foundryts.functions.time_range

foundryts.functions.time_range(start=None, end=None)

Returns a function that filters a single time series to the specified time-range.

Each time-range acts as an individual series. Setting a time-range for your query makes them more efficient as your query will only read the points in the time-range, instead of all the points in the time series. This is also useful for doing operations on intervals of time series.

• Parameters:
  • start (int , str , datetime.datetime , optional) – Inclusive starting point of the time-range. Integers are interpreted as the number of nanoseconds. For more human-readable durations, you can provide a datetime.timedelta object or a string that will be parsed as a pandas.Timedelta. String inputs should follow the format recognized by pandas.to_timedelta, such as ‘1 day’, ‘1 hour’, ‘10 minutes’, or ’42s’. (default is the first point of the time series)
  • end (int , str , datetime.datetime , optional) – Exclusive end point of the time-range. Integers are interpreted as the number of nanoseconds. For more human-readable durations, you can provide a datetime.timedelta object or a string that will be parsed as a pandas.Timedelta. String inputs should follow the format recognized by pandas.to_timedelta, such as ‘1 day’, ‘1 hour’, ‘10 minutes’, or ’42s’. (default is the last point of the time series)
• Returns: A function that accepts a single time series as input and returns the filtered time-range.
• Return type: (FunctionNode) -> FunctionNode

Dataframe schema

Examples

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>>> series = F.points((1, 1.0), (101, 2.0), (200, 4.0), (201, 8.0), name="series")
>>> series.to_pandas()
                    timestamp  value
0 1970-01-01 00:00:00.000000001    1.0
1 1970-01-01 00:00:00.000000101    2.0
2 1970-01-01 00:00:00.000000200    4.0
3 1970-01-01 00:00:00.000000201    8.0

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>>> time_range = F.time_range(start=200, end=202)(series)
>>> time_range.to_pandas()
                      timestamp  value
0 1970-01-01 00:00:00.000000200    4.0
1 1970-01-01 00:00:00.000000201    8.0

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>>> smaller_time_range = F.time_range(start=200, end=201)(series)
>>> smaller_time_range.to_pandas()
                    timestamp  value
0 1970-01-01 00:00:00.000000200    4.0

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>>> unbounded_start_range = F.time_range(end=201)(series)
>>> unbounded_start_range.to_pandas()
                      timestamp  value
0 1970-01-01 00:00:00.000000001    1.0
1 1970-01-01 00:00:00.000000101    2.0
2 1970-01-01 00:00:00.000000200    4.0

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>>> unbounded_end_range = F.time_range(start=101)(series)
>>> unbounded_end_range.to_pandas()
                      timestamp  value
0 1970-01-01 00:00:00.000000101    2.0
1 1970-01-01 00:00:00.000000200    4.0
2 1970-01-01 00:00:00.000000201    8.0