date_time#

predict_backend.utils.date_time.create_cron_description(schedule_meta, use_24hour_time_format=True)#

Creates a cron description in plain English

Parameters:

  • schedule_meta (Dict) – dict, a ScheduleSchema object

  • use_24hour_time_format (bool) – bool, whether to use 24-hour time format, default True

Returns:

A string of the cron description, for example: ‘At 12:00 only on Sunday’

predict_backend.utils.date_time.create_date_range_data_frame(start_date, end_date, interval_length_seconds=3600, interval_column_name='time', zero_minutes=True, zero_seconds=True)#

Creates a data range from provided start and end dates, with custom intervals

Parameters:

  • start_date (datetime) – datetime, the start date of the range

  • end_date (datetime) – datetime, the end date of the range

  • interval_length_seconds (Optional[int]) – the interval length in seconds, default 3600

  • interval_column_name (Optional[str]) – the interval column ame, default “time”

  • zero_minutes (Optional[bool]) – bool, whether to start the start date seconds and microseconds at 0 seconds, default True

  • zero_seconds (Optional[bool]) – bool, whether to start the start date at minute 0, default True

Returns:

A Pandas dataframe

predict_backend.utils.date_time.cron_string_from_kwargs(use_seconds, second, minute, hour, day, month, day_of_week, year, **kwargs)#

Gets a cron formatted string from args

Parameters:

  • use_seconds (:param) – bool, Whether to have seconds at the start of the cron string

  • second (str) – str, the second of the cron string

  • minute (str) – str, the minute of the cron string

  • hour (str) – str, the hour of the cron string

  • day (str) – str, the day of the cron string

  • month (str) – str, the month of the cron string

  • day_of_week (str) – str, the day of the week of the cron string

  • year (str) – str, the year of the cron string

  • **kwargs –

    Allows providing the time args as a dict instead of individual arguments

:return:A cron formatted string

predict_backend.utils.date_time.get_unix_ms_series(series, timezone='UTC', remove_local=False)#

Takes a data series and converts the timezone to the provided one, and can remove the local timezone if needed

Parameters:

  • series – Pandas dataframe series, for example data_frame[col]

  • timezone – str, The timezone to translate to

  • remove_local – bool, whether to set the time to naive local time

Returns:

A data series