*Last updated: 2023-03-16.*
# tf_quant_finance.datetime.PeriodicSchedule
View source
Defines an array of dates specified by a regular schedule.
```python
tf_quant_finance.datetime.PeriodicSchedule(
*, start_date, end_date, tenor, holiday_calendar=None,
roll_convention=tf_quant_finance.datetime.BusinessDayConvention.NONE,
backward=False, end_of_month=False
)
```
#### Args:
* `start_date`: `DateTensor`. Defines the lower boundary of schedule. If
`backward=True` must be broadcastable to `end_date`, otherwise has
arbitrary shape.
* `end_date`: `DateTensor`. Defines the upper boundary of the schedule.
If `backward=False` must be broadcastable to `start_date`, otherwise has
arbitrary shape.
* `tenor`: `PeriodTensor`. Defines the frequency of the schedule. Must
be broadcastable to `start_date` if `backward=False`, and to `end_date`
if `backward=True`.
* `holiday_calendar`: `dates.HolidayCalendar`. If `None`, the dates in the
schedule will not be rolled to business days.
* `roll_convention`: BusinessDayConvention. Defines how dates in the schedule
should be rolled to business days if they fall on holidays. Ignored if
`holiday_calendar = None`.
Default value: BusinessDayConvention.NONE (i.e. no rolling).
* `backward`: Python `bool`. Whether to build the schedule from the
`start_date` moving forwards or from the `end_date` and moving
backwards.
* `end_of_month`: Python `bool`. If `True`, shifts all dates in schedule to
the ends of corresponding months, if `start_date` or `end_date` (
depending on `backward`) is at the end of a month. The shift is applied
before applying `roll_convention`. In the batched case, only those
schedules in a batch, whose corresponding `start_date` (or `end_date`)
are at ends of months, will be shifted.
#### Attributes:
* `end_date`
* `end_of_month`
* `generate_backwards`: Returns whether the schedule is generated from the end date.
* `holiday_calendar`
* `roll_convention`
* `start_date`
* `tenor`
## Methods
dates
View source
```python
dates()
```
Returns the dates as computed from the schedule as a DateTensor.
Constructs the date schedule from the supplied data. For more details see
the initializer docstring.
#### Returns:
`DateTensor` of rank one more than `start_date` or `end_date`
(depending on `backwards`), representing schedules for each element
of the input.