Variables and Data Structures

import onetick.py as otp

You can use variables to keep track of state across ticks. The example below shows how you may keep track of P&L.

# set some defaults
from datetime import datetime
otp.config['default_start_time'] = datetime(2003, 12, 1, 0, 0, 0)
otp.config['default_end_time'] = datetime(2003, 12, 4, 0, 0, 0)
otp.config['default_db'] = 'DEMO_L1'
otp.config['default_symbol'] = 'AAPL'

ticks = otp.Ticks({"PRICE": [13.5, 13.6, 13.3, 14.0],
                   "QTY"  : [ 200,  100,  150, 200],
                   "SIDE"   : [ "B",  "S",  "B", "S"]})

ticks.state_vars["PROFIT"] = 0
ticks.state_vars["PROFIT"] += ticks.apply(lambda t:
    t["PRICE"] * t["QTY"] if t["SIDE"] == "S" else
    - t["PRICE"] * t["QTY"])

ticks["PROFIT"] = ticks.state_vars["PROFIT"]

otp.run(ticks)

	Time	PRICE	QTY	SIDE	PROFIT
0	2003-12-01 00:00:00.000	13.5	200	B	-2700
1	2003-12-01 00:00:00.001	13.6	100	S	-1340
2	2003-12-01 00:00:00.002	13.3	150	B	-3335
3	2003-12-01 00:00:00.003	14.0	200	S	-535

Another use case is to store the value from the last tick during aggregation / grouping.

q = otp.Ticks(X=[-1, 3, -3, 4, 2], Y=[0, 1, 1, 0, 3])
q.state_vars["S"] = 0
q.state_vars["S"] = q["X"]
q = q.high("X", group_by=["Y"])
q["S"] = q.state_vars["S"]
otp.run(q)

	Time	X	Y	S
0	2003-12-01 00:00:00.001	3	1	2
1	2003-12-01 00:00:00.003	4	0	2
2	2003-12-01 00:00:00.004	2	3	2