otp.Source.ob_snapshot#

Source.ob_snapshot(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_shares=None, max_depth_for_price=None, book_uncross_method=None, dq_events_that_clear_book=None, identify_source=False, show_full_detail=False, show_only_changes=False, book_delimiters=None, max_initialization_days=1, state_key_max_inactivity_sec=None, size_max_fractional_digits=0)#

Returns the order book state at the end of each bucket interval: the price, the size, the side, and the time of the last update for a specified number of order book levels.

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 (Union[int, onetick.py.core.column_operations.base.Operation], default=0) –
Determines the length of each bucket (units depends on bucket_units).

If Operation passed, acts as bucket_end_condition.
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_shares (int, default=None) – The total number of shares (i.e., the combined SIZE across top several levels of the book) that determines the number of order book levels that need to be part of the order book computation. If that number of levels exceeds max_levels, only max_levels levels of the book will be computed. The shares in excess of max_depth_shares, from the last included level, are not taken into account.
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.
identify_source (bool, default=False) – When this parameter is set to “true” and the input stream is fed through the VIRTUAL_OB event processor (with the QUOTE_SOURCE_FIELDS parameter specified) and group_by is not set to be “SOURCE” it will separate a tick with the same price from different sources into multiple ticks. The parameter can also be used when merging ticks from multiple feeds. Each feed going into the merge would need an ADD_FIELD EP source value set for the VALUE parameter, where the value would be different for each leg.
show_full_detail (bool, default=False) – When set to “true” and if the state key of the input ticks consists of some fields besides PRICE, output ticks will contain all fields from the input ticks for each price level. When set to “false” only PRICE, UPDATE_TIME, SIZE, LEVEL, and BUY_SELL_FLAG fields will be populated. Note: setting this flag to “true” has no effect on a time series that does not have a state key.
show_only_changes (bool, default=False) –
When set to true, the output stream carries only changes to the book. The representation is as follows:
- Changed and added levels are represented by themselves.
- Deleted levels are shown with a size and level of zero.
As with other modes, correct detection of update boundaries may require setting the book_delimiters option.
book_delimiters (Literal['D'], default=None) – When set to “D” an extra tick is created after each book. 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 zero (0).
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.
state_key_max_inactivity_sec (int, default=None) – If set, specifies in how many seconds after it was added a given state key should be automatically removed from the book.
size_max_fractional_digits (int, default=0) – Specifies maximum number of digits after dot in SIZE, if SIZE can be fractional.

Return type

Source

Examples

>>> data = otp.DataSource(db='SOME_DB', tick_type='PRL', symbols='AA')  
>>> data = data.ob_snapshot(max_levels=1)  
>>> otp.run(data) 
Time  PRICE             UPDATE_TIME  SIZE  LEVEL  BUY_SELL_FLAG
0 2003-12-04    2.0 2003-12-01 00:00:00.003     6      1              1
1 2003-12-04    5.0 2003-12-01 00:00:00.004     7      1              0