def _build_index(self):
def with_index(df, type, column, new_name="symbol"):
if not "country" in df:
df["country"] = "unknown"
else:
df["country"] = df["country"].replace({
None: "unknown",
"": "unknown"
}).fillna('unknown')
df.index = pd.MultiIndex.from_tuples([
(s, type, c)
for s, c in zip(df[column].to_list(), df["country"].to_list())
]).rename([
new_name if new_name is not None else column, "type", "country"
])
df = df.drop([column, "country"], axis=1)
df = df.drop(df.index[df.index.duplicated('first')], axis=0)
return df.loc[df.index.dropna()]
symbols_df = pd.concat(
[
with_index(ip.get_bonds(), "BOND",
"name"), # country "name" full_name
with_index(
ip.get_certificates(), "CERT", "symbol"
), # country', 'name', 'full_name', '"symbol"', 'issuer', 'isin', 'asset_class', 'underlying'
with_index(ip.get_cryptos(), "CRYPTO",
"symbol"), # 'name', '"symbol"', 'currency'
with_index(
ip.get_commodities(), "COMM", "name"
), # 'title', 'country', '"name"', 'full_name', 'currency', 'group'
with_index(
ip.get_etfs(), "ETF", "symbol"
), # 'country', 'name', 'full_name', '"symbol"', 'isin', 'asset_class', 'currency', 'stock_exchange', 'def_stock_exchange'
# with_index(ip.get_funds(), "FUND", "isin"), # 'country', 'name', 'symbol', 'issuer', '"isin"', 'asset_class', 'currency', 'underlying'
with_index(
ip.get_indices(), "INDEX", "symbol"
), # 'country', 'name', 'full_name', '"symbol"', 'currency', 'class', 'market'
with_index(
ip.get_stocks(), "STOCK", "symbol"
), # ['country', 'name', 'full_name', 'isin', 'currency', '"symbol"'
with_index(
pd.DataFrame(
[f'{c}/USD' for c in ip.get_available_currencies()],
columns=['symbol']), "FX", "symbol")
],
axis=0)
# update the index table
upsert(self.engine,
symbols_df,
DataProvider.symbols_table_name,
if_row_exists='ignore')
def get_cryptos():
# function to get dictionary of crypto available at Investing
try:
tickers_df = investpy.get_cryptos()
except:
tickers_df = pd.DataFrame(data=dict(name=['No results'], symbol=['No results']) )
# extract names and symbols
tickers_df.loc[:, 'name'] = tickers_df.loc[:, 'name'].apply(lambda x: x.strip('u200b') )
labels= [', '.join(i) for i in tickers_df.loc[:, ['name','symbol']].values]
values = tickers_df.loc[:, ['symbol']].values.T[0]
tickers_dict = [{'label':i, 'value':j.split(',')[0]} for i,j in zip(labels, labels)]
return tickers_dict
def test_investpy_cryptos():
"""
This function checks that crypto currencies data retrieval functions listed in investpy work properly.
"""
investpy.get_cryptos()
investpy.get_cryptos_list()
params = [
{
'columns': None,
'as_json': False
},
{
'columns': ['name', 'symbol', 'currency'],
'as_json': False
},
{
'columns': None,
'as_json': True
},
]
for param in params:
investpy.get_cryptos_dict(columns=param['columns'],
as_json=param['as_json'])
params = [
{
'as_json': True,
'order': 'ascending',
},
{
'as_json': False,
'order': 'ascending',
},
{
'as_json': True,
'order': 'descending',
},
{
'as_json': False,
'order': 'descending',
},
]
for param in params:
investpy.get_crypto_recent_data(crypto='bitcoin',
as_json=param['as_json'],
order=param['order'],
interval='Daily')
investpy.get_crypto_historical_data(crypto='bitcoin',
from_date='01/01/1990',
to_date='01/01/2019',
as_json=param['as_json'],
order=param['order'],
interval='Daily')
params = [
{
'crypto': 'bitcoin',
'as_json': False
},
{
'crypto': 'bitcoin',
'as_json': True
}
]
for param in params:
investpy.get_crypto_information(crypto=param['crypto'], as_json=param['as_json'])
params = [
{
'as_json': False,
'n_results': 10
},
{
'as_json': True,
'n_results': 10
},
{
'as_json': False,
'n_results': 110
},
{
'as_json': True,
'n_results': 110
},
{
'as_json': False,
'n_results': None
},
{
'as_json': True,
'n_results': None
},
]
for param in params:
investpy.get_cryptos_overview(as_json=param['as_json'], n_results=param['n_results'])
investpy.search_cryptos(by='name', value='bitcoin')
interval='Daily')
investpy_bitcoin.to_pickle('./Market_Watch_Data/investpy_bitcoin.pkl')
investpy_Ethereum = investpy.get_crypto_historical_data(crypto='Ethereum',
from_date="30/01/1900",
to_date=DD_END_DATE,
interval='Daily')
investpy_Ethereum.to_pickle('./Market_Watch_Data/investpy_Ethereum.pkl')
investpy_Ripple = investpy.get_crypto_historical_data(crypto='XRP',
from_date="30/01/1900",
to_date=DD_END_DATE,
interval='Daily')
investpy_Ripple.to_pickle('./Market_Watch_Data/investpy_Ripple.pkl')
df_cryptos = investpy.get_cryptos()
########################################################################################################################
# investpy 패키지를 사용하여 삼성전자 자료 받기
investpy_005930 = investpy.get_stock_historical_data(stock="005930",
country="south korea",
from_date="30/01/1900",
to_date=DD_END_DATE)
investpy_005930.to_pickle('./Market_Watch_Data/investpy_005930.pkl')
########################################################################################################################
# investpy 패키지를 사용하여 ETF 자료 받기 (069500)
investpy_069500 = investpy.get_etf_historical_data(
etf="Samsung KODEX KOSPI 200 Securities",
country="south korea",
from_date="30/01/1900",