def update_db():
user_options = stock_parser()[0]
print("Update Database. ")
db = Database()
# Sectors DB
top_sectors = SectorScrapper.SectorScrapper(URL_SECTOR).summarizer()
# top_sectors = scrap_sectors
db.insert_sectors_table(top_sectors)
# Industry DB
top_industries = IndustryScrapper.IndustryScrapper(
URL_INDUSTRY).summarizer()
# top_industries = scrap_industries
db.insert_industry_table(top_industries)
# TopMarket DB
# top_market = TopMarketScrapper.TopMarketScrapper(URL).summarizer()
db.insert_main_table(top_market)
top_stocks = StockScrapper.main(user_options)
db.insert_valuation_table(top_stocks)
db.insert_metrics_table(top_stocks)
db.insert_balance_sheet_table(top_stocks)
db.insert_price_history_table(top_stocks)
# db.insert_dividends_table(top_stocks)
db.insert_margins_table(top_stocks)
db.insert_income_table(top_stocks)
db.read_from_db('Industry')
print("Done. ")
return db
def main():
"""
Given a URL of the stock market and the url's for each stock imported from TopMarketScrapper.py,
creates a printable DataFrame and financial table for all the stocks.
:return: DF and dict
"""
db = Database()
user_options = stock_parser()
print(
f'{user_options[ARG_SCRAP].title()} Scrapping On {user_options[ARG_TICKER]}...'
)
if user_options[ARG_SCRAP] == 'concise':
scrap_sectors = SectorScrapper.SectorScrapper(URL_SECTOR)
top_sectors = scrap_sectors.summarizer()
dict_sectors = db.dict_sectors(top_sectors)
print('Sectors Summary', top_sectors, sep='\n')
db.insert_sectors_table(top_sectors)
scrap_industries = IndustryScrapper.IndustryScrapper(URL_INDUSTRY)
top_industries = scrap_industries.summarizer()
print('Industry Summary', top_industries, sep='\n')
db.insert_industry_table(top_industries, dict_sectors)
scrap_top = TopMarketScrapper.TopMarketScrapper(URL)
top_stocks = scrap_top.summarizer()
db.insert_main_table(top_stocks, dict_sectors)
print('', 'Stock Summary', top_stocks, sep='\n')
elif user_options[0] == 'expanded':
scrap_sectors = SectorScrapper.SectorScrapper(URL_SECTOR)
top_sectors = scrap_sectors.summarizer()
dict_sectors = db.dict_sectors(top_sectors)
db.insert_sectors_table(top_sectors)
scrap_industries = IndustryScrapper.IndustryScrapper(URL_INDUSTRY)
top_industries = scrap_industries.summarizer()
db.insert_industry_table(top_industries, dict_sectors)
scrap_top = TopMarketScrapper.TopMarketScrapper(URL)
top_stocks = scrap_top.summarizer()
db.insert_main_table(top_stocks, dict_sectors)
ids_list = db.read_from_db('Main')
top_stocks = StockScrapper.main(user_options[ARG_TICKER])
print('Stock Summary', top_stocks, sep='\n')
db.insert_valuation_table(top_stocks, ids_list)
db.insert_metrics_table(top_stocks, ids_list)
db.insert_balance_sheet_table(top_stocks, ids_list)
db.insert_price_history_table(top_stocks, ids_list)
db.insert_dividends_table(top_stocks, ids_list)
db.insert_margins_table(top_stocks, ids_list)
db.insert_income_table(top_stocks, ids_list)
api_overview = API_Scrapper.api_overview(user_options[ARG_TICKER])
db.insert_api_table(api_overview, ids_list)
db.close_connect_db()
def main():
"""
Given a URL of the stock market and the url's for each stock imported from TopMarketScrapper.py,
creates a printable DataFrame and financial table for all the stocks.
:return: DF and dict
"""
db = Database()
user_options = stock_parser()
print(user_options[0])
print(user_options[1])
if user_options[0] == 'concise':
# # printing info to console and file
# scrap_industries = IndustryScrapper.IndustryScrapper(URL_INDUSTRY)
# top_industries = scrap_industries.summarizer()
# print('Industry Summary', top_industries, sep='\n')
# db.insert_industry_table(top_industries)
# # printing info to console and file
#
scrap_sectors = SectorScrapper.SectorScrapper(URL_SECTOR)
top_sectors = scrap_sectors.summarizer()
print('Sectors Summary', top_sectors, sep='\n')
db.insert_sectors_table(top_sectors)
#
# # Stock financial in depth info
# getting urls for individual stock and sectors mining
scrap_top = TopMarketScrapper.TopMarketScrapper(URL)
stock, sectors = scrap_top.get_urls()
# print('Links to Stocks and Sectors:', stock, sectors, sep='\n')
# printing info to console and file
top_stocks = scrap_top.summarizer()
print('', 'Stock Summary', top_stocks, sep='\n')
db.insert_main_table(top_stocks)
print(db.read_from_db('Main'))
elif user_options[0] == 'expanded':
scrap_sectors = SectorScrapper.SectorScrapper(URL_SECTOR)
top_sectors = scrap_sectors.summarizer()
dict_sectors = db.dict_sectors(top_sectors)
print(dict_sectors)
db.insert_sectors_table(top_sectors)
scrap_industries = IndustryScrapper.IndustryScrapper(URL_INDUSTRY)
top_industries = scrap_industries.summarizer()
db.insert_industry_table(top_industries, dict_sectors)
scrap_top = TopMarketScrapper.TopMarketScrapper(URL)
top_stocks = scrap_top.summarizer()
db.insert_main_table(top_stocks, dict_sectors)
ids_list = db.read_from_db('Main')
top_stocks = StockScrapper.main(user_options[1])
print('Stock Summary', top_stocks, sep='\n')
db.insert_valuation_table(top_stocks, ids_list)
db.insert_metrics_table(top_stocks, ids_list)
db.insert_balance_sheet_table(top_stocks, ids_list)
db.insert_price_history_table(top_stocks, ids_list)
db.insert_dividends_table(top_stocks, ids_list)
db.insert_margins_table(top_stocks, ids_list)
db.insert_income_table(top_stocks, ids_list)
api_overview = API_Scrapper.api_overview(user_options[1])
db.insert_api_table(api_overview, ids_list)
db.close_connect_db()