otp.Source.time_filter#

Source.time_filter(discard_on_match=False, start_time=0, end_time=0, day_patterns='', timezone=utils.default, end_time_tick_matches=False, inplace=False)#

Filters ticks by time.

Parameters:

  • discard_on_match (bool, optional) – If True, then ticks that match the filter will be discarded. Otherwise, only ticks that match the filter will be passed.

  • start_time (str or int or datetime.time, optional) – Start time of the filter, string must be in the format HHMMSSmmm or HH:MM:SS[.mmm]. Default value is 0.

  • end_time (str or int or datetime.time, optional) – End time of the filter, string must be in the format HHMMSSmmm or HH:MM:SS[.mmm]. To filter ticks for an entire day, this parameter should be set to 24:00:00. Default value is 0.

  • day_patterns (list or str) –

    Pattern or list of patterns that determines days for which the ticks can be propagated. A tick can be propagated if its date matches one or more of the patterns. Three supported pattern formats are:

    1. month.week.weekdays, 0 month means any month, 0 week means any week,

      6 week means the last week of the month for a given weekday(s), weekdays are digits for each day, 0 being Sunday.

    2. month/day, 0 month means any month.

    3. year/month/day, 0 year means any year, 0 month means any month.

  • timezone (str, optional) – Timezone of the filter. Default value is otp.config.tz or timezone set in the parameter of otp.run.

  • end_time_tick_matches (bool, optional) – If True, then the end time is inclusive. Otherwise, the end time is exclusive.

  • inplace (bool, optional) – 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. Default value is False.

  • self (Source)

Returns:

Returns None if inplace=True.

Return type:

Source or None

Examples

Filter ticks from 09:30:00 to 09:30:00.001:

>>> data = otp.DataSource(db='US_COMP_SAMPLE', tick_type='TRD', symbols='AAPL')
>>> data = data[['PRICE', 'SIZE']]
>>> data = data.time_filter(start_time='09:30:00', end_time='09:30:00.001')
>>> otp.run(data, date=otp.dt(2024, 2, 1))
                            Time   PRICE  SIZE
0  2024-02-01 09:30:00.000961260  184.01   302
1  2024-02-01 09:30:00.000961491  184.00   100
2  2024-02-01 09:30:00.000961701  184.00     1
3  2024-02-01 09:30:00.000973163  184.00     1
4  2024-02-01 09:30:00.000973355  184.00     5
5  2024-02-01 09:30:00.000973517  184.00     5
6  2024-02-01 09:30:00.000973674  184.00     5
7  2024-02-01 09:30:00.000980967  184.00     1
8  2024-02-01 09:30:00.000984514  184.00    10
9  2024-02-01 09:30:00.000984626  184.00     1
10 2024-02-01 09:30:00.000984730  184.00     1
11 2024-02-01 09:30:00.000989008  184.00     1
12 2024-02-01 09:30:00.000992129  184.00     2
13 2024-02-01 09:30:00.000994257  184.00     2
14 2024-02-01 09:30:00.000994541  184.00     3
15 2024-02-01 09:30:00.000996695  184.00    10
16 2024-02-01 09:30:00.000999752  184.00   100

Filter ticks from 09:30:00 to 09:30:00.005 every Monday:

>>> data = otp.DataSource(db='US_COMP_SAMPLE', tick_type='TRD', symbols='AAPL')
>>> data = data[['PRICE', 'SIZE']]
>>> data = data.time_filter(start_time='09:30:00', end_time='09:30:00.005', day_patterns='0.0.1')
>>> otp.run(data, start=otp.dt(2024, 2, 1), end=otp.dt(2024, 3, 1))
                           Time   PRICE  SIZE
0 2024-02-05 09:30:00.002470305  188.13    26
1 2024-02-05 09:30:00.003490655  188.15    26
2 2024-02-05 09:30:00.004413985  188.13     1
3 2024-02-12 09:30:00.004972167  188.41    50
4 2024-02-26 09:30:00.003312559  182.33   100
5 2024-02-26 09:30:00.003316234  182.33   100

See also

TIME_FILTER OneTick event processor