def get_allsymbol_items():
df, msg = usstock.get_symbols()
if df.empty:
print("Symbol list data empty.")
return None
else:
data_list = []
for i in range(0, len(df)):
astk = stock.Usstock_item()
astk.symbol = str(df.iat[i, 0])
astk.name = str(df.iat[i, 1])
astk.last_sale = str(df.iat[i, 2])
astk.market_cap = str(df.iat[i, 3])
astk.ipo_year = str(df.iat[i, 4])
astk.sector = str(df.iat[i, 5])
astk.industry = str(df.iat[i, 6])
astk.sum_quote = str(df.iat[i, 7])
data_list.append(astk)
return data_list
def usstock_get_symbols():
df, msg = usstock.get_symbols()
return df.to_json(orient='table')
else:
return None
start = datetime.now()
info_table = 'us_stocks_info'
# 更新 标普500 权重股
spx_columns = ['code', 'name', 'is_spx', 'sp_sector']
mydb.upsert_table(info_table, spx_columns, us.get_spx())
spx2_columns = ['code', 'name', 'spx_weight']
mydb.upsert_table(info_table, spx2_columns, us.get_spx2())
# 更新 纳斯达克100 权重股
ndx_columns = ['code', 'name', 'is_ndx', 'ndx_weight']
mydb.upsert_table(info_table, ndx_columns, us.get_ndx())
# 更新 道琼斯 权重股
dji_columns = ['code', 'name', 'is_dji', 'dji_weight']
mydb.upsert_table(info_table, dji_columns, us.get_dji())
# 全美股市场股票
symbols, msg = usstock.get_symbols()
if symbols is not None:
columns = ['code', 'name', 'sector', 'industry', 'total_cap']
symbols.rename(columns={'Symbol': 'code', 'Name': 'name', 'Sector': 'sector', 'MarketCap': 'total_cap'},
inplace=True)
symbols = symbols[columns].set_index(['code']).drop_duplicates().reset_index()
symbols.total_cap = symbols.total_cap.map(us_total_cap)
mydb.upsert_table(info_table, columns, symbols)
end = datetime.now()
print('Download Data use {}'.format(end - start))