class tdAction(object):
def __init__(self):
"""Constructor"""
self.conKey = CONSUMER_KEY
self.redirect = REDIRECT_URL
self.acct = ACCT_NUM
self.tdClient = TDClient(client_id=self.conKey,
redirect_uri=self.redirect)
self.tdClient.login()
def quote(self, tickerList):
"""Grab quotes"""
retDict = {}
quotes = self.tdClient.get_quotes(instruments=tickerList)
for key in quotes:
if type(quotes[key]['lastPrice']) is not None:
retDict[key] = quotes[key]['lastPrice']
return retDict
def history(self, tickerList):
"""Create real time data for a given list of tickers"""
retDict = {}
for item in tickerList:
tickerHistory = self.tdClient.get_price_history(symbol=item,
period_type='year')
priceHistory = []
for data in tickerHistory['candles']:
priceHistory.append(data['close'])
df = DataFrame({item: priceHistory})
retDict[item] = df
return retDict
def history(symbol):
quotes = TDClient.get_price_history(TDSession, symbol=symbol, period_type='day',
period=1, frequency_type='minute', frequency=1,
extended_hours=False)
# start_date = 1606086000000, end_date = 1606341600000,
return quotes
def history(symbol, period, p_type, freq, f_type):
quotes = TDClient.get_price_history(TDSession,
symbol=symbol,
period=period,
period_type=p_type,
frequency=freq,
frequency_type=f_type,
extended_hours=False,
start_date=1606086000000)
# start_date=1606086000000, end_date = 1606341600000,
return quotes
def dt_signal_prices(candle_minutes, symbols):
TDSession = TDClient(client_id=config.client_id,
redirect_uri='http://localhost/test',
credentials_path='td_state.json')
TDSession.login()
cur_day = datetime.datetime.now(tz=pytz.timezone('US/Eastern'))
price_end_date = str(int(round(cur_day.timestamp() * 1000)))
price_start_date = str(
int(
round(
datetime.datetime(cur_day.year, cur_day.month,
cur_day.day - 1).timestamp() * 1000)))
candle_list = []
for symbol in symbols:
p_hist = TDSession.get_price_history(symbol,
period_type='day',
frequency_type='minute',
frequency=str(candle_minutes),
end_date=price_end_date,
start_date=price_start_date)
for candle in p_hist['candles']:
candle_list.append([
symbol,
datetime.datetime.fromtimestamp(candle['datetime'] / 1000),
candle['open'], candle['close'], candle['high'], candle['low']
])
df_dt = pd.DataFrame(
candle_list,
columns=['Symbol', 'Date', 'Open', 'Close', 'High', 'Low'])
# Calculate moving average
df_dt['SMA_9'] = df_dt.groupby('Symbol')['Close'].rolling(
9).mean().reset_index(0, drop=True)
return df_dt
for frequency_period in frequency_periods.keys():
possible_values = frequency_periods[frequency_period]
for value in possible_values:
# Define the dynamic arguments - I want 5 DAYS of historical 1-minute bars.
hist_periodType = frequency_period
hist_period = value
hist_frequencyType = frequency_type
hist_frequency = 1
# make the request
historical_1_minute = TDSession.get_price_history(
symbol=hist_symbol,
period_type=hist_periodType,
period=hist_period,
frequency_type=hist_frequencyType,
frequency=hist_frequency,
extended_hours=hist_needExtendedHoursData)
"""
CUSTOM RANGE
"""
# The max look back period for minute data is 31 Days.
lookback_period = 31
# Define today.
today_00 = datetime.now()
# Define 300 days ago.
today_ago = datetime.now() - timedelta(days=lookback_period)
def request_data():
# Create a new session
td_client = TDClient(
client_id='AZ2BZPRDVDNFBHUB5ADYDAPMD2CLG9RG',
redirect_uri='https://localhost/first',
credentials_path='C:/Users/R/Desktop/code/2nd-tda-api/td_state.json')
# Login to a new session
td_client.login()
print('td client logged in')
# ... Backfill data ...
''' This is for filling in data from overnight or
whenever the program hasn't been running during
market hours '''
for symbol in symbols:
print(symbol)
ext_hours = True # extended hours
period_type = 'month'
period = 3
frequency_type = 'daily'
frequency = 1
# Make request
backfill = td_client.get_price_history(symbol=symbol,
period_type=period_type,
period=period,
frequency_type=frequency_type,
frequency=frequency,
extended_hours=ext_hours)
# returns a dictionary with 3 items: candles (a list), empty, and symbol
# found a typo: http://prntscr.com/sw8dtq
# Remove symbol prefix if present
if symbol[0] == '$' or symbol[0] == '/':
symbol = symbol[1:]
# in case I get bad data that causes an error
# (log something too)
print('backfill requested')
try:
# Save the OHLC data
s = backfill['candles']
new_data = pd.DataFrame(s)
new_data['datetime'] = pd.to_datetime(new_data['datetime'],
unit='ms',
origin='unix')
new_data.rename(columns={"datetime": "dt"}, inplace=True)
# new_data.set_index('dt', inplace=True)
new_data = new_data[[
'dt', 'open', 'high', 'low', 'close', 'volume'
]]
f = open(
'C:/Users/R/Desktop/code/2nd-tda-api/data/{}_1d.csv'.format(
symbol), 'w+')
# append to existing raw data and delete duplicates
old_data = pd.DataFrame(f)
df = old_data.append(new_data)
df.drop_duplicates(inplace=True)
df.fillna(method='ffill', inplace=True)
df.to_csv(
'C:/Users/R/Desktop/code/2nd-tda-api/data/{}_1d.csv'.format(
symbol),
index=True)
f.close()
print('backfill saved!!!!')
except Exception as e:
print(e)
#log someting maybe
pass
class TDSession(TestCase):
"""Will perform a unit test for the TD session."""
def setUp(self) -> None:
"""Set up the `TDClient`."""
# Grab configuration values.
config = ConfigParser()
config.read('config/config.ini')
# Load the values.
CLIENT_ID = config.get('main', 'CLIENT_ID')
REDIRECT_URI = config.get('main', 'REDIRECT_URI')
JSON_PATH = config.get('main', 'JSON_PATH')
ACCOUNT_NUMBER = config.get('main', 'ACCOUNT_NUMBER')
# Initalize the session.
self.td_session = TDClient(client_id=CLIENT_ID,
redirect_uri=REDIRECT_URI,
credentials_path=JSON_PATH,
account_number=ACCOUNT_NUMBER)
def test_creates_instance_of_session(self):
"""Create an instance and make sure it's a `TDClient` object."""
self.assertIsInstance(self.td_session, TDClient)
def test_login(self):
"""Test whether the session is authenticated or not."""
self.assertTrue(self.td_session.login())
self.assertTrue(self.td_session.authstate)
def test_state(self):
"""Make sure the state is updated."""
self.assertIsNotNone(self.td_session.state['refresh_token'])
self.assertIsNotNone(self.td_session.state['access_token'])
self.assertNotEqual(self.td_session.state['refresh_token_expires_at'],
0)
self.assertNotEqual(self.td_session.state['access_token_expires_at'],
0)
def test_single_get_quotes(self):
"""Test Getting a Single quote."""
# Grab a single quote.
quotes = self.td_session.get_quotes(instruments=['MSFT'])
# See if the Symbol is in the Quotes.
self.assertIn('MSFT', quotes)
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_single_quotes.jsonc',
'w+') as data_file:
json.dump(obj=quotes, fp=data_file, indent=3)
def test_get_quotes(self):
"""Test Getting Multiple Quotes."""
# Grab multiple Quotes.
quotes = self.td_session.get_quotes(instruments=['MSFT', 'AAPL'])
# See if the Symbols are in the Quotes.
self.assertTrue(set(['MSFT', 'AAPL']).issuperset(set(quotes.keys())))
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_multiple_quotes.jsonc',
'w+') as data_file:
json.dump(obj=quotes, fp=data_file, indent=3)
def test_get_accounts(self):
"""Test Get Accounts."""
accounts = self.td_session.get_accounts(account='all',
fields=['orders', 'positions'])
self.assertIn('positions', accounts[0]['securitiesAccount'])
self.assertIn('currentBalances', accounts[0]['securitiesAccount'])
# self.assertIn('orderStrategies', accounts[0]['securitiesAccount'])
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_accounts.jsonc',
'w+') as data_file:
json.dump(obj=accounts, fp=data_file, indent=3)
def test_create_stream_session(self):
"""Test Creating a new streaming session."""
stream_session = self.td_session.create_streaming_session()
self.assertIsInstance(stream_session, TDStreamerClient)
def test_get_transactions(self):
"""Test getting transactions."""
# `get_transactions` Endpoint. Should not return an error
transaction_data_multi = self.td_session.get_transactions(
account=self.td_session.account_number, transaction_type='ALL')
# Make sure it's a list.
self.assertIsInstance(transaction_data_multi, list)
self.assertIn('type', transaction_data_multi[0])
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_transaction_data.jsonc',
'w+') as data_file:
json.dump(obj=transaction_data_multi, fp=data_file, indent=3)
def test_get_market_hours(self):
"""Test get market hours."""
# `get_market_hours` Endpoint with multiple values
market_hours_multi = self.td_session.get_market_hours(
markets=['EQUITY', 'FOREX'], date=datetime.today().isoformat())
# If it's a weekend nothing is returned, so raise an error.
if datetime.today().weekday() in (5, 6):
# Make sure it's a list.
self.assertIsInstance(market_hours_multi, dict)
self.assertIn('isOpen', market_hours_multi['equity']['equity'])
else:
# Make sure it's a list.
self.assertIsInstance(market_hours_multi, dict)
self.assertIn('isOpen', market_hours_multi['equity']['EQ'])
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_market_hours.jsonc',
'w+') as data_file:
json.dump(obj=market_hours_multi, fp=data_file, indent=3)
def test_get_instrument(self):
"""Test getting an instrument."""
# `get_instruments` Endpoint.
get_instrument = self.td_session.get_instruments(cusip='594918104')
# Make sure it's a list.
self.assertIsInstance(get_instrument, list)
self.assertIn('cusip', get_instrument[0])
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_instrument.jsonc',
'w+') as data_file:
json.dump(obj=get_instrument, fp=data_file, indent=3)
def test_chart_history(self):
"""Test getting historical prices."""
# Define a list of all valid periods
valid_values = {
'minute': {
'day': [1, 2, 3, 4, 5, 10]
},
'daily': {
'month': [1, 2, 3, 6],
'year': [1, 2, 3, 5, 10, 15, 20],
'ytd': [1]
},
'weekly': {
'month': [1, 2, 3, 6],
'year': [1, 2, 3, 5, 10, 15, 20],
'ytd': [1]
},
'monthly': {
'year': [1, 2, 3, 5, 10, 15, 20]
}
}
# Define the static arguments.
hist_symbol = 'MSFT'
hist_needExtendedHoursData = False
for frequency_type in valid_values.keys():
frequency_periods = valid_values[frequency_type]
for frequency_period in frequency_periods.keys():
possible_values = frequency_periods[frequency_period]
for value in possible_values:
# Define the dynamic arguments - I want 5 DAYS of historical 1-minute bars.
hist_periodType = frequency_period
hist_period = value
hist_frequencyType = frequency_type
hist_frequency = 1
# make the request
historical_prices = self.td_session.get_price_history(
symbol=hist_symbol,
period_type=hist_periodType,
period=hist_period,
frequency_type=hist_frequencyType,
frequency=hist_frequency,
extended_hours=hist_needExtendedHoursData)
self.assertIsInstance(historical_prices, dict)
self.assertFalse(historical_prices['empty'])
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_historical_prices.jsonc',
'w+') as data_file:
json.dump(obj=historical_prices, fp=data_file, indent=3)
def test_custom_historical_prices(self):
"""Test getting historical prices for a custom date range."""
# The max look back period for minute data is 31 Days.
lookback_period = 10
# Define today.
today_00 = datetime.now()
# Define 300 days ago.
today_ago = datetime.now() - timedelta(days=lookback_period)
# The TD API expects a timestamp in milliseconds. However, the timestamp() method only returns to seconds so multiply it by 1000.
today_00 = str(int(round(today_00.timestamp() * 1000)))
today_ago = str(int(round(today_ago.timestamp() * 1000)))
# These values will now be our startDate and endDate parameters.
hist_startDate = today_ago
hist_endDate = today_00
# Define the dynamic arguments.
hist_periodType = 'day'
hist_frequencyType = 'minute'
hist_frequency = 1
# Make the request
historical_custom = self.td_session.get_price_history(
symbol='MSFT',
period_type=hist_periodType,
frequency_type=hist_frequencyType,
start_date=hist_startDate,
end_date=hist_endDate,
frequency=hist_frequency,
extended_hours=True)
self.assertIsInstance(historical_custom, dict)
self.assertFalse(historical_custom['empty'])
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_historical_prices.jsonc',
'w+') as data_file:
json.dump(obj=historical_custom, fp=data_file, indent=3)
def test_search_instruments(self):
"""Test Searching for Instruments."""
# `search_instruments` Endpoint
instrument_search_data = self.td_session.search_instruments(
symbol='MSFT', projection='symbol-search')
self.assertIsInstance(instrument_search_data, dict)
self.assertIn('MSFT', instrument_search_data)
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_search_instrument.jsonc',
'w+') as data_file:
json.dump(obj=instrument_search_data, fp=data_file, indent=3)
def test_get_movers(self):
"""Test getting Market movers."""
# `get_movers` Endpoint
movers_data = self.td_session.get_movers(market='$DJI',
direction='up',
change='value')
if datetime.today().weekday() in (5, 6):
self.assertIsInstance(movers_data, list)
self.assertFalse(movers_data)
else:
self.assertIsInstance(movers_data, list)
self.assertIn('symbol', movers_data[0])
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_movers.jsonc',
'w+') as data_file:
json.dump(obj=movers_data, fp=data_file, indent=3)
def test_get_user_preferences(self):
"""Test getting user preferences."""
# `get_preferences` endpoint. Should not return an error
preference_data = self.td_session.get_preferences(
account=self.td_session.account_number)
self.assertIsInstance(preference_data, dict)
self.assertIn('expressTrading', preference_data)
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_account_preferences.jsonc',
'w+') as data_file:
json.dump(obj=preference_data, fp=data_file, indent=3)
def test_get_user_principals(self):
"""Test getting user principals."""
# `get_preferences` endpoint. Should not return an error
user_principals = self.td_session.get_user_principals(
fields=['preferences', 'surrogateIds'])
self.assertIsInstance(user_principals, dict)
self.assertIn('userId', user_principals)
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_user_principals.jsonc',
'w+') as data_file:
json.dump(obj=user_principals, fp=data_file, indent=3)
def test_get_streamer_keys(self):
"""Test getting user preferences."""
# `get_subscription_keys` endpoint. Should not return an error
streamer_keys = self.td_session.get_streamer_subscription_keys(
accounts=[self.td_session.account_number])
self.assertIsInstance(streamer_keys, dict)
self.assertIn('keys', streamer_keys)
# Save the data.
if SAVE_FLAG:
with open('samples/responses/sample_streamer_keys.jsonc',
'w+') as data_file:
json.dump(obj=streamer_keys, fp=data_file, indent=3)
def tearDown(self) -> None:
"""Teardown the Robot."""
self.td_session = None
def grab_candle_data(pull_from_td: bool) -> list[dict]:
"""A function that grabs candle data from TD Ameritrade,
cleans up the data, and saves it to a JSON file, so we can
use it later.
### Parameters
----------
pull_from_td : bool
If `True`, pull fresh candles from the TD
Ameritrade API. If `False`, load the data
from the JSON file.
### Returns
-------
list[dict]
A list of candle dictionaries with cleaned
dates, and additional values.
"""
if pull_from_td:
# Grab configuration values.
config = ConfigParser()
config.read('config/config.ini')
# Read the Config File.
CLIENT_ID = config.get('main', 'CLIENT_ID')
REDIRECT_URI = config.get('main', 'REDIRECT_URI')
JSON_PATH = config.get('main', 'JSON_PATH')
ACCOUNT_NUMBER = config.get('main', 'ACCOUNT_NUMBER')
# Create a new session
TDSession = TDClient(client_id=CLIENT_ID,
redirect_uri=REDIRECT_URI,
credentials_path=JSON_PATH,
account_number=ACCOUNT_NUMBER)
# Login to the session
TDSession.login()
# Initialize the list to store candles.
all_candles = []
# Loop through each Ticker.
for ticker in ['AAPL', 'NIO', 'FIT', 'TSLA', 'MSFT', 'AMZN', 'IBM']:
# Grab the Quotes.
quotes = TDSession.get_price_history(symbol=ticker,
period_type='day',
period='10',
frequency_type='minute',
frequency=1,
extended_hours=False)
# Grab the Candles.
candles = quotes['candles']
# Loop through each candle.
for candle in candles:
# Calculate the Range.
candle['range'] = round(candle['high'] - candle['low'], 5)
# Add the Symbol.
candle['symbol'] = quotes['symbol']
# Convert to ISO String.
candle['datetime_iso'] = datetime.fromtimestamp(
candle['datetime'] / 1000).isoformat()
# Conver to a Timestamp non-milliseconds.
candle['datetime_non_milli'] = int(candle['datetime'] / 1000)
all_candles.append((candle))
# Save it to a JSON File.
with open(file='data/candles.json', mode='w+') as candle_file:
json.dump(obj=all_candles, fp=candle_file, indent=4)
elif pull_from_td is False and pathlib.Path('data/candles.json').exists():
# Save it to a JSON File.
with open(file='data/candles.json', mode='r') as candle_file:
all_candles = json.load(fp=candle_file)
return all_candles
