ScheduleEveryDay
ScheduleEveryDay#
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class sigtech.framework.schedules.schedule.ScheduleEveryDay
Schedule class containing every day (weekends included).
Keyword arguments:
Start date.
End date.
delivery_kwargs
as inScheduleBase
class.
Example of object creation:
every_day = ScheduleEveryDay( date(2013, 10, 1), date(2013, 10, 10), )
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all_data_dates() list[datetime.date]
Return the timestamps of all data dates from
calculation_start_date
tocalculation_end_date
inclusive.
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all_data_ts() pandas.core.indexes.datetimes.DatetimeIndex
Return the timestamps of all data dates from
calculation_start_date
tocalculation_end_date
inclusive.
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all_reference_datetimes()
Timeseries indexed by data dates between start and end with corresponding reference times for that date.
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approximate_holidays() str
A possibly not exact holiday set for this schedule.
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calculation_end_date() datetime.date
Return the date on which the calculation of all data dates ends.
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calculation_end_ts() pandas._libs.tslibs.timestamps.Timestamp
Date on which calculation of all data dates ends.
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calculation_start_date() datetime.date
Return the date on which the calculation of all data dates starts.
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calculation_start_ts() pandas._libs.tslibs.timestamps.Timestamp
Date on which calculation of all data dates starts.
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current_next_data_date(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) datetime.date
Returns the first data date on or after the input date.
- Parameters
d – Input date, datetime or timestamp.
- Returns
date.
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current_next_data_ts(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) pandas._libs.tslibs.timestamps.Timestamp
Return the first data date on or after date
d
.- Parameters
d – Input date, datetime or timestamp.
- Returns
pandas
Timestamp
.
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current_previous_data_date(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) datetime.date
Returns the first data date on or before the input date.
- Parameters
d – Input date, datetime or timestamp.
- Returns
date.
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current_previous_data_ts(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) pandas._libs.tslibs.timestamps.Timestamp
Return the first data date on or before date
d
.- Parameters
d – Input date, datetime or timestamp.
- Returns
pandas
Timestamp
.
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data_dates(start: Optional[Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]] = None, end: Optional[Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]] = None) list[Union[datetime.datetime, datetime.date]]
List of value dates for which data is published between start and end dates inclusive.
- Parameters
start – Start date, datetime or timestamp.
end – End date, datetime ot timestamp.
- Returns
date or datetime.
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data_ts(start: Optional[Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]] = None, end: Optional[Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]] = None) pandas.core.indexes.datetimes.DatetimeIndex
List of value dates for which data is published between start and end dates inclusive.
- Parameters
start – Start date, datetime or timestamp.
end – End date, datetime ot timestamp.
- Returns
pandas
DatetimeIndex
.
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date_increment(d: datetime.date, n: int) Any
Move a given date
d
exactlyn
business days forward or backward.- Parameters
d – Input date.
n – Number of business days for bump.
- Returns
New bumped date from the input date.
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delivery_kwargs()
Return a dict containing the class attributes.
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dependencies(input_dependency: sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency, valuation_currency: Optional[str] = None, use_start: bool = False) list[sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency]
Dependencies of this schedule
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end_date() datetime.date
Return the last date on which data will be available, typically
date.max
if no end date is set.
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end_ts() pandas._libs.tslibs.timestamps.Timestamp
The last date on which data will be available, typically
date.max
if no end date is set.
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get_exact_business_dates(d: datetime.date, n: int) list[datetime.date]
Return
n
business days after dated
.- Parameters
d – Start date.
n – Number of days.
- Returns
List of dates.
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is_data_date(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) bool
Return True if the input date is part of the schedule, otherwise False.
- Parameters
d – Input date, datetime or timestamp.
- Returns
bool.
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is_data_ts(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) bool
Return True if the input date is part of the schedule, otherwise False.
- Parameters
d – Input date, datetime or timestamp.
- Returns
bool.
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next_data_date(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) datetime.date
Return the first data date after the input date.
- Parameters
d – Input date, datetime or timestamp.
- Returns
date.
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next_data_ts(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) pandas._libs.tslibs.timestamps.Timestamp
Return the first data date after the input date.
- Parameters
d – Input date, datetime or timestamp.
- Returns
pandas
Timestamp
.
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prev_reference_date(d: datetime.date) datetime.date
Return the past delivery date for the input date.
- Parameters
d – Input date.
- Returns
date.
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prev_reference_datetime(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) pandas._libs.tslibs.timestamps.Timestamp
Return the past delivery datetime for the input date.
- Parameters
d – Input date, datetime or timestamp.
- Returns
pandas
Timestamp
.
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previous_data_date(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) datetime.date
Return the first data date prior to the input date.
- Parameters
d – Input date, datetime or timestamp.
- Returns
date.
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previous_data_ts(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) pandas._libs.tslibs.timestamps.Timestamp
Return the first data date prior to the input date.
- Parameters
d – Input date, datetime or timestamp.
- Returns
pandas
Timestamp
.
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reference_datetime(d: Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]) pandas._libs.tslibs.timestamps.Timestamp
Return the delivery datetime for the input date.
- Parameters
d – Input date, datetime or timestamp.
- Returns
pandas
Timestamp
.
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reference_datetimes(start: Optional[Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]] = None, end: Optional[Union[datetime.date, datetime.datetime, pandas._libs.tslibs.timestamps.Timestamp]] = None)
Return the reference datetimes restricted to data dates between start and end inclusive.
- Parameters
start – Input date, datetime or timestamp (optional).
end – Input date, datetime or timestamp (optional).
- Returns
pandas Series.
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start_date() datetime.date
The first date on which data will be available.
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start_ts() pandas._libs.tslibs.timestamps.Timestamp
The first date on which data will be available.