema_50, ema_200, rsi, atr, stoch_rsi, mfi, cci, priceToSalesRatio, priceToBookRatio, eps, pe, ESGScore, marketCap, revenue, netIncome, grossProfit, costOfRevenue, costAndExpenses, interestIncome, interestExpense, researchAndDevelopmentExpenses, ebitda, operatingExpenses, operatingIncome, growthRevenue, growthNetIncome, growthGrossProfit, growthCostOfRevenue, growthCostAndExpenses, growthInterestExpense, growthResearchAndDevelopmentExpenses, growthEBITDA, growthEPS, growthOperatingExpenses, growthOperatingIncome, beta FROM stocks WHERE eps IS NOT NULL AND revenue IS NOT NULL AND marketCap IS NOT NULL AND beta IS NOT NULL")
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cursor.execute("SELECT symbol, name, avgVolume, change_1W, change_1M, change_3M, change_6M, change_1Y, change_3Y, sma_50, sma_200, ema_50, ema_200, rsi, atr, stoch_rsi, mfi, cci, priceToSalesRatio, priceToBookRatio, eps, pe, marketCap, revenue, netIncome, grossProfit, costOfRevenue, costAndExpenses, interestIncome, interestExpense, researchAndDevelopmentExpenses, ebitda, operatingExpenses, operatingIncome, growthRevenue, growthNetIncome, growthGrossProfit, growthCostOfRevenue, growthCostAndExpenses, growthInterestExpense, growthResearchAndDevelopmentExpenses, growthEBITDA, growthEPS, growthOperatingExpenses, growthOperatingIncome, beta FROM stocks WHERE eps IS NOT NULL AND revenue IS NOT NULL AND marketCap IS NOT NULL AND beta IS NOT NULL")
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raw_data = cursor.fetchall()
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stock_screener_data = [{
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'symbol': symbol,
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@ -81,7 +81,6 @@ async def get_stock_screener(con,symbols):
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'priceToBookRatio': priceToBookRatio,
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'eps': eps,
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'pe': pe,
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'esgScore': ESGScore,
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'marketCap': marketCap,
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'revenue': revenue,
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'netIncome': netIncome,
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@ -106,7 +105,7 @@ async def get_stock_screener(con,symbols):
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'growthOperatingExpenses': growthOperatingExpenses,
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'growthOperatingIncome': growthOperatingIncome,
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'beta': beta,
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} for (symbol, name, avgVolume, change_1W, change_1M, change_3M, change_6M, change_1Y, change_3Y, sma_50, sma_200, ema_50, ema_200, rsi, atr, stoch_rsi, mfi, cci, priceToSalesRatio, priceToBookRatio, eps, pe, ESGScore, marketCap, revenue, netIncome, grossProfit,costOfRevenue, costAndExpenses, interestIncome, interestExpense, researchAndDevelopmentExpenses, ebitda, operatingExpenses, operatingIncome, growthRevenue, growthNetIncome, growthGrossProfit, growthCostOfRevenue, growthCostAndExpenses, growthInterestExpense, growthResearchAndDevelopmentExpenses, growthEBITDA, growthEPS, growthOperatingExpenses, growthOperatingIncome, beta) in raw_data]
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} for (symbol, name, avgVolume, change_1W, change_1M, change_3M, change_6M, change_1Y, change_3Y, sma_50, sma_200, ema_50, ema_200, rsi, atr, stoch_rsi, mfi, cci, priceToSalesRatio, priceToBookRatio, eps, pe, marketCap, revenue, netIncome, grossProfit,costOfRevenue, costAndExpenses, interestIncome, interestExpense, researchAndDevelopmentExpenses, ebitda, operatingExpenses, operatingIncome, growthRevenue, growthNetIncome, growthGrossProfit, growthCostOfRevenue, growthCostAndExpenses, growthInterestExpense, growthResearchAndDevelopmentExpenses, growthEBITDA, growthEPS, growthOperatingExpenses, growthOperatingIncome, beta) in raw_data]
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stock_screener_data = [{k: round(v, 2) if isinstance(v, (int, float)) else v for k, v in entry.items()} for entry in stock_screener_data]
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@ -203,6 +202,9 @@ async def get_stock_screener(con,symbols):
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item['debtEquityRatio'] = round(float(res['debtEquityRatio']),2)
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item['quickRatio'] = round(float(res['quickRatio']),2)
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item['currentRatio'] = round(float(res['currentRatio']),2)
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item['freeCashFlowPerShare'] = round(float(res['freeCashFlowPerShare']),2)
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item['cashPerShare'] = round(float(res['cashPerShare']),2)
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item['priceToFreeCashFlowsRatio'] = round(float(res['priceToFreeCashFlowsRatio']),2)
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except:
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item['returnOnAssets'] = None
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@ -211,6 +213,9 @@ async def get_stock_screener(con,symbols):
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item['debtEquityRatio'] = None
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item['quickRatio'] = None
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item['currentRatio'] = None
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item['freeCashFlowPerShare'] = None
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item['cashPerShare'] = None
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item['priceToFreeCashFlowsRatio'] = None
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return stock_screener_data
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