def descarga_registros(self, request, queryset):
for i in queryset:
perfil = investpy.get_stock_company_profile(stock=i.symbol,
country=i.pais)
obj = Empresa.objects.get(symbol=i.symbol)
FundamentalesEmpresa.objects.create(
empresa_id=obj.id,
num_acciones=int(perfil['num_acciones'].replace(',', '')),
beneficios=0 if perfil['beneficios'] == 'N/A' else float(
perfil['beneficios'].replace('B', '000000')),
valor_bursatil=float(perfil['valor_bursatil'].replace('B', '')),
proximos_resultados=perfil['proximos_resultados'])
print(perfil)
def get_stock_info(ticker):
info = investpy.get_stock_company_profile(stock=ticker, country='iceland')
description = info["desc"]
url = info["url"]
price_now = get_stock_price(ticker)
now = datetime.datetime.now()
price_year_ago = investpy.get_stock_historical_data(
stock=ticker,
country='iceland',
from_date=(now - datetime.timedelta(days=365)).strftime('%d/%m/%Y'),
to_date=(
now -
datetime.timedelta(days=350)).strftime('%d/%m/%Y'))['Close'][-1]
return price_now, price_year_ago, description, url
def only():
stock = request.form.get('stockName').upper()
start = request.form.get('startDate')
end = request.form.get('endDate')
country = request.form.get('countryName')
model = load_model('model.h5')
start_date = datetime.strptime(start, "%Y-%m-%d").strftime("%d/%m/%Y")
end_date = datetime.strptime(end, "%Y-%m-%d").strftime("%d/%m/%Y")
df = investpy.get_stock_historical_data(stock=stock,
country=country,
from_date=start_date,
to_date=end_date)
df.drop('Currency', axis=1, inplace=True)
data = df.filter(['Close'])
dataset = data.values
scaler = MinMaxScaler(feature_range=(0, 1))
scaled_data = scaler.fit_transform(dataset)
df = investpy.get_stock_historical_data(stock=stock,
country=country,
from_date=start_date,
to_date=end_date)
df.drop('Currency', axis=1, inplace=True)
pred_data = df.filter(['Close'])
last_60_days = pred_data[-60:].values
last_60_days_scaled = scaler.fit_transform(last_60_days)
X_test = []
X_test.append(last_60_days_scaled)
X_test = np.array(X_test)
X_test = np.reshape(X_test, (X_test.shape[0], X_test.shape[1], 1))
pred_price = model.predict(X_test)
pred_price = scaler.inverse_transform(pred_price)
print(pred_price)
com_profile = investpy.get_stock_company_profile(stock=stock,
country=country,
language='english')
profile = com_profile['desc']
return render_template('only.html',
stock=stock,
start_date=start_date,
end_date=end_date,
profile=profile,
pred_price=pred_price)
def find_technical_details(symbol):
# Using the investpy module, we would get investing.com website url for the company
# TODO:
# Add functionality for Canadian and Stocks that are from other parts of the world
company_profile = investpy.get_stock_company_profile(
stock=symbol, country='United States')
# print(company_profile)
company_profile_url = company_profile['url']
technical_url = company_profile_url[:-15] + 'technical'
response = requests.get(technical_url,
headers={'User-Agent': 'Mozilla/5.0'})
soup = BeautifulSoup(response.text, 'lxml')
# print(soup)
data_table = soup.find_all('div', {'id': 'techinalContent'})
# print(data_table)
cols = [td.text for td in data_table[0].select('td')]
# print(cols)
# We initializa a empty list
parsed_list = []
# Parse data that we receive from web scraping into array
for text in cols:
parsed_text = text.strip()
if '\t' or '\n' in text:
parsed_text = text.replace('\n', '')
parsed_text = parsed_text.replace('\t', '')
parsed_list.append(parsed_text)
print(parsed_list)
# Now we initialize a dictionary that contains information in regards to the data we want, as well as how
# many number of elements are contained in the array
technical_indicators = {
'Classic': 7,
'RSI(14)': 2,
'MACD(12,26)': 2,
'MA10': 1,
'MA20': 1,
'MA50': 1,
'MA100': 1,
}
""" SECOND APPROACH
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
def get_company_summary(symbol):
summary_text = inp.get_stock_company_profile(stock=symbol,
country='turkey')['desc']
return summary_text
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')
# 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',
from_date='01/01/2010',
to_date='01/01/2019')
df_bbva_etf = investpy.get_etf_recent_data(etf='bbva accion dj eurostoxx 50',
country='spain')
def get_company_profile(a):
company_profile = investpy.get_stock_company_profile(stock=a,
country='malaysia')
return company_profile.get('desc','')
#stocks_prices
# libraries
import investpy as inv
# declarations
# execution
preco = inv.get_stock_company_profile('IBFF11', 'brazil')
print(preco)
def update_graph(ticker, selected_sector):
# Get company info
company_info = investpy.get_stock_company_profile(
ticker, country='malaysia')['desc']
# Get sector volume
if selected_sector == 'All':
all_sec_list = lookup['sector'].unique().tolist()
sec_vol_list = []
for sec in all_sec_list:
sec_vol_list.append(get_sector_vol(sec))
sector_volume = sum(sec_vol_list)
else:
sector_volume = get_sector_vol(selected_sector)
# Get latest closed price and volume for selected stock
data = get_stock_data(ticker)
latest_sto_close = data.iloc[-1]['Close']
latest_sto_vol = data.iloc[-1]['Volume']
# Get stock percentage contribution of volume
percentage = (latest_sto_vol) / (sector_volume) * 100
percentage_str = "{0:.5f}%".format(percentage)
# Set up overlap graphs
figure = plotly.subplots.make_subplots(specs=[[{"secondary_y": True}]])
figure.add_trace(
go.Scatter(x=data['Date'],
y=data['Close'],
mode="lines",
name='Stock Price'),
secondary_y=False,
)
figure.add_trace(go.Bar(x=data['Date'],
y=data['Volume'],
name='Volume Traded'),
secondary_y=True)
# Set x-axis title
figure.update_xaxes(title_text="Date")
# Set y-axes titles
figure.update_yaxes(title_text="Volume traded", secondary_y=True)
figure.update_yaxes(title_text="Price (RM)", secondary_y=False)
figure.update_xaxes(
rangeslider_visible=True,
rangeselector=dict(buttons=list([
dict(count=7, label="1w", step="day", stepmode="backward"),
dict(count=1, label="1m", step="month", stepmode="backward"),
dict(count=6, label="6m", step="month", stepmode="backward"),
dict(count=1, label="1y", step="year", stepmode="backward"),
dict(step="all")
])),
rangebreaks=[
dict(enabled=True,
bounds=['sat', 'mon']), #hide weekends (not working atm)
])
figure.update_layout(
autosize=True,
# height=380,
# width = 850,
margin=dict(l=55, r=15, b=50, t=50, pad=0),
legend=dict(x=0.7, y=1.05, orientation='h'),
)
return ([
company_info, latest_sto_close, latest_sto_vol, sector_volume,
percentage_str, figure
])
