otp.Source.limit#

Source.limit(tick_limit, tick_offset=None, inplace=False)#

Propagates ticks until the count limit is reached.

Once the limit is reached, hidden ticks will still continue to propagate until the next regular tick appears.

Parameters

tick_limit (int) – The number of regular ticks to propagate. Must be a non-negative integer or -1, which means no limit.
tick_offset (int) – The number of regular ticks to skip before starting to propagate. Must be a non-negative integer. By default no ticks are skipped.
inplace (bool) – The flag controls whether operation should be applied inplace or not. If inplace=True, then it returns nothing. Otherwise method returns a new modified object.
self (Source) –

Return type

Source or None

Examples

Simple example, get first 3 ticks:

data = otp.Ticks(X=[1, 2, 3, 4, 5, 6])
data = data.limit(3)
df = otp.run(data)
print(df)

                     Time  X
2003-12-01 00:00:00.000  1
2003-12-01 00:00:00.001  2
2003-12-01 00:00:00.002  3

Disable limit by setting it to -1:

data = otp.Ticks(X=[1, 2, 3, 4, 5, 6])
data = data.limit(-1)
df = otp.run(data)
print(df)

                     Time  X
2003-12-01 00:00:00.000  1
2003-12-01 00:00:00.001  2
2003-12-01 00:00:00.002  3
2003-12-01 00:00:00.003  4
2003-12-01 00:00:00.004  5
2003-12-01 00:00:00.005  6

Setting parameter tick_offset can be used to skip first ticks before propagating them.

For example, we can skip first 2 ticks and propagate all other:

data = otp.Ticks(X=[1, 2, 3, 4, 5, 6])
data = data.limit(-1, tick_offset=2)
df = otp.run(data)
print(df)

                     Time  X
2003-12-01 00:00:00.002  3
2003-12-01 00:00:00.003  4
2003-12-01 00:00:00.004  5
2003-12-01 00:00:00.005  6

Or we can return ticks from the middle of the stream by skipping first 2 ticks and then returning next 2 ticks like this:

data = otp.Ticks(X=[1, 2, 3, 4, 5, 6])
data = data.limit(2, tick_offset=2)
df = otp.run(data)
print(df)

                     Time  X
0 2003-12-01 00:00:00.002  3
1 2003-12-01 00:00:00.003  4