def do_echo(bot: Bot, update: Update):
chat_id = update.message.chat_id
text = update.message.text
if text == BUTTON2_APTEKA36_6:
df = investpy.get_stock_recent_data(stock='aptk', country='russia')
bot.send_message(
chat_id=chat_id,
text="На открытии Курс акций Аптека36.6 : {} {}, на закрытии : {} {}"
" Изменение составило {} {}".format(
df['Open'][-1], df['Currency'][-1], df['Close'][-1],
df['Currency'][-1], "%2f" % (df['Close'][-1] - df['Open'][-1]),
df['Currency'][-1]),
)
elif text == BUTTON1_YANDEX:
df = investpy.get_stock_recent_data(stock='yndx', country='russia')
bot.send_message(
chat_id=chat_id,
text="На открытии Курс Яндекса : {} {}, на закрытии : {} {}"
" Изменение составило {} {}".format(
df['Open'][-1], df['Currency'][-1], df['Close'][-1],
df['Currency'][-1], "%2f" % (df['Close'][-1] - df['Open'][-1]),
df['Currency'][-1]),
)
elif text == BUTTON3_SBERBANK:
df = investpy.get_stock_recent_data(stock='SBER', country='russia')
bot.send_message(
chat_id=chat_id,
text="На открытии курс Сбербанка : {} {}, на закрытии : {} {}"
" Изменение составило {} {}".format(
df['Open'][-1], df['Currency'][-1], df['Close'][-1],
df['Currency'][-1], "%2f" % (df['Close'][-1] - df['Open'][-1]),
df['Currency'][-1]),
)
elif text == BUTTON4_MCDONALDS:
df = investpy.get_stock_recent_data(stock='MCD',
country='United States')
bot.send_message(
chat_id=chat_id,
text="На открытии курс McDonalds : {} {}, на закрытии : {} {}"
" Изменение составило {} {}".format(
df['Open'][-1], df['Currency'][-1], df['Close'][-1],
df['Currency'][-1], "%2f" % (df['Close'][-1] - df['Open'][-1]),
df['Currency'][-1]),
)
def getstockValue(stock, country):
df = investpy.get_stock_recent_data(stock=stock, country=country, as_json=False, order='ascending')
a = df.last('1D')['Close'].item()
b = df.last('1D')['Currency'].item()
c = CurrencyRates()
try:
rate = c.get_rates(b)['EUR']
return a*rate
except:
return a
def get_current_data(symbol):
"""
Function returns stock data of latest trading day for given stock symbol
"""
try:
day_data = investpy.get_stock_recent_data(symbol, "india")
current_day_data = day_data.iloc[-1]
return current_day_data
except IndexError:
return False
def get_price_investpy(sname, sticker, stype, scountry):
if stype == "Stock":
try:
df = investpy.get_stock_recent_data(sname, scountry)
except RuntimeError:
try:
df = investpy.get_stock_recent_data(sticker, scountry)
except RuntimeError:
raise MethodNotWorkingError
elif stype == "Fund":
try:
df = investpy.get_fund_recent_data(sname, scountry)
except RuntimeError:
try:
df = investpy.get_fund_recent_data(sticker, scountry)
except RuntimeError:
raise MethodNotWorkingError
elif stype == "ETF":
try:
df = investpy.get_etf_recent_data(sname, scountry)
except RuntimeError:
try:
df = investpy.get_etf_recent_data(sticker, scountry)
except RuntimeError:
raise MethodNotWorkingError
elif stype == "Crypto":
try:
df = investpy.get_crypto_recent_data(sname)
except RuntimeError:
try:
df = investpy.get_crypto_recent_data(sticker)
except RuntimeError:
raise MethodNotWorkingError
else:
raise MethodNotWorkingError
return df.iloc[-1]['Close']
def extraer(cond, stock_valor, pais, pi="", pf=""):
"""
Se extraen los datos del precio final diaro del valor
"""
if cond == 1:
# Se extraen los datos del precio final diario del valor en el rango de días dado
df = investpy.get_stock_historical_data(stock_valor, pais, pi, pf)
else:
# Se extraen los datos del precio final diario del valor en el último mes del valor
df = investpy.get_stock_recent_data(stock_valor,
pais,
as_json=False,
order='ascending')
return df
def test_stocks_errors():
"""
This function raises errors on stock retrieval functions
"""
try:
retrieve_stocks(test_mode=None)
except:
pass
try:
retrieve_stock_countries(test_mode=None)
except:
pass
params = [
{
'country': ['error']
},
{
'country': 'error'
},
]
for param in params:
try:
investpy.get_stocks(country=param['country'])
except:
pass
try:
investpy.get_stocks_list(country=param['country'])
except:
pass
params = [
{
'country': ['error'],
'columns': None,
'as_json': False
},
{
'country': 'spain',
'columns': None,
'as_json': 'error'
},
{
'country': 'spain',
'columns': 0,
'as_json': True
},
{
'country': 'spain',
'columns': ['error'],
'as_json': False
},
]
for param in params:
try:
investpy.get_stocks_dict(country=param['country'],
columns=param['columns'],
as_json=param['as_json'])
except:
pass
params = [
{
'stock': 'FERR',
'country': 'spain',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': None,
'country': 'spain',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': None,
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': ['error'],
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'greece',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'as_json': 'error',
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'as_json': True,
'order': 'error',
'debug': True
},
{
'stock': 'error',
'country': 'spain',
'as_json': True,
'order': 'ascending',
'debug': True
},
{
'stock': ['error'],
'country': 'spain',
'as_json': True,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'as_json': True,
'order': 'ascending',
'debug': 'error'
},
]
for param in params:
try:
investpy.get_stock_recent_data(stock=param['stock'],
country=param['country'],
as_json=param['as_json'],
order=param['order'],
debug=param['debug'])
except:
pass
params = [
{
'stock': 'FERR',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': None,
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': None,
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': ['error'],
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'greece',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': 'error',
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': False,
'order': 'error',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': 'error',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': '01/01/2019',
'to_date': 'error',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'error',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': ['error'],
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': '01/01/1999',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': '01/01/1900',
'to_date': '01/01/1950',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': '01/01/1950',
'to_date': '01/01/2019',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': '01/01/2019',
'to_date': '01/01/1999',
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'stock': 'BBVA',
'country': 'spain',
'from_date': '01/01/2019',
'to_date': '01/03/2019',
'as_json': False,
'order': 'ascending',
'debug': 'error'
},
]
for param in params:
try:
investpy.get_stock_historical_data(stock=param['stock'],
country=param['country'],
from_date=param['from_date'],
to_date=param['to_date'],
as_json=param['as_json'],
order=param['order'],
debug=param['debug'])
except:
pass
params = [
{
'stock': None,
'country': 'spain',
'language': 'spanish'
},
{
'stock': 'BBVA',
'country': None,
'language': 'spanish'
},
{
'stock': 'BBVA',
'country': 'greece',
'language': 'spanish'
},
{
'stock': 'BBVA',
'country': 'spain',
'language': 'error'
},
{
'stock': 'error',
'country': 'spain',
'language': 'spanish'
},
{
'stock': ['error'],
'country': 'spain',
'language': 'spanish'
},
]
for param in params:
try:
investpy.get_stock_company_profile(stock=param['stock'],
country=param['country'],
language=param['language'])
except:
pass
params = [
{
'stock': None,
'country': 'spain',
},
{
'stock': ['error'],
'country': 'spain',
},
{
'stock': 'bbva',
'country': ['error'],
},
{
'stock': 'bbva',
'country': 'error',
},
{
'stock': 'error',
'country': 'spain',
},
{
'stock': 'ALUA',
'country': 'argentina',
},
]
for param in params:
try:
investpy.get_stock_dividends(stock=param['stock'],
country=param['country'])
except:
pass
params = [
{
'by': None,
'value': 'BBVA',
},
{
'by': ['error'],
'value': 'BBVA',
},
{
'by': 'error',
'value': 'BBVA',
},
{
'by': 'name',
'value': None,
},
{
'by': 'name',
'value': ['error'],
},
{
'by': 'isin',
'value': 'BBVA',
},
]
for param in params:
try:
investpy.search_stocks(by=param['by'], value=param['value'])
except:
pass
import numpy as np
import investpy
import pandas as pd
from cs50 import get_string
import plotly.express as px
## Getting the symbol from user
symbol = get_string("Symbol is ")
print(symbol)
## Getting stocks' open price, close price, low price, close price, volume and currency with investpy
df = investpy.get_stock_recent_data(stock=symbol,
country='United States',
as_json=False,
order='ascending')
## Changing Pandas' database to csv
df.to_csv('file.csv', index=True, encoding='utf-8')
csv_file = 'file.csv'
df = pd.read_csv(csv_file)
print(df)
## Plotting close price against time
fig = px.line(df, x='Date', y='Close', title='Apple Share Prices over a month')
fig.show()
## Plotting volume traded against time
fig1 = px.line(df,
x='Date',
y='Volume',
title='Volume traded over the past month')
def test_investpy_stocks():
"""
This function checks that stock data retrieval functions listed in investpy work properly.
"""
params = [
{
'country': 'spain',
},
{
'country': None,
},
]
for param in params:
investpy.get_stocks(country=param['country'])
investpy.get_stocks_list(country=param['country'])
params = [
{
'country': None,
'columns': ['full_name', 'name'],
'as_json': True
},
{
'country': None,
'columns': ['full_name', 'name'],
'as_json': False
},
{
'country': 'spain',
'columns': ['full_name', 'name'],
'as_json': True
},
{
'country': 'spain',
'columns': ['full_name', 'name'],
'as_json': False
},
{
'country': 'spain',
'columns': None,
'as_json': False
},
]
for param in params:
investpy.get_stocks_dict(country=param['country'],
columns=param['columns'],
as_json=param['as_json'])
investpy.get_stock_countries()
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_stock_recent_data(stock='BBVA',
country='spain',
as_json=param['as_json'],
order=param['order'],
interval='Daily')
investpy.get_stock_historical_data(stock='BBVA',
country='spain',
from_date='01/01/1990',
to_date='01/01/2019',
as_json=param['as_json'],
order=param['order'],
interval='Daily')
for value in ['spanish', 'english']:
investpy.get_stock_company_profile(stock='BBVA',
country='spain',
language=value)
params = [
{
'stock': 'bbva',
'country': 'spain',
'as_json': False
},
{
'stock': 'bbva',
'country': 'spain',
'as_json': True
},
{
'stock': 'HSBK',
'country': 'kazakhstan',
'as_json': False
}
]
for param in params:
investpy.get_stock_information(stock=param['stock'], country=param['country'], as_json=param['as_json'])
params = [
{
'country': 'spain',
'as_json': True,
'n_results': 50
},
{
'country': 'united states',
'as_json': False,
'n_results': 50
},
{
'country': 'bosnia',
'as_json': False,
'n_results': 50
},
{
'country': 'palestine',
'as_json': False,
'n_results': 50
},
{
'country': 'dubai',
'as_json': False,
'n_results': 50
},
{
'country': 'ivory coast',
'as_json': False,
'n_results': 50
}
]
for param in params:
investpy.get_stocks_overview(country=param['country'], as_json=param['as_json'], n_results=param['n_results'])
params = [
{
'stock': 'bbva',
'country': 'spain'
},
{
'stock': 'entel',
'country': 'chile'
}
]
for param in params:
investpy.get_stock_dividends(stock=param['stock'], country=param['country'])
params = [
{
'stock': 'bbva',
'country': 'spain',
'summary_type': 'balance_sheet',
'period': 'annual'
},
{
'stock': 'aapl',
'country': 'united states',
'summary_type': 'income_statement',
'period': 'quarterly'
},
{
'stock': 'barc',
'country': 'united kingdom',
'summary_type': 'cash_flow_statement',
'period': 'annual'
}
]
for param in params:
investpy.get_stock_financial_summary(stock=param['stock'],
country=param['country'],
summary_type=param['summary_type'],
period=param['period'])
investpy.search_stocks(by='name', value='BBVA')
def test_investpy_stocks():
"""
This function checks that stock data retrieval functions listed in investpy work properly.
"""
params = [
{
'country': 'spain',
},
{
'country': None,
},
]
for param in params:
investpy.get_stocks(country=param['country'])
investpy.get_stocks_list(country=param['country'])
params = [
{
'country': None,
'columns': ['full_name', 'name'],
'as_json': True
},
{
'country': None,
'columns': ['full_name', 'name'],
'as_json': False
},
{
'country': 'spain',
'columns': ['full_name', 'name'],
'as_json': True
},
{
'country': 'spain',
'columns': ['full_name', 'name'],
'as_json': False
},
{
'country': 'spain',
'columns': None,
'as_json': False
},
]
for param in params:
investpy.get_stocks_dict(country=param['country'],
columns=param['columns'],
as_json=param['as_json'])
investpy.get_stock_countries()
params = [
{
'as_json': True,
'order': 'ascending',
'debug': False
},
{
'as_json': False,
'order': 'ascending',
'debug': True
},
{
'as_json': True,
'order': 'descending',
'debug': False
},
{
'as_json': False,
'order': 'descending',
'debug': False
},
]
for param in params:
investpy.get_stock_recent_data(stock='BBVA',
country='spain',
as_json=param['as_json'],
order=param['order'],
debug=param['debug'])
investpy.get_stock_historical_data(stock='BBVA',
country='spain',
from_date='01/01/1990',
to_date='01/01/2019',
as_json=param['as_json'],
order=param['order'],
debug=param['debug'])
for value in ['spanish', 'english']:
investpy.get_stock_company_profile(stock='BBVA',
country='spain',
language=value)
investpy.get_stock_dividends(stock='BBVA', country='spain')
investpy.search_stocks(by='name', value='BBVA')
print(f'ticker {ticker} SUCCESS.....')
time.sleep(13)
#%%
import investpy
# https://investpy.readthedocs.io/_info/introduction.html
# Retrieve all the available stocks as a Python list
stocks = investpy.get_stocks_list()
funds = investpy.get_funds_list()
etfs = investpy.get_etfs_list()
# Retrieve the recent historical data (past month) of a stock as a pandas.DataFrame on ascending date order
df_bbva = investpy.get_stock_recent_data(stock='bbva',
country='spain',
as_json=False,
order='ascending')
# Retrieve the company profile of the introduced stock on english
profile = investpy.get_stock_company_profile(stock='bbva',
country='spain',
language='english')
df_aapl = investpy.get_stock_historical_data(stock='AAPL',
country='United States',
from_date='01/01/2010',
to_date='01/01/2020')
df_fund = investpy.get_fund_historical_data(
fund='bbva plan multiactivo moderado pp',
country='spain',
import investpy
import yaml
with open('stock.yaml') as f:
data = yaml.load(f, Loader=yaml.FullLoader)
for item in data["stocks"]:
print(item["name"])
df = investpy.get_stock_recent_data(stock=item["name"],country=item["country"])
print(df)
for item in data["etfs"]:
print(item["name"])
df = investpy.get_etf_recent_data(etf=item["name"],country=item["country"])
print(df)
# df = investpy.get_stock_recent_data(stock='PEUP',country='france')
# print(df)
# search_results = investpy.search_etfs(by='isin', value='LU1681043599')
# print(search_results)
# df = investpy.get_etf_recent_data(etf='Amundi MSCI World UCITS',country='france')
# print(df)
# df = investpy.get_etf_historical_data(etf='Amundi MSCI World UCITS',country='france',from_date='01/12/2019',to_date='06/02/2020')
# print(df)
df3 = pandas.DataFrame({ 'apple': apple["adjclose"].pct_change(),
'mcrsft': mcrsft["adjclose"].pct_change(),
'DJI': DJI["adjclose"].pct_change()})
dfna = df3.dropna()
#investing.com
#pip install investpy==0.9.7
import investpy
df = investpy.get_stock_recent_data(stock='BBVA',
country='spain')
print(df.head())
df = investpy.get_stock_historical_data(stock='BBVA',
country='spain',
from_date='01/01/2010',
to_date='01/01/2019')
print(df.head())
df = investpy.get_indices_historical_data(indices='ise-100',
country='turkey',
from_date='01/01/2010',
to_date='01/01/2019')
print(df.head())
def get_stock_price(ticker):
return investpy.get_stock_recent_data(stock=ticker,
country='iceland',
as_json=False,
order='ascending')['Close'][-1]
