class AlpacaData(DataAPI):
def __init__(self):
self.alpaca_rest_client = REST(key_id=config.alpaca_api_key,
secret_key=config.alpaca_api_secret)
if not self.alpaca_rest_client:
raise AssertionError(
"Failed to authenticate Alpaca RESTful client")
def get_symbols(self) -> List[Dict]:
if not self.alpaca_rest_client:
raise AssertionError("Must call w/ authenticated Alpaca client")
return self.alpaca_rest_client.list_assets()
def get_symbol_data(
self,
symbol: str,
start: date,
end: date = date.today(),
scale: TimeScale = TimeScale.minute,
) -> pd.DataFrame:
_start = nytz.localize(datetime.combine(
start, datetime.min.time())).isoformat()
_end = (nytz.localize(datetime.now().replace(
microsecond=0)).isoformat() if end >= date.today() else end)
if not self.alpaca_rest_client:
raise AssertionError("Must call w/ authenticated Alpaca client")
t: TimeFrame = (TimeFrame.Minute if scale == TimeScale.minute else
TimeFrame.Day if scale == TimeScale.day else None)
data = self.alpaca_rest_client.get_bars(
symbol=symbol,
timeframe=t,
start=_start,
end=_end,
limit=10000,
adjustment="raw",
).df
data = data.tz_convert("America/New_York")
data["vwap"] = None
data["average"] = None
data["count"] = None
if data.empty:
raise ValueError(
f"[ERROR] {symbol} has no data for {_start} to {_end} w {scale.name}"
)
return data
class AlpacaData(DataAPI):
def __init__(self):
self.alpaca_rest_client = REST(
key_id=config.alpaca_api_key, secret_key=config.alpaca_api_secret
)
if not self.alpaca_rest_client:
raise AssertionError(
"Failed to authenticate Alpaca RESTful client"
)
def get_symbols(self) -> List[Dict]:
if not self.alpaca_rest_client:
raise AssertionError("Must call w/ authenticated polygon client")
data = self.alpaca_rest_client.list_assets()
return data
def get_symbol_data(
self,
symbol: str,
start: date,
end: date = date.today(),
scale: TimeScale = TimeScale.minute,
) -> pd.DataFrame:
if not self.alpaca_rest_client:
raise AssertionError("Must call w/ authenticated Alpaca client")
t: TimeFrame = (
TimeFrame.Minute
if scale == TimeScale.minute
else TimeFrame.Day
if scale == TimeScale.day
else None
)
data = self.alpaca_rest_client.get_bars(
symbol=symbol, timeframe=t, start=start, end=end, limit=10000
).df
if data.empty:
raise ValueError(
f"[ERROR] {symbol} has no data for {start} to {end} w {scale.name}"
)
return data
print(trades)
print(trades[trades['size']>=200])
min_price = float(trades['price'].min())
max_size = float(trades['size'].max())
print('min_price: %s' %min_price)
print('max_size: %s' %max_size)
if min_price<(0.96*low_price):
print('Low price on the day: %s' %(low_price))
for i in range(0,min(50,len(trades))):
print(trades.sort_values('price').iloc[[i]] )
print('conditions: %s' %((trades.sort_values('price')[['conditions','exchange']].iloc[[i]]) ))
print('size: %s' %(trades.sort_values('price').iloc[[i]][['size']]) )
print('Highest prices: %s' %((trades.sort_values('price')).iloc[[-1]][['price','exchange']]))
sys.exit(0)
trade_days = api.get_bars(ticker, TimeFrame.Day, "2021-01-02", "2021-03-12", 'raw').df
#trade_days = api.get_bars(ticker, TimeFrame.Day, "2021-03-05", "2021-03-12", 'raw').df
#print(trade_days)
#print(pd.unique(trade_days['volume']))
print(trade_days.index.unique())
total_days_tested = len(trade_days.index.unique())
days_less_thr=0
for myday in trade_days.index.unique():
ts = pd.Timestamp(year = myday.year, month = myday.month, day = myday.day,
hour = 16, minute=00, second = 0, tz = 'US/Eastern')
te = pd.Timestamp(year = myday.year, month = myday.month, day = myday.day,
hour = 20, minute=00, second = 0, tz = 'US/Eastern')
#choseInd = [ind for ind in trade_days.index if (ind.day<9 or ind.hour>=16)]
days_price = trade_days.loc[myday]
print(days_price['high'])
low_price=0.0
def download_symbol(cls,
symbol: str,
timeframe: str = '1d',
start: tp.DatetimeLike = 0,
end: tp.DatetimeLike = 'now UTC',
adjustment: tp.Optional[str] = 'all',
limit: int = 500,
exchange: tp.Optional[str] = 'CBSE',
**kwargs) -> tp.Frame:
"""Download the symbol.
Args:
symbol (str): Symbol.
timeframe (str): Timeframe of data.
Must be integer multiple of 'm' (minute), 'h' (hour) or 'd' (day). i.e. '15m'.
See https://alpaca.markets/data.
!!! note
Data from the latest 15 minutes is not available with a free data plan.
start (any): Start datetime.
See `vectorbt.utils.datetime_.to_tzaware_datetime`.
end (any): End datetime.
See `vectorbt.utils.datetime_.to_tzaware_datetime`.
adjustment (str): Specifies the corporate action adjustment for the stocks.
Allowed are `raw`, `split`, `dividend` or `all`.
limit (int): The maximum number of returned items.
exchange (str): For crypto symbols. Which exchange you wish to retrieve data from.
Allowed are `FTX`, `ERSX`, `CBSE`
For defaults, see `data.alpaca` in `vectorbt._settings.settings`.
"""
from vectorbt._settings import settings
from alpaca_trade_api.rest import TimeFrameUnit, TimeFrame, REST
alpaca_cfg = settings['data']['alpaca']
client_kwargs = dict()
for k in get_func_kwargs(REST):
if k in kwargs:
client_kwargs[k] = kwargs.pop(k)
client_kwargs = merge_dicts(alpaca_cfg, client_kwargs)
client = REST(**client_kwargs)
_timeframe_units = {'d': TimeFrameUnit.Day, 'h': TimeFrameUnit.Hour, 'm': TimeFrameUnit.Minute}
if len(timeframe) < 2:
raise ValueError("invalid timeframe")
amount_str = timeframe[:-1]
unit_str = timeframe[-1]
if not amount_str.isnumeric() or unit_str not in _timeframe_units:
raise ValueError("invalid timeframe")
amount = int(amount_str)
unit = _timeframe_units[unit_str]
_timeframe = TimeFrame(amount, unit)
start_ts = to_tzaware_datetime(start, tz=get_utc_tz()).isoformat()
end_ts = to_tzaware_datetime(end, tz=get_utc_tz()).isoformat()
def _is_crypto_symbol(symbol):
return len(symbol) == 6 and "USD" in symbol
if _is_crypto_symbol(symbol):
df = client.get_crypto_bars(
symbol=symbol,
timeframe=_timeframe,
start=start_ts,
end=end_ts,
limit=limit,
exchanges=exchange
).df
else:
df = client.get_bars(
symbol=symbol,
timeframe=_timeframe,
start=start_ts,
end=end_ts,
adjustment=adjustment,
limit=limit
).df
# filter for OHLCV
# remove extra columns
df.drop(['trade_count', 'vwap'], axis=1, errors='ignore', inplace=True)
# capitalize
df.rename(columns={
'open': 'Open',
'high': 'High',
'low': 'Low',
'close': 'Close',
'volume': 'Volume',
'exchange': 'Exchange'
}, inplace=True)
df['Open'] = df['Open'].astype(float)
df['High'] = df['High'].astype(float)
df['Low'] = df['Low'].astype(float)
df['Close'] = df['Close'].astype(float)
df['Volume'] = df['Volume'].astype(float)
return df
from dotenv import load_dotenv
import os
from alpaca_trade_api.rest import REST, TimeFrame
load_dotenv()
api = REST()
bars = api.get_bars("AAPL",
TimeFrame.Hour,
"2021-02-08",
"2021-02-08",
limit=10,
adjustment='raw').df
print(bars)
from alpaca_trade_api.rest import REST, TimeFrame
import sys
BASE_URL = "https://paper-api.alpaca.markets"
ALPACA_API_KEY = sys.argv[1]
ALPACA_SECRET_KEY = sys.argv[2]
api = REST(ALPACA_API_KEY, ALPACA_SECRET_KEY, BASE_URL)
account = api.get_account()
print("Your account is:" + account.status)
rawData = api.get_bars("KO",
TimeFrame.Day,
"2021-06-01",
"2021-07-07",
limit=10,
adjustment='raw').df
print(rawData)
order = api.submit_order(
symbol='KO',
qty=1,
side='buy',
type='market',
time_in_force='day',
)
print(order)