otp.agg.multi_portfolio_price#
- agg.multi_portfolio_price(columns='PRICE', running=False, bucket_interval=0, bucket_time='end', bucket_units=None, bucket_end_condition=None, end_condition_per_group=False, boundary_tick_bucket='new', group_by=None, groups_to_display='all', weight_field_name='', weight_multiplier_field_name='', side='both', weight_type='absolute', portfolios_query_params='', portfolio_value_field_name='VALUE', symbols=None)#
- MULTI_PORTFOLIO_PRICEaggregation.- For each bucket, computes weighted portfolio price for multiple portfolios. - Parameters
- portfolios_query (str, - Source) –- A mandatory parameter that the specifies server-side .otq file that is expected to return mandatory columns - PORTFOLIO_NAMEand- SYMBOL_NAME, as well as an optional columns- WEIGHT,- FX_SYMBOL_NAMEand- FX_MULTIPLY.- For a local OneTick server you can pass otp.Source objects. 
- columns (str or list of Column or str, default=PRICE) – - A list of the names of the input fields for which portfolio value is computed. - Could be set as a comma-separated list of the names or - listof name strings/- Columnsobjects.
- running (bool, default=False) – - See Aggregation buckets guide to see examples of how this parameter works. - Specifies if the aggregation will be calculated as a sliding window. - runningand- bucket_intervalparameters 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 set to query start time. For each tick aggregation will be calculated in the interval [start_time; tick_t] from query start time to the tick’s timestamp (inclusive). 
 
- running= False (default)- 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_intervalis 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 float or - Operationor- OnetickParameteror- symbol parameteror datetime offset object, default=0) –- Determines the length of each bucket (units depends on - bucket_units).- If - Operationof bool type is passed, acts as- bucket_end_condition.- Bucket interval can also be set as a float value if - bucket_unitsis set to seconds. Note that values less than 0.001 (1 millisecond) are not supported.- Bucket interval can be set via some of the datetime offset objects: - otp.Milli,- otp.Second,- otp.Minute,- otp.Hour,- otp.Day,- otp.Month. In this case you could omit setting- bucket_unitsparameter.- Bucket interval can also be set with integer - OnetickParameteror- 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_unitsand- bucket_end_conditionnot specified, set to seconds. If- bucket_end_conditionspecified, then- bucket_unitsset to flexible.- If set to flexible then - bucket_end_conditionmust 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_unitsis set to “flexible”.- Also can be set via - bucket_intervalparameter by passing- Operationobject.
- end_condition_per_group (bool, default=False) – - Controls application of - bucket_end_conditionin groups.- end_condition_per_group= True- bucket_end_conditionis applied only to the group defined by- group_by
- end_condition_per_group= False- bucket_end_conditionapplied across all groups
 - This parameter is only used if - bucket_unitsis 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.
- boundary_tick_bucket (Literal['new', 'previous'], default=new) – - Controls boundary tick ownership. - previous - A tick on which - bucket_end_conditionevaluates to “true” belongs to the bucket being closed.
- new - tick belongs to the new bucket. 
 - This parameter is only used if - bucket_unitsis set to “flexible”
- 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 - Operationis 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_bylist then GROUP_0 field will be added.
- groups_to_display (Literal['all', 'previous'], default=all) – Specifies for which sub-buckets (groups) ticks should be shown for each bucket interval. By default all groups are shown at the end of each bucket interval. If this parameter is set to event_in_last_bucket, only the groups that received at least one tick within a given bucket interval are shown. 
- weight_field_name (Optional, str or Column, default=) – - The name of the field that contains the current value of weight for a member of the portfolio that contributed the tick. - You can also specify weight through the value of symbol parameter - WEIGHT.- If - weight_field_nameis specified, all ticks should have the field pointed by this parameter and the value of this field is used as the weight.- If weights are not specified in any of these ways, and you are running a single-stage query, the weights take the default value - 1.
- weight_multiplier_field_name (str, default=) – Name of the field, value from which is used for multiplying portfolio value result. 
- side (Literal['long', 'short', 'both'], default=both) – - When set to long, the price of the portfolio is computed only for the input time series with - weight > 0.- When set to short, the price of the portfolio is computed only for the input time series with - weight < 0.- When set to both, the price of the portfolio is computed for all input time series. 
- weight_type (Literal['absolute', 'relative'], default=absolute) – - When set to - absolute, the portfolio price is computed as the sum of- input_field_value*weightacross all members of the portfolio.- When set to - relative, the portfolio price is computed as the sum of- input_field_value*weight/sum_of_all_weightsacross all members of the portfolio.
- portfolios_query_params (Union[str, Dict[str, str]], default=) – An optional parameter that specifies parameters of the query specified in portfolios_query. 
- portfolio_value_field_name (Union[str, List[Union[str, onetick.py.core.column.Column]]], default=VALUE) – - List of the names (string with comma-separated list or - listof strings/- Columns) of the output fields which contain computed values of the portfolio.- The number of the field names must match the number of the field names listed in the columns parameter. 
- symbols (str, list of str, - Source,- query,- eval query,- onetick.query.GraphQuery., default=None) – Symbol(s) from which data should be taken.
 
 - Examples - Basic example, by default this EP takes - PRICEcolumn as input- >>> data = otp.DataSource( ... 'US_COMP', tick_type='TRD', date=otp.dt(2022, 3, 1) ... ) >>> data = data.multi_portfolio_price( ... portfolios_query='some_query.otq::portfolios_query', ... symbols=['US_COMP::AAPL', 'US_COMP::MSFT', 'US_COMP::ORCL'], ... ) >>> otp.run(data) Time VALUE NUM_SYMBOLS PORTFOLIO_NAME 0 2003-12-01 95.0 3 PORTFOLIO_1 1 2003-12-01 47.5 1 PORTFOLIO_2 2 2003-12-01 32.5 2 PORTFOLIO_3 - Override - weightreturned by- portfolios_querywith- weight_field_name- >>> data = otp.DataSource( ... 'US_COMP', tick_type='TRD', date=otp.dt(2022, 3, 1) ... ) >>> data['WEIGHT'] = 2 >>> data = data.multi_portfolio_price( ... portfolios_query='some_query.otq::portfolios_query', ... weight_field_name='WEIGHT', ... symbols=['US_COMP::AAPL', 'US_COMP::MSFT', 'US_COMP::ORCL'], ... ) >>> otp.run(data) Time VALUE NUM_SYMBOLS PORTFOLIO_NAME 0 2003-12-01 38.0 3 PORTFOLIO_1 1 2003-12-01 19.0 1 PORTFOLIO_2 2 2003-12-01 13.0 2 PORTFOLIO_3 - Pass parameters to the query from - portfolios_queryvia- portfolios_query_params- >>> data = otp.DataSource( ... 'US_COMP', tick_type='TRD', date=otp.dt(2022, 3, 1) ... ) >>> data = data.multi_portfolio_price( ... portfolios_query='some_query.otq::portfolios_query_with_param', ... symbols=['US_COMP::AAPL', 'US_COMP::MSFT', 'US_COMP::ORCL'], ... portfolios_query_params={'PORTFOLIO_1_NAME': 'CUSTOM_NAME'} ... ) >>> otp.run(data) Time VALUE NUM_SYMBOLS PORTFOLIO_NAME 0 2003-12-01 95.0 3 CUSTOM_NAME 1 2003-12-01 47.5 1 PORTFOLIO_2 2 2003-12-01 32.5 2 PORTFOLIO_3 - Use - otp.Sourceobject as- portfolios_query(only for local queries)- >>> portfolios = otp.Ticks( ... SYMBOL_NAME=['US_COMP::AAPL', 'US_COMP::MSFT', 'US_COMP::AAPL'], ... PORTFOLIO_NAME=['PORTFOLIO_1', 'PORTFOLIO_1', 'PORTFOLIO_2'], ... WEIGHT=[1, 1, 2], ... ) >>> data = otp.DataSource( ... 'US_COMP', tick_type='TRD', date=otp.dt(2022, 3, 1) ... ) >>> data = data.multi_portfolio_price( ... portfolios_query=portfolios, ... symbols=['US_COMP::AAPL', 'US_COMP::MSFT'], ... ) >>> otp.run(data) Time VALUE NUM_SYMBOLS PORTFOLIO_NAME 0 2003-12-01 47.5 2 PORTFOLIO_1 1 2003-12-01 46.0 1 PORTFOLIO_2 - See also - MULTI_PORTFOLIO_PRICE OneTick event processor