def run(self):
"""Starts the algo
Connects to the Blotter, processes market data and passes
tick data to the ``on_tick`` function and bar data to the
``on_bar`` methods.
"""
# -----------------------------------
# backtest mode?
if self.backtest:
if self.output is None:
print("ERROR: Must provide an output file for backtesting mode")
sys.exit(0)
if self.backtest_start is None:
print("ERROR: Must provide start date for backtesting mode")
sys.exit(0)
if self.backtest_end is None:
self.backtest_end = datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
# backtest history
self.blotter.drip(
symbols = self.symbols,
start = self.backtest_start,
end = self.backtest_end,
resolution = self.resolution,
tz = self.timezone,
quote_handler = self._quote_handler,
tick_handler = self._tick_handler,
bar_handler = self._bar_handler
)
# -----------------------------------
# live data mode
else:
# preload history
if self.preload is not None:
try: # dbskip may be active
self.bars = self.blotter.history(
symbols = self.symbols,
start = tools.backdate(self.preload),
resolution = self.resolution,
tz = self.timezone
)
except:
pass
# print(self.bars)
# add instruments to blotter in case they do not exist
self.blotter.register(self.instruments)
# listen for RT data
self.blotter.listen(
symbols = self.symbols,
tz = self.timezone,
quote_handler = self._quote_handler,
tick_handler = self._tick_handler,
bar_handler = self._bar_handler
)
def trades(self, start=None, end=None, algo_id=None, json=True):
if algo_id is not None:
algo_id = algo_id.replace('/', '')
if start is not None:
start = start.replace('/', '')
if end is not None:
end = end.replace('/', '')
if start is None:
start = tools.backdate("7D", date=None, as_datetime=False)
trades_query = "SELECT * FROM trades WHERE exit_time IS NOT NULL"
trades_where = []
if isinstance(start, str):
trades_where.append("entry_time>='" + start + "'")
if isinstance(end, str):
trades_where.append("exit_time<='" + end + "'")
if algo_id is not None:
trades_where.append("algo='" + algo_id + "'")
if len(trades_where) > 0:
trades_query += " AND " + " AND ".join(trades_where)
trades = pd.read_sql(trades_query, self.dbconn)
trades['exit_time'].fillna(0, inplace=True)
trades['slippage'] = abs(trades['entry_price'] -
trades['market_price'])
trades['slippage'] = np.where(
((trades['direction'] == "LONG") &
(trades['entry_price'] > trades['market_price'])) |
((trades['direction'] == "SHORT") &
(trades['entry_price'] < trades['market_price'])),
-trades['slippage'], trades['slippage'])
trades = trades.sort_values(['exit_time', 'entry_time'],
ascending=[False, False])
trades = trades.to_dict(orient="records")
if json:
return jsonify(trades)
else:
return trades
def trades(self, start=None, end=None, algo_id=None, json=True):
if algo_id is not None:
algo_id = algo_id.replace('/', '')
if start is not None:
start = start.replace('/', '')
if end is not None:
end = end.replace('/', '')
if start is None:
start = tools.backdate("7D", date=None, as_datetime=False)
trades_query = "SELECT * FROM trades WHERE exit_time IS NOT NULL"
trades_where = []
if isinstance(start, str):
trades_where.append("entry_time>='" + start + "'")
if isinstance(end, str):
trades_where.append("exit_time<='" + end + "'")
if algo_id is not None:
trades_where.append("algo='" + algo_id + "'")
if len(trades_where) > 0:
trades_query += " AND " + " AND ".join(trades_where)
trades = pd.read_sql(trades_query, self.dbconn)
trades['exit_time'].fillna(0, inplace=True)
trades['slippage'] = abs(trades['entry_price'] - trades['market_price'])
trades['slippage'] = np.where(
((trades['direction'] == "LONG") & (trades['entry_price'] > trades['market_price'])) |
((trades['direction'] == "SHORT") & (trades['entry_price'] < trades['market_price'])),
-trades['slippage'], trades['slippage'])
trades = trades.sort_values(['exit_time', 'entry_time'], ascending=[False, False])
trades = trades.to_dict(orient="records")
if json:
return jsonify(trades)
else:
return trades
def bars(self, resolution, symbol, start=None, end=None, json=True):
if start is not None:
start = start.replace('/', '')
if end is not None:
end = end.replace('/', '')
if start is None:
start = tools.backdate("7D", date=None, as_datetime=False)
bars = self.blotter.history(symbols=symbol,
start=start,
end=end,
resolution=resolution)
bars['datetime'] = bars.index
bars = bars.to_dict(orient="records")
if json:
return jsonify(bars)
return bars
def bars(self, resolution, symbol, start=None, end=None, json=True):
if start is not None:
start = start.replace('/', '')
if end is not None:
end = end.replace('/', '')
if start is None:
start = tools.backdate("7D", date=None, as_datetime=False)
bars = self.blotter.history(
symbols = symbol,
start = start,
end = end,
resolution = resolution
)
bars['datetime'] = bars.index
bars = bars.to_dict(orient="records")
if json:
return jsonify(bars)
else:
return bars
def run(self):
"""Starts the algo
Connects to the Blotter, processes market data and passes
tick data to the ``on_tick`` function and bar data to the
``on_bar`` methods.
"""
history = pd.DataFrame()
# get history from csv dir
if self.backtest and self.backtest_csv:
kind = "TICK" if self.resolution[-1] in ("K", "V") else "BAR"
dfs = []
for symbol in self.symbols:
file = "%s/%s.%s.csv" % (self.backtest_csv, symbol, kind)
if not os.path.exists(file):
self.log_algo.error("Can't load data for %s (%s doesn't exist)" % (symbol, file))
sys.exit(0)
try:
df = pd.read_csv(file)
if "expiry" not in df.columns or not validate_csv_columns(df, kind, raise_errors=False):
self.log_algo.error("%s Doesn't appear to be a QTPyLib-compatible format" % file)
sys.exit(0)
if df['symbol'].values[-1] != symbol:
self.log_algo.error("%s Doesn't content data for %s" % (file, symbol))
sys.exit(0)
dfs.append(df)
except:
self.log_algo.error("Error reading data for %s (%s)" % (symbol, file))
sys.exit(0)
history = prepare_history(
data = pd.concat(dfs),
resolution = self.resolution,
tz = self.timezone,
continuous = self.continuous
)
history = history[history.index >= self.backtest_start]
elif not self.blotter_args["dbskip"] and (self.backtest or self.preload):
start = self.backtest_start if self.backtest else tools.backdate(self.preload)
end = self.backtest_end if self.backtest else None
history = self.blotter.history(
symbols = self.symbols,
start = start,
end = end,
resolution = self.resolution,
tz = self.timezone,
continuous = self.continuous
)
# history needs backfilling?
# self.blotter.backfilled = True
if not self.blotter.backfilled:
# "loan" Blotter our ibConn
self.blotter.ibConn = self.ibConn
# call the back fill
self.blotter.backfill(data=history, resolution=self.resolution, start=start, end=end)
# re-get history from db
history = self.blotter.history(
symbols = self.symbols,
start = start,
end = end,
resolution = self.resolution,
tz = self.timezone,
continuous = self.continuous
)
# take our ibConn back :)
self.blotter.ibConn = None
if self.backtest:
# initiate strategy
self.on_start()
# drip history
self.blotter.drip(history,
self._tick_handler if self.resolution[-1] in ("K", "V") else self._bar_handler)
else:
# place history self.bars
self.bars = history
# add instruments to blotter in case they do not exist
self.blotter.register(self.instruments)
# initiate strategy
self.on_start()
# listen for RT data
self.blotter.stream(
symbols = self.symbols,
tz = self.timezone,
quote_handler = self._quote_handler,
tick_handler = self._tick_handler,
bar_handler = self._bar_handler,
book_handler = self._book_handler
)
