def forex(API_key, fromCurr, toCurr):
from alpha_vantage.foreignexchange import ForeignExchange
import matplotlib.pyplot as plt
fe=ForeignExchange(key=API_key,output_format='pandas')
option=input('1. Exchange Rates\n2. Intraday\n3. Daily\n4. Weekly\n5. Monthly\n').lower()
if option=='exchange rates' or option=='1':
data=fe.get_currency_exchange_rate(from_currency=fromCurr, to_currency=toCurr)[0]
return data
elif option=='intraday' or option=='2':
interval=int(input("Enter Interval:\n\t1. 1 minute\n\t2. 5 minutes\n\t3. 15 minutes\n\t4. 30 minutes\n\t5. 60 minutes\n"))
intervalList=['','1min','5min','15min','30min','60min']
data=fe.get_currency_exchange_intraday(from_symbol=fromCurr, to_symbol=toCurr,interval=intervalList[interval])[0]
data.plot()
plt.title(f'Forex Intraday for the {fromCurr}-{toCurr} stock ({intervalList[interval]})')
plt.tight_layout()
plt.grid()
plt.show()
return data
elif option=='daily' or option=='3':
data=fe.get_currency_exchange_daily(from_symbol=fromCurr, to_symbol=toCurr)[0]
data.plot()
plt.title(f'Forex Daily for the {fromCurr}-{toCurr} stock')
plt.tight_layout()
plt.grid()
plt.show()
return data
elif option=='weekly' or option=='4':
data=fe.get_currency_exchange_weekly(from_symbol=fromCurr, to_symbol=toCurr)[0]
data.plot()
plt.title(f'Forex Weekly for the {fromCurr}-{toCurr} stock')
plt.tight_layout()
plt.grid()
plt.show()
return data
elif option=='monthly' or option=='5':
data=fe.get_currency_exchange_monthly(from_symbol=fromCurr, to_symbol=toCurr)[0]
data.plot()
plt.title(f'Forex Monthly for the {fromCurr}-{toCurr} stock')
plt.tight_layout()
plt.grid()
plt.show()
return data
else:
print("DATA NOT AVAILABLE")
class AlphaVantageFOREXClient:
def __init__(self, api_key=None):
if api_key is None:
default_api_key = utils.get_api_key('AlphaVantage')
if default_api_key is None:
raise ValueError('No AlphaVantage API Key found.')
else:
self.ts = ForeignExchange(key=default_api_key,
output_format='pandas')
else:
self.ts = ForeignExchange(key=api_key, output_format='pandas')
def get_data(self,
from_currency,
to_currency,
freq='daily',
interval='15min',
outputsize='full'):
""" Return time series in pandas formet.
Keyword Arguments:
from_currency: The currency you would like to get the exchange rate
for. It can either be a physical currency or digital/crypto currency.
to_currency: The destination currency for the exchange rate.
It can either be a physical currency or digital/crypto currency.
freq: frequency of data, supported values are 'daily', 'weekly', 'monthly' (default 'daily'). Currently not support for 'intraday'
interval: time interval between two conscutive values, used when freq is intraday
supported values are '1min', '5min', '15min', '30min', '60min'
(default '15min')
outputsize: The size of the call, supported values are
'compact' and 'full; the first returns the last 100 points in the
data series, and 'full' returns the full-length intraday times
series, commonly above 1MB (default 'compact')
"""
# if freq == 'intraday':
# data, _ = self.ts.get_currency_exchange_intraday(from_symbol=from_currency, to_symbol=to_currency, interval=interval, outputsize=outputsize)
if freq == 'daily':
data, _ = self.ts.get_currency_exchange_daily(
from_symbol=from_currency,
to_symbol=to_currency,
outputsize=outputsize)
elif freq == 'weekly':
data, _ = self.ts.get_currency_exchange_weekly(
from_symbol=from_currency,
to_symbol=to_currency,
outputsize=outputsize)
elif freq == 'monthly':
data, _ = self.ts.get_currency_exchange_monthly(
from_symbol=from_currency,
to_symbol=to_currency,
outputsize=outputsize)
else:
raise Warning('Freq: {} is not valid. Default to Daily.')
data, _ = self.ts.get_currency_exchange_daily(
from_symbol=from_currency,
to_symbol=to_currency,
outputsize=outputsize)
data.columns = ['Open', 'High', 'Low', 'Close']
data = data.rename(index={'date': 'Date'})
return data.sort_index(ascending=True)
def get_latest_data(self, from_currency, to_currency):
""" Return the latest price and volume information for a exchange of your choice
Keyword Arguments:
from_currency: The currency you would like to get the exchange rate
for. It can either be a physical currency or digital/crypto currency.
to_currency: The destination currency for the exchange rate.
It can either be a physical currency or digital/crypto currency.
"""
data, _ = self.ts.get_currency_exchange_rate(
from_currency=from_currency, to_currency=to_currency)
data = data.iloc[:, [0, 2, 4, 5, 7, 8]]
columns_name = ['From', 'To', 'Rate', 'Date', 'Bid', 'Ask']
data.columns = columns_name
data = data.set_index(['Date'])
return data
class REST(object):
def __init__(self, api_key):
self._api_key = get_alpha_vantage_credentials(api_key)
self._session = requests.Session()
self._timeseries = TimeSeries(key=self._api_key)
self._cryptocurrencies = CryptoCurrencies(key=self._api_key)
self._foreignexchange = ForeignExchange(key=self._api_key)
self._sectorperformance = SectorPerformances(key=self._api_key)
self._techindicators = TechIndicators(key=self._api_key)
def _request(self, method, params=None):
url = 'https://www.alphavantage.co/query?'
params = params or {}
params['apikey'] = self._api_key
resp = self._session.request(method, url, params=params)
resp.raise_for_status()
return resp.json()
def get(self, params=None):
''' Customizable endpoint, where you can pass all
keywords/paramters from the documentation:
https://www.alphavantage.co/documentation/#
Returns:
pandas, csv, or json
'''
return self._request('GET', params=params)
def historic_quotes(self, symbol, adjusted=False, outputsize='full', cadence='daily', output_format=None):
''' Returns the one of the TIME_SERIES_* endpoints of the Alpha Vantage API.
Params:
symbol: The ticker to return
adjusted: Return the adjusted prices
cadence: Choose between ['daily', 'weekly', 'monthly'], to return the cadence
output_format: Choose between['json', 'csv', 'pandas']
Returns:
pandas, csv, or json
'''
if output_format:
self._timeseries.output_format = output_format
if cadence == 'daily':
data, _ = self._timeseries.get_daily_adjusted(
symbol=symbol, outputsize=outputsize) if adjusted else self._timeseries.get_daily(symbol=symbol, outputsize=outputsize)
if cadence == 'weekly':
data, _ = self._timeseries.get_weekly_adjusted(
symbol=symbol) if adjusted else self._timeseries.get_weekly(symbol=symbol)
if cadence == 'monthly':
data, _ = self._timeseries.get_monthly_adjusted(
symbol=symbol) if adjusted else self._timeseries.get_monthly(symbol=symbol)
return data
def intraday_quotes(self, symbol, interval='5min', outputsize='full', output_format=None):
''' Returns the TIME_SERIES_INTRADAY endpoint of the Alpha Vantage API.
Params:
symbol: The ticker to return
interval: Choose between['1min', '5min', '15min', '30min', '60min']
output_format: Choose between['json', 'csv', 'pandas']
Returns:
pandas, csv, or json
'''
if output_format:
self._timeseries.output_format = output_format
data, _ = self._timeseries.get_intraday(
symbol=symbol, interval=interval, outputsize=outputsize)
return data
def current_quote(self, symbol):
''' Returns the GLOBAL_QUOTE endpoint
of the Alpha Vantage API.
Params:
symbol: The ticker to return
output_format: Choose between['json', 'csv', 'pandas']
Returns:
pandas, csv, or json
'''
data, _ = self._timeseries.get_quote_endpoint(symbol=symbol)
return data
def last_quote(self, symbol):
return self.current_quote(symbol)
def company(self, symbol, datatype='json'):
return self.search_endpoint(symbol, datatype=datatype)
def search_endpoint(self, keywords, datatype='json'):
'''Search endpoint returns a list of possible companies
that correspond to keywords
Params:
datatype: csv, json, or pandas
keywords: ex. keywords=microsoft
Returns:
pandas, csv, or json
'''
params = {'function': 'SYMBOL_SEARCH',
'keywords': keywords, 'datatype': datatype}
return self.get(params)
def historic_fx_quotes(self, from_symbol, to_symbol, outputsize='full', cadence='daily', output_format=None):
''' Returns the one of the FX_* endpoints of the Alpha Vantage API.
Params:
from_currency: The symbol to convert
to_currency: The symbol to convert to
cadence: Choose between ['daily', 'weekly', 'monthly'], to return the cadence
output_format: Choose between['json', 'csv', 'pandas']
Returns:
pandas, csv, or json
'''
if output_format:
self._foreignexchange.output_format = output_format
if cadence == 'daily':
data, _ = self._foreignexchange.get_currency_exchange_daily(
from_symbol=from_symbol, to_symbol=to_symbol, outputsize=outputsize)
if cadence == 'weekly':
data, _ = self._foreignexchange.get_currency_exchange_weekly(
from_symbol=from_symbol, to_symbol=to_symbol, outputsize=outputsize)
if cadence == 'monthly':
data, _ = self._foreignexchange.get_currency_exchange_monthly(
from_symbol=from_symbol, to_symbol=to_symbol, utputsize=outputsize)
return data
def intraday_fx_quotes(self, from_symbol, to_symbol, interval='5min', outputsize='full', output_format=None):
''' Returns the FX_INTRADAY endpoint of the Alpha Vantage API.
Params:
from_currency: The symbol to convert
to_currency: The symbol to convert to
interval: Choose between['1min', '5min', '15min', '30min', '60min']
output_format: Choose between['json', 'csv', 'pandas']
Returns:
pandas, csv, or json
'''
if output_format:
self._foreignexchange.output_format = output_format
data, _ = self._foreignexchange.get_currency_exchange_intraday(
from_symbol=from_symbol, to_symbol=to_symbol, interval=interval, outputsize=outputsize)
return data
def exchange_rate(self, from_currency, to_currency):
''' Returns the exchange rate of two currencies, digital or physical.
CURRENCY_EXCHANGE_RATE endpoint of the Alpha Vantage API
Params:
from_currency: The symbol to convert
to_currency: The symbol to convert to
Returns:
json
'''
params = {'function': "CURRENCY_EXCHANGE_RATE",
'from_currency': from_currency, 'to_currency': to_currency}
data = self.get(params)
return data
def historic_cryptocurrency_quotes(self, symbol, market, cadence='daily', output_format=None):
''' Returns the one of the DIGITAL_CURRENCY_* endpoints of the Alpha Vantage API.
Params:
symbol: The cryptocurrency to return
market: The market it's being sold on
cadence: Choose between ['daily', 'weekly', 'monthly'], to return the cadence
output_format: Choose between['json', 'csv', 'pandas']
Returns:
pandas, csv, or json
'''
if output_format:
self._cryptocurrencies.output_format = output_format
if cadence == 'daily':
data, _ = self._cryptocurrencies.get_digital_currency_daily(
symbol=symbol, market=market)
if cadence == 'weekly':
data, _ = self._cryptocurrencies.get_digital_currency_weekly(
symbol=symbol, market=market)
if cadence == 'monthly':
data, _ = self._cryptocurrencies.get_digital_currency_monthly(
symbol=symbol, market=market)
return data
def techindicators(self, techindicator='SMA', output_format='json', **kwargs):
''' Returns the one of the technical indicator endpoints of the Alpha Vantage API.
Params:
techindicator: The technical indicator of choice
params: Each technical indicator has additional optional parameters
Returns:
pandas, csv, or json
'''
if output_format:
self._techindicators.output_format = output_format
params = {'function': techindicator}
for key, value in kwargs.items():
params[key] = value
data = self.get(params)
return data
def sector(self):
''' Returns the sector performances
Returns:
pandas, csv, or json
'''
data, _ = self._sectorperformance.get_sector()
return data
dfd = pd.DataFrame()
def clean_Columns(df):
if 'errorslope' not in df.columns:
df.reset_index(inplace=True) #reset index to get timestamp out
df.columns = ['date', 'open', 'high', 'low',
'close'] #Make sure column names are legit
df['index'] = np.arange(len(df)) #create an index
#df['hilow_median'] = df[['high', 'low']].median(axis=1)
return df
if dfm.empty:
dfm, meta_data = cc.get_currency_exchange_monthly(from_symbol='EUR',
to_symbol='USD',
outputsize='full')
clean_Columns(dfm)
dfm = dfm.tail(12)
if dfw.empty:
dfw, meta_data = cc.get_currency_exchange_weekly(from_symbol='EUR',
to_symbol='USD',
outputsize='full')
clean_Columns(dfw)
dfw = dfw.tail(24)
if dfd.empty:
dfd, meta_data = cc.get_currency_exchange_daily(from_symbol='EUR',
to_symbol='USD',
outputsize='full')