otp.agg.generic#

generic(query_fun, bucket_delimiter=False, bucket_interval=0, bucket_units='seconds', bucket_time='end', bucket_end_condition=None, running=False, group_by=None, end_condition_per_group=False, boundary_tick_bucket='new')#

Generic aggregation. Aggregation logic is provided in query_fun parameter and this logic is applied for ticks in each bucket. Currently, this aggregation can be used only with .apply() method.

Parameters

query_fun (Callable) – Function that takes Source as a parameter, applies some aggregation logic to it and returns Source as a result. Note that currently only methods that support dynamic symbol change could be used in the provided function. For example, rename() can’t be used. If you try to use such methods here, you will get an error during runtime.
bucket_delimiter (bool) – When set to True an extra tick is created after each bucket. Also, an additional column, called DELIMITER, is added to output ticks. The extra tick has values of all fields set to the defaults (0,NaN,””), except the delimiter field, which is set to “D” All other ticks have the DELIMITER set to string zero “0”.
bucket_interval (int) – Determines the length of each bucket (units depends on bucket_units).
bucket_units (Literal['seconds', 'ticks', 'days', 'months', 'flexible']) –
Set bucket interval units.

If set to flexible bucket_end_criteria must be set.
bucket_time (Literal['start', 'end']) –
Control output timestamp.
- start
  
  the timestamp assigned to the bucket is the start time of the bucket.
- end
  
  the timestamp assigned to the bucket is the end time of the bucket.
bucket_end_condition (condition) – An expression that is evaluated on every tick. If it evaluates to “True”, then a new bucket is created. This parameter is only used if bucket_units is set to “flexible”
running (bool) –
Aggregation will be calculated as sliding window. running and bucket_interval parameters determines when new buckets are created.
- running = True
  
  aggregation will be calculated in a sliding window.
  - bucket_interval = N (N > 0)
    
    Window size will be N. Output tick wil be generated when tick “enter” window (arrival event) and when “exit” window (exit event)
  - bucket_interval = 0
    
    Left boundary of window will be binded to start time. For each tick aggregation will be calculated in [start_time; tick_t].
- running = False
  
  buckets partition the [query start time, query end time) interval into non-overlapping intervals of size bucket_interval (with the last interval possibly of a smaller size). If bucket_interval is set to 0 a single bucket for the entire interval is created.
Default: False - create totally independent buckets. Number of buckets = (end - start) / bucket_interval’)
group_by (list, str or expression) – When specified, each bucket is broken further into additional sub-buckets based on specified field values.
end_condition_per_group (bool) –
Controls application of bucket_end_condition in groups.
- end_condition_per_group = True
  
  bucket_end_condition is applied only to the group defined by group_by
- end_condition_per_group = False
  
  bucket_end_condition applied across all groups
This parameter is only used if bucket_units is set to “flexible”
boundary_tick_bucket (Literal['new', 'previous']) –
Controls boundary tick ownership.
- previous
  
  A tick on which bucket_end_condition evaluates to “true” belongs to the bucket being closed.
- new
  
  tick belongs to the new bucket.
This parameter is only used if bucket_units is set to “flexible”

Note

Some functions may be not supported in query_fun. For example, join() and rename().

Examples

>>> data = otp.Ticks({'A': [1, 2, 3]})
>>> def agg_fun(source):
...     return source.agg({'X': otp.agg.count()})
>>> data = otp.agg.generic(agg_fun).apply(data)
>>> data()
        Time  X
0 2003-12-04  3