def set_historical_prices(trading_robot: PyRobot):
"""
Set the historical prices for the robot
:param trading_robot {PyRobot} -- The trading robot class
"""
end_date = datetime.today()
start_date = end_date - timedelta(days=20)
# Get historical data
historical_prices = trading_robot.grab_historical_prices(
start=start_date,
end=end_date,
bar_size=1,
bar_type='minute'
)
# Convert data to a stock frame
stock_frame = trading_robot.create_stock_frame(
data=historical_prices['aggregated']
)
# Add the stock frame to the portfolio
trading_robot.portfolio.stock_frame = stock_frame
trading_robot.portfolio.historical_prices = historical_prices
class PyRobotIndicatorTest(TestCase):
"""Will perform a unit test for the Indicator Object."""
def setUp(self) -> None:
"""Set up the Indicator Client."""
# Grab configuration values.
config = ConfigParser()
config.read('configs/config.ini')
CLIENT_ID = config.get('main', 'CLIENT_ID')
REDIRECT_URI = config.get('main', 'REDIRECT_URI')
CREDENTIALS_PATH = config.get('main', 'JSON_PATH')
# Create a robot.
self.robot = PyRobot(client_id=CLIENT_ID,
redirect_uri=REDIRECT_URI,
credentials_path=CREDENTIALS_PATH)
# Grab historical prices, first define the start date and end date.
start_date = datetime.today()
end_date = start_date - timedelta(days=30)
# Grab the historical prices.
historical_prices = self.robot.grab_historical_prices(
start=end_date,
end=start_date,
bar_size=1,
bar_type='minute',
symbols=['AAPL', 'MSFT'])
# Convert data to a Data Frame.
self.stock_frame = self.robot.create_stock_frame(
data=historical_prices['aggregated'])
def test_creates_instance_of_session(self):
"""Create an instance and make sure it's a StockFrame."""
self.assertIsInstance(self.stock_frame, StockFrame)
# Print out the order.
pprint.pprint(new_trade.order)
# Grab historical prices, first define the start date and end date.
start_date = datetime.today()
end_date = start_date - timedelta(days=30)
# Grab the historical prices.
historical_prices = trading_robot.grab_historical_prices(start=end_date,
end=start_date,
bar_size=1,
bar_type='minute')
# Convert data to a Data Frame.
stock_frame = trading_robot.create_stock_frame(
data=historical_prices['aggregated'])
# We can also add the stock frame to the Portfolio object.
trading_robot.portfolio.stock_frame = stock_frame
# Additionally the historical prices can be set as well.
trading_robot.portfolio.historical_prices = historical_prices
# Portfolio Variance
pprint.pprint(trading_robot.portfolio.portfolio_metrics())
# Create an indicator Object.
indicator_client = Indicators(price_data_frame=stock_frame)
# Add the RSI Indicator.
indicator_client.rsi(period=14)
class PyRobotStockFrameTest(TestCase):
"""Will perform a unit test for the StockFrame Object."""
def setUp(self) -> None:
"""Set up the Stock Frame."""
# Grab configuration values.
config = ConfigParser()
config.read('configs/config.ini')
CLIENT_ID = config.get('main', 'CLIENT_ID')
REDIRECT_URI = config.get('main', 'REDIRECT_URI')
CREDENTIALS_PATH = config.get('main', 'JSON_PATH')
# Create a robot.
self.robot = PyRobot(client_id=CLIENT_ID,
redirect_uri=REDIRECT_URI,
credentials_path=CREDENTIALS_PATH)
# Grab historical prices, first define the start date and end date.
start_date = datetime.today()
end_date = start_date - timedelta(days=30)
# Grab the historical prices.
historical_prices = self.robot.grab_historical_prices(
start=end_date,
end=start_date,
bar_size=1,
bar_type='minute',
symbols=['AAPL', 'MSFT'])
# Convert data to a Data Frame.
self.stock_frame = self.robot.create_stock_frame(
data=historical_prices['aggregated'])
def test_creates_instance_of_session(self):
"""Create an instance and make sure it's a StockFrame."""
self.assertIsInstance(self.stock_frame, StockFrame)
def test_frame_property(self):
"""Test that the `frame` property returns a Pandas DataFrame object."""
self.assertIsInstance(self.stock_frame.frame, pd.DataFrame)
self.assertIsInstance(self.stock_frame.frame.index, pd.MultiIndex)
def test_frame_symbols(self):
"""Test that the `frame.index` property contains the specified symbols."""
self.assertIn('AAPL', self.stock_frame.frame.index)
self.assertIn('MSFT', self.stock_frame.frame.index)
def test_symbol_groups_property(self):
"""Test that the `symbol_groups` property returns a Pandas DataFrameGroupBy object."""
self.assertIsInstance(self.stock_frame.symbol_groups,
pd.core.groupby.DataFrameGroupBy)
def test_symbol_rolling_groups_property(self):
"""Test that the `symbol_rolling_groups` property returns a Pandas RollingGroupBy object."""
self.assertIsInstance(self.stock_frame.symbol_rolling_groups(size=15),
pd.core.window.RollingGroupby)
def test_add_row(self):
"""Test adding a new row to our data frame."""
# Define a new row.
new_row_dict = {
'AAPL': {
'openPrice': 100.00,
'closePrice': 100.00,
'highPrice': 100.00,
'lowPrice': 100.00,
'askSize': 100,
'bidSize': 100,
'quoteTimeInLong': 1586390399572
}
}
# Add the row.
self.stock_frame.add_rows(data=new_row_dict)
# Create a timestamp.
time_stamp_parsed = pd.to_datetime(1586390399572,
unit='ms',
origin='unix')
index_tuple = ('AAPL', time_stamp_parsed)
# Check to see if the Tuple is in the Index.
self.assertIn(index_tuple, self.stock_frame.frame.index)
def tearDown(self) -> None:
"""Teardown the StockFrame."""
self.stock_frame = None
class PyRobotIndicatorTest(TestCase):
"""Will perform a unit test for the Indicator Object."""
def setUp(self) -> None:
"""Set up the Indicator Client."""
# Grab configuration values.
config = ConfigParser()
config.read('configs/config.ini')
CLIENT_ID = config.get('main', 'CLIENT_ID')
REDIRECT_URI = config.get('main', 'REDIRECT_URI')
CREDENTIALS_PATH = config.get('main', 'JSON_PATH')
# Create a robot.
self.robot = PyRobot(
client_id = CLIENT_ID,
redirect_uri = REDIRECT_URI,
credentials_path = CREDENTIALS_PATH
)
# Grab historical prices, first define the start date and end date.
start_date = datetime.today()
end_date = start_date - timedelta(days=30)
# Grab the historical prices.
historical_prices = self.robot.grab_historical_prices(
start=end_date,
end=start_date,
bar_size=1,
bar_type='minute',
symbols=['AAPL','MSFT']
)
# Convert data to a Data Frame.
self.stock_frame = self.robot.create_stock_frame(data=historical_prices['aggregated'])
# Create the indicator client.
self.indicator_client = Indicators(price_data_frame=self.stock_frame)
def test_creates_instance_of_session(self):
"""Create an instance and make sure it's a StockFrame."""
self.assertIsInstance(self.stock_frame, StockFrame)
self.assertIsInstance(self.indicator_client, Indicators)
def test_price_frame_data_property(self):
"""Test getting the Price Data Frame."""
self.assertIsNotNone(self.indicator_client.price_data_frame)
def test_is_multi_index_property(self):
"""Test getting the Price Data Frame."""
self.assertTrue(self.indicator_client.is_multi_index)
def test_change_in_price(self):
"""Test adding the Change in Price."""
# Create the Change in Price indicator.
self.indicator_client.change_in_price()
# Check if we have the column.
self.assertIn('change_in_price', self.stock_frame.frame.columns)
# And that it's not empty.
self.assertFalse(self.stock_frame.frame['change_in_price'].empty)
def test_rsi(self):
"""Test adding the Relative Strength Index."""
# Create the RSI indicator.
self.indicator_client.rsi(period=14)
# Check if we have the column.
self.assertIn('rsi', self.stock_frame.frame.columns)
# And that it's not empty.
self.assertFalse(self.stock_frame.frame['rsi'].empty)
def test_sma(self):
"""Test adding the Simple Moving Average."""
# Create the SMA indicator.
self.indicator_client.sma(period=200)
# Check if we have the column.
self.assertIn('sma', self.stock_frame.frame.columns)
# And that it's not empty.
self.assertFalse(self.stock_frame.frame['sma'].empty)
def test_ema(self):
"""Test adding the Exponential Moving Average."""
# Create the EMA indicator.
self.indicator_client.ema(period=50)
# Check if we have the column.
self.assertIn('ema', self.stock_frame.frame.columns)
# And that it's not empty.
self.assertFalse(self.stock_frame.frame['ema'].empty)
def test_indicator_exist(self):
"""Test checkinf if an indicator column exist."""
# Create the EMA indicator.
self.indicator_client.ema(period=50)
# Check if we have the column.
self.assertIn('ema', self.stock_frame.frame.columns)
# And that it's not empty.
self.assertTrue(self.stock_frame.do_indicator_exist(column_names=['ema']))
def test_indicator_signal(self):
"""Test checkinf if an indicator column exist."""
# Create the EMA indicator.
self.indicator_client.ema(period=50)
self.indicator_client.set_indicator_signal(
indicator='sma',
buy=50.0,
sell=30.0,
condition_buy=operator.ge,
condition_sell=operator.le
)
func_1 = operator.ge
func_2 = operator.le
correct_dict = {
'buy': 50.0,
'sell': 30.0,
'buy_operator': func_1,
'sell_operator': func_2
}
correct_dict_all = {
'sma':{
'buy': 50.0,
'sell': 30.0,
'buy_operator': func_1,
'sell_operator': func_2
}
}
# And that it's not empty.
self.assertDictEqual(
self.indicator_client.get_indicator_signal(indicator='sma'),
correct_dict
)
# And that it's not empty.
self.assertDictEqual(
self.indicator_client.get_indicator_signal(),
correct_dict_all
)
def tearDown(self) -> None:
"""Teardown the Indicator object."""
self.stock_frame = None
self.indicator_client = None