otp.agg.ob_size#

ob_size(running=False, bucket_interval=0, bucket_time='end', bucket_units=None, bucket_end_condition=None, end_condition_per_group=False, group_by=None, side=None, max_levels=None, max_depth_for_price=None, book_uncross_method=None, dq_events_that_clear_book=None, max_initialization_days=1, best_ask_price_field=None, best_bid_price_field=None)#

Returns the total size for a specified number of order book levels at the end of each bucket interval.

Parameters

running (bool, default=False) –
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 will be generated when tick “enter” window (arrival event) and when “exit” window (exit event)
  - bucket_interval = 0
    
    Left boundary of window will be bound 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.
  
  Note that in non-running mode OneTick unconditionally divides the whole time interval into specified number of buckets. It means that you will always get this specified number of ticks in the result, even if you have less ticks in the input data.
Default: False
bucket_interval (int or Operation or OnetickParameter or symbol parameter or datetime offset object, default=0) –
Determines the length of each bucket (units depends on bucket_units).

If Operation of bool type is passed, acts as bucket_end_condition.

Bucket interval can be set via datetime offset objects like otp.Second, otp.Minute, otp.Hour, otp.Day, otp.Month. In this case you could omit setting bucket_units parameter.

Bucket interval can also be set with integer OnetickParameter or symbol parameter.
bucket_time (Literal['start', 'end'], default=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_units (Optional[Literal['seconds', 'ticks', 'days', 'months', 'flexible']], default=None) –
Set bucket interval units.

By default, if bucket_units and bucket_end_condition not specified, set to seconds. If bucket_end_condition specified, then bucket_units set to flexible.

If set to flexible then bucket_end_condition must be set.

Note that seconds bucket unit doesn’t take into account daylight-saving time of the timezone, so you may not get expected results when using, for example, 24 * 60 * 60 seconds as bucket interval. In such case use days bucket unit instead. See example in onetick.py.agg.sum().
bucket_end_condition (condition, default=None) –
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”.

Also can be set via bucket_interval parameter by passing Operation object.
end_condition_per_group (bool, default=False) –
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”.

When set to True, applies to all bucketing conditions. Useful, for example, if you need to specify group_by, and you want to group items first, and create buckets after that.
group_by (list, str or expression, default=None) – When specified, each bucket is broken further into additional sub-buckets based on specified field values. If Operation is used then GROUP_{i} column is added. Where i is index in group_by list. For example, if Operation is the only element in group_by list then GROUP_0 field will be added.
side (Literal['ASK', 'BID'], default=None) – Specifies whether the function is to be applied to sell orders (ASK), buy orders (BID), or both (empty).
max_levels (int, default=None) – Number of order book levels (between 1 and 100_000) that need to be computed. If empty, all levels will be computed.
max_depth_for_price (float, default=None) – The multiplier, product of which with the price at the top level of the book determines maximum price distance from the top of the book for the levels that are to be included into the book. In other words, only bids at <top_price>*(1-max_depth_for_price) and above and only asks of <top_price>*(1+`max_depth_for_price`) and less will be returned. If the number of the levels that are to be included into the book, according to this criteria, exceeds max_levels, only max_levels levels of the book will be returned.
book_uncross_method (Literal['REMOVE_OLDER_CROSSED_LEVELS'], default=None) – When set to “REMOVE_OLDER_CROSSED_LEVELS”, all ask levels that have price lower or equal to the price of a new bid tick get removed from the book, and all bid levels that have price higher or equal to the price of a new ask tick get removed from the book.
dq_events_that_clear_book (List[str], default=None) – A list of names of data quality events arrival of which should clear the order book.
max_initialization_days (int, default=1) – This parameter specifies how many days back book event processors should go in order to find the latest full state of the book. The query will not go back resulting number of days if it finds initial book state earlier. When book event processors are used after VIRTUAL_OB EP, this parameter should be set to 0. When set, this parameter takes precedence over the configuration parameter BOOKS.MAX_INITIALIZATION_DAYS.
best_ask_price_field (Union[str, onetick.py.core.column.Column], default=None) – If specified, this parameter represents the name of the field value of which represents the lowest ask price starting from which the book ask size is to be computed. This value would also be used as the top price, relative to which max_depth_for_price would be computed.
best_bid_price_field (Union[str, onetick.py.core.column.Column], default=None) – If specified, this parameter represents the name of the field value of which represents the highest bid price starting from which the book bid size is to be computed. This value would also be used as the top price, relative to which max_depth_for_price would be computed.

Examples

Basic example

>>> data = otp.DataSource(db='SOME_DB', tick_type='PRL', symbols='AA')  
>>> data = otp.agg.ob_size(bucket_interval=otp.Second(300), max_levels=10).apply(data)  
>>> otp.run(data) 
                     Time  ASK_VALUE  BID_VALUE
0 2003-12-01 00:05:00.000     194800      47200
1 2003-12-01 00:10:00.000     194800      47200
2 2003-12-01 00:15:00.000     313400       7700
...

Selecting side via side parameter

>>> data = otp.DataSource(db='SOME_DB', tick_type='PRL', symbols='AA')  
>>> data = otp.agg.ob_size(bucket_interval=otp.Second(300), max_levels=10, size='ASK').apply(data)  
>>> otp.run(data) 
                     Time   VALUE
0 2003-12-01 00:05:00.000  194800
1 2003-12-01 00:10:00.000  194800
2 2003-12-01 00:15:00.000  313400
...